Operations | Monitoring | ITSM | DevOps | Cloud

What Anthropic's 6:1 AI Work Ratio Means for Every Business

Anthropic's AI agents are logging 6x more hours than the humans directing them. Is this the beginning of a fundamental shift in how businesses operate? New data from Anthropic reveals how AI agents are transforming the workforce, accelerating software development, and changing what employees actually do every day. But the biggest story isn't just AI productivity. It's what happens next.

Why web application security needs a multi-layered approach

The recent PHP security emergency has highlighted how vulnerabilities in widely used web technologies can quickly become a significant cybersecurity concern. It is also a reminder that protecting internet-facing applications requires more than keeping software up to date. Organisations need a layered security strategy to protect applications, maintain availability and mitigate malicious traffic.

What Is Real-Time Agent Assist, and How Does It Cut Escalation Time?

When a ticket reaches an experienced technician, the issue is supposed to be closer to resolution. Too often, the escalation starts the investigation again. The technician reads the history, checks what L1 attempted, opens the CMDB, searches past incidents, and pulls logs. The fix itself may take two minutes, but reconstructing the situation can take far longer. Real-time agent assist targets that gap.

From Laptop to Production: A Technical Teardown of the Komodor Agentic Operations Platform

An agent that works on your laptop is borrowing three things it doesn’t own: your identity, your attention, and your judgment. It runs with your credentials and your access. It runs when you trigger it. And when it gets something wrong, you notice and tell it, which is the only evaluation it ever gets. Deploy the same skill to the cloud, unattended and pointed at production, and all three disappear at once.

Why haven't UK organizations moved off the hyperscalers?

Two-thirds of UK IT leaders say they would switch cloud providers to take back control. Fifteen percent have actually done it. That is the headline from Civo's Digital Sovereignty Revolution 2026, a survey of 1,000 UK IT leaders. The intent is loud and getting louder. The movement is almost silent. It would be easy to call that apathy. It is not. UK organizations are staying on hyperscale infrastructure they no longer fully trust for four very specific reasons. Three of them are structural.

Shipped: Fit more of your cost data on one screen

Most cost questions get answered the same way. You read a chart and the table under it together. Maybe you spot a jump on the chart, and then you go looking in the table for the service, account, or team that caused it. When you can see more of that table while the chart is still in view, the whole review goes faster. You’re also a lot less likely to lose your place halfway through.

Can you see what your sales org did with $206,000 of AI last month?

Activity categorization classifies every AI request by the work it performs, such as meeting prep, code review or account research, then assigns that spend to the team, person, model and provider behind it. It turns a provider invoice that shows only totals by model and API key into a breakdown finance can allocate, charge back and budget from. CloudZero AI Signals does this as the spend happens.

Amazon told its engineers to stop chasing tokens

Amazon told its own engineers this week to stop tokenmaxxing. The memo circulated internally in September and Amazon published it on Tuesday, Oct. 27. Tokenmaxxing is the practice of using AI as heavily as possible with little regard for whether the output justifies the spend. The memo calls token usage, adoption rates, and code-change counts “deeply flawed” ways to measure a team.

PHP2Shell explained: blocked 22 hours before the patch existed

PHP2Shell let attackers run code on PHP servers without logging in, and updating a CMS or its plugins didn't help. Only a new version of PHP fixed it. In this explainer, we break down how the two flaws work (CVE-2026-109618 and CVE-2026-109619, both rated 9.2 critical) and what Upsun Cloud did between PHP's one-day warning and the fix. We get into.

Announcing SOC 1, FedRAMP 20x Class A, PCI, and HIPAA Milestones At Harness

Explore Harness' latest compliance milestones: SOC 1, FedRAMP 20x Class A, PCI DSS, and HIPAA assessments across its platform and runtime security. Harness announced four compliance milestones: its first SOC 1 audit, FedRAMP 20x Class A certification, and first PCI DSS and HIPAA Security Rule assessments. SOC 1 and FedRAMP 20x Class A apply to the Harness Autonomous SDLC Platform. PCI DSS and HIPAA apply to the Runtime Protection Agent.

CloudZero in 3 Minutes: See What Your AI and Cloud Spend Actually Buys

Cloud and AI spend in one place, tied to the teams, products, and customers behind it. Your bill tells you what you spent. CloudZero tells you why, and whether it paid off. This quick tour shows how CloudZero pulls cost from AWS, Azure, GCP, Kubernetes, Snowflake, OpenAI, Anthropic, and more, then allocates it to what your business actually cares about. No perfect tagging required.

The Full Stack Network (And Everything We Broke Along the Way) | Richard Olson | Megaport Connect

What does it take to build a global hybrid multicloud network? Richard Olson, Tech Lead at Canva, shares the architectural decisions, tradeoffs, and lessons learned scaling infrastructure across clouds, regions, and bare metal at global scale. Recorded at Megaport Connect 2026. Chicago | Thursday 22 October ABOUT THE SPEAKER | Richard Olson, Tech Lead (Networking and Compute), Canva.

Building Secure Hybrid Multicloud Architectures | Jeremiah Johnson | Megaport Connect 2026

As infrastructure expands across clouds, data centers, and the edge, complexity grows. This session explores practical strategies for designing secure, scalable multicloud architectures that balance performance, governance, connectivity, and operational simplicity. Recorded at Megaport Connect 2026. Chicago | Thursday 22 October ABOUT THE SPEAKER | Jeremiah Johnson, US Cloud Engineering Manager, Fortinet.

Application Chaos Testing using Traffic Replay #apitesting #devops #microservices #chaostesting

Learn how to test your application's fallback mechanisms by intentionally injecting chaos and simulated dependency failures into recorded API traffic. Easily configure scoped rules to inject status code errors or delays during mock runs to verify your app handles failure gracefully. Learn more: speedscale.com.

Cloud Networking 101 | Holly Podbielak | Megaport Connect 2026

Cloud has transformed networking. This session explores the fundamentals of cloud networking, including software-defined infrastructure, automation, APIs, infrastructure as code, and cloud connectivity, providing a practical foundation for modern network engineers. Recorded at Megaport Connect 2026. Chicago | Thursday 22 October ABOUT THE SPEAKER | Holly Podbielak, Solutions Consultant, Palo Alto Networks.

Can AI Do Your Software Testing? #softwaretesting #aitools #codingtips #devlife #tech #aiagents

Learn how AI handles different types of testing, from simple unit tests to complex end-to-end setups. Discover where AI succeeds in writing test code and where human strategy is still needed. Learn more: speedscale.com.

How AI Is Changing Cybersecurity and Exposing Decades of Bad Code

Was this the worst week in cybersecurity? AI-discovered PHP2Shell vulnerabilities, the LiteLLM supply chain attack, and reports of unauthorized AI agents accessing bank accounts are exposing serious weaknesses in software security. But is this really a cybersecurity problem, or has AI exposed decades of poor software engineering decisions? In this episode of ShipTalk, Martin Reynolds and Adam Arellano break down a remarkable week in AI security and debate whether engineering or security teams should be responsible for fixing what comes next.

CA distrust wargame: moving every certificate in 10 minutes

Last week, dozens of schools found out their certificate authority was being distrusted and they needed to replace all of their certificates in a few days. We wanted to know how we’d handle it if our own CA went away, and how long it would take. So we tried it with one of our other products. It has 6 certificates from Let’s Encrypt, deploying to 18 targets across Windows IIS, Linux nginx, Elasticsearch, and a mail server. Then we wargamed it: “Let’s Encrypt is being distrusted.

AI Signals Demo: See Exactly What Your AI Spend Is Buying | CloudZero

See who’s spending on AI, on which models, for what work, and what you got for it. Most companies can tell you what they spent on AI last month. Very few can tell you what it bought. In this demo, we show how AI Signals captures AI usage as it happens and ties every dollar to the person, team, and work behind it, across every model and provider.

A fresh look for Bitbucket Pipelines

We’re refreshing the Bitbucket Pipelines experience to make it easier to read logs, find the steps you need, and navigate a pipeline run. The update focuses on the Pipelines list and Pipeline result pages. This is a visual refresh only. Your pipeline configurations, builds, data, runners, variables, deployments, and integrations stay as they are. It’s the same Bitbucket Pipelines underneath, with a cleaner, more focused view.

Shipped: Log and track Insights from your AI assistant

Insights are how your team tracks interesting observations, analysis and optimization work in CloudZero. Each one records the opportunity and its status, so the work gets sized, assigned, and closed out. Teams now do a lot of this work in an AI assistant. For example, you can ask Claude which instances sat idle last month, and it will tell you. But if you have to switch to CloudZero and fill out a form to log that finding, some findings won’t get logged.

AI cost per customer: measure it and protect your margins

AI cost per customer is each customer's attributed share of your AI spend: API tokens, inference infrastructure, and per-seat AI tools, measured against that customer's revenue. It matters because AI usage is wildly uneven across customers, so healthy blended margins can hide individual customers you serve at a loss. It's cost to serve, not acquisition cost. Cost per customer is the metric CloudZero was built around.

Make Kepler Yours: Create a Theme and Share It in the Gallery

In Kepler ADE by GitKraken, you can make your own theme. Describe the look you want in plain words, and an agent builds it for you. How it works: Open Settings, go to Appearance, and click Create a theme Type the look you want. In this video I asked for gold and maroon The agent drafts the theme and checks every color for contrast before it saves. Then pick your new theme under Your themes Keep your theme for yourself, or share it with a pull request to gitkraken/kepler-themes so it can join the public gallery.

Devart Python Connectors add support for Python 3.15 and the latest database versions

We are pleased to announce a new release of Devart Python Connectors, bringing support for Python 3.15, Microsoft SQL Server 2025, Oracle 26ai, and MySQL 9.7.x. The update also introduces new authentication methods, connection options, and improvements to data type handling across multiple connectors.

Can One Building Hold a Country Full of Experts? | Civo Navigate London 2026

AI factories don't sell floor space. They produce tokens, the currency of intelligence, and every jump from Hopper to Vera Rubin packs in up to 4x the density. Training wants one giant site. Inference wants to be as close to you as physics allows. So the panel maps out what comes next: edge data centres of 5 to 50MW, handing work between your watch, your phone and the cloud at the lowest possible latency.

What are decision models? Uses, examples, and tradeoffs

A decision model is a specialized AI model that evaluates inputs against predefined outcomes, returning a structured choice, classification, or score. Unlike large language models (LLMs), which handle a broad range of generative and reasoning tasks, decision models are optimized for tasks like routing requests, selecting agent actions, and evaluating AI outputs.

Beyond Drag-and-Drop: What Sets AI Workflow Tools Apart

“AI workflow tool” now describes products with very different build models. One may generate an executable workflow from a plain-language request. Another may add a chat panel or autocomplete to the same drag-and-drop experience it has offered for years. That difference matters to buyers because teams choose workflow tools to reduce automation backlogs, eliminate repetitive work, and extend orchestration across ITSM, cloud, network, identity, and infrastructure systems.

Inside Rootly On-Call: Schedules, Escalations & Alerts, End to End

Paging people shouldn’t be the hard part of incident response. In this walkthrough, we tour the Rootly On-Call platform end to end and show how teams set up on-call that’s reliable, fair, and easy to manage. Whether you’re moving off another paging tool or setting up on-call for the first time, this video shows how Rootly brings on-call and incident response together in one place.

AI cost per query: how to calculate and optimize it

AI cost per query is your total AI serving spend divided by the number of queries served over the same period. It combines model API charges (input and output tokens), retrieval and orchestration overhead, and shared infrastructure. Most production text queries cost between $0.0005 and $0.02. It's the base unit of AI unit economics, and the number finance needs before any ROI claim holds up.

Shipped: Azure cost totals that match your invoice

Azure cost exports sometimes fail with a server error and then succeed on the next try. Some reports cover only part of the month. Large tenants get rate-limited when they request a lot of data at once. Each of these things can leave a gap in your Azure history. You normally find the gap when finance compares the Azure total in CloudZero to the Microsoft invoice.

Shipped: AI dimensions, organized around how your team works

AI Signals adds a standard set of AI dimensions to your dimension picker, plus custom dimensions built from your own data. Not every team needs all of them. The ones you don’t use make the ones you want harder to find. Cleaning that up used to require an engineer to run a script every time an account team needed a change. We identified the bottleneck and automated it, so account teams can manage dimensions themselves and engineering stays focused on product work.

Building a local AI agent in Workshop on Ubuntu

Build a fully local AI coding agent on Ubuntu using Canonical Workshop and the Qwen3-Coder Inference Snap. In this step-by-step demo, you'll set up an isolated development environment, connect your coding agent to a locally hosted LLM, and run coding tasks without an internet connection. Follow along to recreate the setup on your own machine, using CPU or GPU inference. Chapters.

What Is Agentic Operations and Why Ops Teams Are Adopting It

AI coding tools have changed how fast software ships. They haven’t changed who runs it. Every extra release, alert and incident still lands on the same SRE, Platform and DevOps teams, and 78% of technology leaders report more incidents since adopting AI-generated code. So operations teams are turning to agents too. Six in 10 enterprise leaders are piloting, deploying or evaluating automated incident response, according to Caylent.

What Is Continuous Data Protection and How Can You Achieve It?

Learn what continuous data protection is, how it reduces data loss, and how it supports lower recovery point objectives. Table of Contents A backup can complete exactly as scheduled and still leave you with more data loss than your business can tolerate. Imagine this scenario. Your business database is backed up at midnight every night – but one afternoon, it fails at 4 p.m. Everything written in the 16 hours leading up to this failure falls outside your latest recovery point.

Why AI Coding Agents Are Breaking Your Software

While AI coding agents increase initial build speed, they often lack context about real-world user behavior, leading to downstream production bugs. Watch to learn how to move beyond basic agent-on-agent reviews and set up a true "Quality Factory" using: Check out our demos or get started free: speedscale.com.

Audit-Ready Before the Holiday Rush: How Retail IT Teams Prevent Outages with Puppet

Every retail IT leader knows that a mix of anticipation, cautious relief, and low-grade paranoia the week before the holiday freeze. Change requests stack up. Teams push last-minute updates to servers, registers, and store systems. And somewhere across hundreds or thousands of locations, one system has drifted slightly out of compliance. Nobody notices until peak traffic arrives. Then a lane goes down, a register stops processing transactions, checkout slows, and revenue starts walking out the door.

Can Big Tech's $200 Billion AI Bet Pay Off?

China’s AI and chip stocks have fallen sharply, raising a bigger question: could the same thing happen in the U.S.? With Microsoft, Alphabet, and Amazon reporting earnings, investors are looking for signs that cloud growth can justify the enormous sums being spent on AI. Is this a warning for the U.S. market, or can Big Tech’s AI investments deliver the growth investors expect?

Test and Mock GraphQL APIs Without Trusting the 200

Replay a GraphQL recording at the server that produced it, and every request comes back 200 OK. Here is one of those 200s, from a Session query whose recorded token has expired: A GraphQL server reports most failures inside a successful HTTP response, so any check that stops at the status code passes this request. And that is the second way GraphQL hides from URL-shaped tooling.

Inside Kraken: Regression Testing With Traffic Replay

A readiness check should make a release safer. During one release validation, ours kept Kraken’s traffic replays stuck in Initializing until they timed out. The operator was asking Kubernetes for EndpointSlices. Its installed permissions did not allow that request. The code needed a real cluster, the generated permissions, and a replay trying to start before that mistake became obvious. Kraken put those pieces together during release validation.

Monitoring Modernization: 6 Lessons for IT Leaders

Monitoring modernization doesn’t have to begin with a rip-and-replace project. For many IT teams, it starts with a specific need: better visibility, stronger historical context, more useful alerting, or capabilities their current tools simply don’t provide. From there, modernization can happen in stages.

gRPC Mocks, Tests and Contract Checks From a .proto

Change one field in a.proto from double to string, and nothing complains. The code compiles, the deploy goes green, and a service still built from the old contract keeps answering with a double. Here’s what Go’s protobuf runtime does when a client on the new contract reads that answer: No error. risk_score comes back empty, and the nine bytes of the double are tucked away as unknown fields.

Britain's schools are adopting AI, but who controls the infrastructure behind it?

Four in five UK teachers now use artificial intelligence for work. That is an extraordinary level of adoption for a technology that, just a few years ago, most people outside the technology industry had barely encountered. But there's another figure from the same research that I find considerably more interesting. Only 35% of teachers using AI say they're actually working fewer hours because of it.

The Migration Takes 2 Weeks. Deciding to Do It Takes 6 Months. (Webinar Replay)

Replay and recap of our October 20 live session: why the decision to migrate takes longer than the migration itself, the five human blockers behind it, two customer migrations, and three ways to cut decision time. Chapters, timestamps and key takeaways. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

Microsoft Offers 60,000 Employees Buyouts. Here's the AI Problem.

Microsoft is offering voluntary buyouts to 60,000 employees—more than a quarter of its workforce—while investing billions into AI infrastructure. But here's the bigger question: What happens when experienced engineers leave and AI-generated code keeps accelerating? AI can write code faster than ever. But deploying it safely, securely, and at scale? That's becoming the real bottleneck. Is Microsoft funding AI with headcount instead of efficiency?

7 weak points in your delivery model to fix before your next audit or outage

An auditor asking for evidence of your deployment process and an incident review asking what went wrong are asking about the same things. The difference is timing. One catches the weak point before it costs you anything. The other catches it in the middle of an outage, with a customer on the phone.

Fixing distrusted InCommon certificates with ERR_CERT_AUTHORITY_INVALID

Starting Tuesday, October 27, a lot of university websites will open in Chrome to this. Chrome is distrusting a root certificate, emSign ECC Root CA - G3, after eMudhra generated CA keys as small as 4. Every InCommon certificate issued from eMudhra’s ECC chain since April chains to that root.

PHP2Shell: Manage security patches at scale with Cortex

"Patch every PHP server. Today." That was the message a lot of engineering leaders got the week of October 20. PHP2Shell is a pair of unauthenticated remote code execution bugs in PHP itself, CVE-2026-109618 and CVE-2026-109619, both rated CVSS 9.2. Attacks started before the patches shipped, and working exploits followed within days.

Shipped: See which billing connections stopped sending data, and why

Every number in CloudZero comes from a billing connection. When a credential expires or a permission changes, that connection stops sending data, and your reports show less spend than you actually have. If you catch it early, you can fix the connection before month-end close. You also need to know what broke. For Azure and Snowflake connections, CloudZero now tells you which check failed, so you can send the fix to the right person without opening a support ticket.

How much does it cost to train an AI model? Frontier figures, graded [2026]

Training an AI model costs anywhere from a few hundred dollars to several hundred million, depending entirely on what “train” means. Fine-tuning an existing model: tens to thousands of dollars. Pretraining a small model from scratch: tens of thousands to millions. A frontier run in 2026: hundreds of millions, with Epoch AI projecting the largest runs will pass $1 billion by 2027.

The Cyber Security Arms Race

My content creator friends were eating well last week, figuratively. I would be very surprised if you didn’t hear about any of the security vulnerabilities that were disclosed last week. There were several high profile bugs that could lead to Remote Code Execution (RCE). The vulnerabilities for PHP were so widespread that governmental bodies were advising website owners to take their sites offline until they can implement the latest patches when they became available.

Let's Encrypt Is Shortening Certificate Lifetimes

Let's Encrypt is cutting its certificate lifetimes in half, from 90 days down to 45 days by 2028. If your team still has a calendar reminder that says "renew the certs," this is the nudge to finally retire it. The change isn't purely a Let's Encrypt decision. It's part of an industry-wide shift driven by the CA/Browser Forum, and every publicly trusted certificate authority is heading the same direction.

Was Saudi Arabia Secretly Listening to OpenAI's Biggest Secrets?

A hidden recording device. A former OpenAI engineer. And a possible connection to the Saudi government. What started as a suspicious discovery behind a television inside OpenAI has turned into a federal investigation with potential national security implications. The FBI is investigating whether former OpenAI engineer Abdulrahman Alfozan was involved in corporate espionage, with prosecutors pointing to alleged connections to a member of the Saudi royal family.

Microsoft Has a Bigger Problem Than Anyone Realizes

Microsoft just released over 1,400 security patches, including three zero-day vulnerabilities, one of which is already being exploited. But is this a sign of better security or a much bigger problem? In this ShipTalk discussion, we break down Microsoft's massive Patch Tuesday release, the challenges of managing thousands of vulnerabilities across enterprise environments, and whether AI is helping Microsoft find problems too late in the software development process.

5 Questions to Ask Before the Next Cloud Outage

On October 20, a power failure in one of Google Cloud’s three London zones disrupted Revolut, Lloyds, HSBC and others for hours. One zone failed, errors spread region-wide, and Google warned customers they might not be able to create new workloads to fail over to. Most teams find out how resilient they are during an outage, not before one. These five questions let you find out first.

Test AI-Generated Code with Real Traffic#aiagents #devops #observability #shiftleft #softwaretesting

AI can generate code in seconds, but testing it against real production behavior is where developers get stuck. Learn how capturing and replaying actual production traffic in development helps you catch bugs before you deploy!

Adding friction to your AI spend isn't saving money. It's costing you growth.

Enterprises are putting hard ceilings on AI spend. Accenture now centrally funds $29 a month per person for Claude and charges anything above that to a project budget code. Uber used up its 2026 AI budget in four months and restricted access. A cap stops waste and useful work at the same rate. The alternative is seeing AI cost by team, by project and by outcome, then funding what returns. Companies spent the past year telling employees to use more AI. Now a lot of them are putting a lid on it.

Shipped: Slice AI spend eight ways in AI Explorer

You can already break down cloud spend by team, product, or customer in Explorer. But AI spend has been harder to decompose. Which models is each team running? What activity is driving the cost growth you saw this month? Before AI Explorer, answering those questions meant exporting raw event data and building your own breakdowns, or waiting days for reconciled billing to land in Explorer.

Git worktrees: How to work on multiple branches at once

Git worktrees let you check out multiple branches of the same repository in separate directories. Each worktree has its own files and staging area, but they all share the same Git history. You can work on several branches without repeatedly switching between them, stashing changes, or cloning the repository again. Worktrees are especially useful when working with coding agents. Tools like Claude Code, Codex, and Cursor can use them to handle multiple tasks in parallel without editing the same files.

AI Can Write Infinite Code. But Can We Ship It Safely?

AI is making code generation faster than ever. But writing code is only half the battle. Neil Watkins from Burns & McDonnell explains why the next big challenge in AI-driven software development isn't generating more code. It's making sure that code can be tested, secured, and deployed safely. As AI accelerates development, businesses need to rethink how they manage risk and ship software with confidence.

Before you build your own internal platform, run these numbers

"We'll just build it ourselves" is usually said with confidence and a rough headcount estimate. Six months later, the team that was supposed to spend two sprints on it is still maintaining it a year in, and the platform that was meant to save engineering time has become one of the things engineering time goes to. Build isn't automatically the wrong call. Sometimes it's the right one.

Does the UK really need Gigawatt data centres? | Civo Navigate London 2026

Everyone's racing to build gigawatt AI factories by 2035. What if the faster route is already plugged in? Swarms of agents need far more compute than a chat prompt ever did, and the scaling laws say demand isn't slowing. But in the UK, anything over 15MW can mean waiting until 2032 or later for a grid connection. So the panel makes a different case: smaller sites on existing power and fibre, linked into one national campus, live in less time than a single mega-build.

Strengthening the Security of Qovery's Access to Your AWS Account

Qovery now sends your organization ID as the sts:ExternalId when it assumes the IAM role in your AWS account, and the role's trust policy only accepts it on behalf of your organization. Your role is already updated. If you manage it with the qovery-role-creation CloudFormation stack, update the stack to the latest template. Romain is a staff engineer at Qovery working on the control plane and AI integrations. He writes about distributed systems, incident response, and MCP-based tooling.

Create an Operational Risk Policy in JFrog Curation

Protect your organization from the next software package hijacking with JFrog Curation! Learn how to create an operational risk policy in JFrog Curation that flags immature package versions. This walkthrough reviews the available operational risk conditions, explains why brand-new or outdated releases can carry supply chain risk, and shows how a Dry Run action lets you measure a policy's impact on developers before you switch it to Block.

Create a Legal Risk Policy in JFrog Curation

Protect your proprietary code with JFrog Curation! Learn how to create a legal risk policy that blocks packages with licenses you don’t want developers using. In this demo, we build a policy for the GNU AGPL license, add a waiver for a package covered by a commercial license, and configure how waiver requests are handled. Read more about it in the JFrog Docs.

Configure Your JFrog Curation Service

Learn how to configure the JFrog Curation service for the first time. This video walks through each setting on the Curation General page, including turning on Curation, connecting package types, compliant version selection and notifications, and explains what each one does. Creating Curation policies and advanced coverage are covered in separate videos. Read more about it in JFrog Docs.

How Upsun handled PHP2Shell: protection in place 22 hours before the patch

On 21 October 2026, the team behind PHP released an emergency fix for two critical security flaws. PHP is the programming language behind a large share of the web, including WordPress, Drupal and many online stores. Researchers at Wiz named the flaws PHP2Shell. An attacker could use them to take control of a website without ever logging in. Updating a website, its CMS, or its plugins doesn't help. The only real fix is (and was) a new version of PHP itself.

The Upsun Performance Agent: a diagnosis instead of a call graph

The data to explain a slow endpoint is usually already sitting in your project. Blackfire has the profile. Continuous profiling has the flame graph. The traffic numbers show which route matters. The code is in git. What takes the afternoon is putting those four things next to each other and working out which function is responsible. That afternoon is what the Upsun Performance Agent is for.

AWS Interconnect Is Coming to Megaport

AWS Interconnect is coming to Megaport, giving enterprises and AI infrastructure providers another way to scale private AWS connectivity with automation, encryption, and built-in resilience. Megaport customers just got a new AWS connectivity option, and it fits perfectly with how we’ve always believed infrastructure should work: direct, automated, resilient, and easier to operate.

Security Just Hit Machine Speed

What if we could eliminate vulnerabilities before they become a problem? Neil Watkins from Burns & McDonnell explains how AI, automated security assessments, and Harness CI/CD capabilities could transform vulnerability management. From reducing attack surfaces to rapidly responding to critical zero-day vulnerabilities, the future of security is about moving faster without slowing down developers.

Introducing Ergo: explainable policies on OPA

When an auditor tests a control, they ask two questions about each change: was the control met, and what evidence shows how that result was reached? Most automated controls can answer the first. A Rego policy returns allow: true or allow: false, but says nothing about what it checked. Engineers can hand-write violation messages to explain a failure, but a passing check leaves no record at all. When an auditor asks how a change passed, someone has to reconstruct the answer.

One update can brick everything

When hardware operates unattended in remote locations, a failed update could be an operational disaster. Bricking a device hundreds of miles away turns a simple software patch into a costly physical recovery mission. Without built-in self-healing mechanisms, one bad deployment can paralyze your entire field operation. Canonical offers solution.

How to Secure Your PHP Infrastructure and Remediate PHP2Shell with Puppet

The detailed flaw coined “php2shell” is inherent in the PHP language itself, with multiple versions of PHP affected that have been released on the last decade. Ryan Austin, a Calif researcher who helped uncover the issue told the BBC it was, “The most serious vulnerability I’ve ever found". Wiz wrote in a blog post about the detailed findings that would allow hackers to exploit the PHP2Shell issue and take control of an affected web server.

Sandbox Environments for AI Agents: A Full, Isolated Stack for Every Task

A code sandbox like Daytona or E2B isolates a process. A sandbox environment isolates a whole stack: services, databases, queues and configuration, cloned for one agent task and destroyed when it is done. Here is how sandbox environments work, what they are good for, and how to run them on Qovery. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

How to run fewer tests and speed up CI with CircleCI Smarter Testing

A one-line fix shouldn’t wait on the whole test suite. Yet a typical CI pipeline runs every test on every push, and a single flaky failure sends developers back to the rerun button. CircleCI’s Smarter Testing addresses both problems. Test impact analysis tracks which source files each test executes, then runs only the tests affected by a code change. Auto rerun retries flaky tests inside the job instead of failing the build.

How to Stop Secrets Leaking From Your Deployment Platform, and How Qovery Stores Yours

Railway's disclosure of leaked customer environment variables is a reminder that deployment platforms hold the keys to everything. Here is how secrets leak from platforms, the practices that prevent it or limit the damage, and exactly how Qovery stores secrets across its control plane and your data plane, with AWS Secrets Manager, Parameter Store, GCP Secret Manager, Doppler and Infisical. Romaric founded Qovery to make Kubernetes accessible to every engineering team.

Getting started with the CircleCI CLI

The CircleCI CLI brings CI into your terminal, where developers and coding agents can work with it directly. You can set up projects, trigger and monitor pipelines, investigate failures, retrieve test results and artifacts, manage project settings, and more. Agents can use the CLI through shell commands or its built-in MCP server, giving them the tools and context to validate changes, diagnose failures, and try again without switching to a browser.

What Is a Citizen Developer, and Why IT Teams Need Them Now

"Citizen developer" sounds simple: give business teams low-code tools and let them solve their own process problems. In practice, many organizations discover that the tools are still too technical for the intended builders or too loosely governed for IT to trust. Both problems matter. A policy cannot create citizen developers if the tool still demands platform expertise. An approachable builder cannot scale safely if workflows operate outside permissions, testing, audit, and lifecycle controls.

The Best Cloud Providers for Data Sovereignty and Residency in 2026

Data residency is about where data is stored and processed. Data sovereignty is about whose laws and operators can reach it. The strongest setups put regulated data in in-country regions or with sovereign providers, hold their own encryption keys, enforce placement with policy, and keep the ability to move. No single provider covers every country, so most teams combine two or three. Disclosure: Control Plane publishes this guide and is one of the options listed. This guide is not legal advice.

Capping the AI free-for-all? Know what each dollar returns first.

Most companies gave everyone AI access and thought they’d sort out the costs later. Engineering, support, product, marketing, and finance all got licenses to the best models. The early results looked good, and for a while it didn’t matter there wasn’t an explicit business case. Let’s call the first half of 2026 the free-for-all period for many companies. AI adoption spread across the org fast, people and teams loved it, and then the invoices started coming in.

The Best Cloud Migration Tools and Services in 2026

The best cloud migration tool depends on what you are moving, from where, to where, and whether you can afford downtime. Native tools (AWS Transform MGN, Azure Migrate, and Google Cloud Migration Center) move servers into their own cloud. Replication tools move VMs and data with minimal downtime. Kubernetes tools move containerized apps. Platforms like Control Plane let you run the same workloads in the old and new environment at once, so you cut over gradually.

Shipped: Create a Jira ticket from a cost spike, with status synced both ways

When Monitors flags a cost spike, the fix usually belongs to an engineering team, and that team might track their work in Jira. Now you can hand the incident to them from CloudZero in one click. The Jira ticket and the CloudZero incident stay in step. When the engineer resolves the ticket, the incident resolves too. You track the work in one place, and the status you see in CloudZero matches what the team is doing.

Internet2's certificate authority (eMudhra) is being distrusted

On Tuesday, October 27, Chrome will distrust an eMudhra root certificate, emSign ECC Root CA - G3. Mozilla already did. Most of the people who have to deal with it run IT at American universities. They get their certificates from InCommon, the certificate service Internet2 runs for higher education. The certificates say Internet2 on them, but since April, eMudhra, an Indian certificate authority, has issued them.

Hyperview DCIM 5.7 Software Release

Hyperview 5.7 is here! See what's new in this release: formula-based Custom Sensors, a Network Path view for circuits, and temperature heat maps for racks and floor plans. WHAT'S NEW IN HYPERVIEW 5.7 Custom Sensors: Create numeric sensors calculated from a formula that uses other sensors as inputs. Manage them from the new Assets → Custom Sensors page. Connectivity Visualization (Phase 1): The new Network Path tab on circuits shows the assets and connections that make up each circuit. Select any asset or connection for details, and export the path as a JPG, PDF or PNG.

One Platform, Three Borders: Multi-Tenancy Isolation on Cycle

When it comes to multi-tenancy isolation, most platforms only support one approach, and you have to make it work for every customer. Usually that means either all tenants share the same infrastructure and rely on the application to keep them apart, or every customer gets a separate stack that your ops team has to deploy, patch, and monitor on its own. Both approaches work. The trouble is that they're rigid.

Policy as code for AI coding: How to turn engineering standards into guardrails for AI agents

Key Takeaways Engineering standards exist in every organization. They cover how services communicate, how secrets are managed, who reviews changes before they merge, and what "production-ready" means. The problem is where those standards live: wiki pages, onboarding docs, the memory of whoever happens to review a pull request that day. Conventional enforcement depended on reviewer knowledge, which varied across teams.

Demo: New Loom for Mac Desktop App

Introducing the all-new Loom Desktop app for Mac. About Atlassian: Behind every great human achievement, there is a team. From medicine and space travel to disaster response and pizza deliveries, we help teams all over the planet advance humanity through the power of software. Our mission is to help unleash the potential of every team.
Featured Post

Monitoring CloudNativePG: What Changes When the Operator Owns Your Logs

Postgres operators like CloudNativePG (CNPG) have lowered the threshold for running highly available Postgres clusters on Kubernetes. Failover, replicas, backups, and rolling upgrades are handled by the operator, along with helpful niceties like automatic configuration of essential extensions. A few changes to a YAML manifest can provide a lot of value very quickly.

5 takeaways from the State of Software Delivery Q3 Pulse report

Software teams are taking on more work than ever. Developers are juggling more branches, coding agents are keeping CI busy through the weekend, and builds are passing more often and finishing faster. But is all that extra activity helping teams ship faster? Today we released the 2026 State of Software Delivery Q3 Pulse report, the latest in our quarterly series tracking how software teams are adapting to AI-driven development.

How to Troubleshoot Intermittent Network Issues After They Happen

One of the most frustrating challenges I faced as a network engineer was troubleshooting problems that had already disappeared. A user would call and report that an application was performing terribly. A site would become unusable for several minutes. Voice calls would break up. File transfers would suddenly slow to a crawl. Then, by the time I started investigating, everything would be working normally again.

php2shell: the flaw hiding all across the web

Discover how php2shell vulnerabilities expose PHP servers to remote code execution and how Harness virtual patching protects endpoints while you deploy fixes. On October 21, 2026, the PHP project rushed out emergency patches for two critical flaws nicknamed php2shell (CVE-2026-109618 and CVE-2026-109619, both rated 9.2 out of 10). This isn't a bug in some plugin or a server someone set up wrong. It's in PHP itself, in the way the language has handled errors since 2012.

HAProxy Enterprise WAF protects against PHP2Shell (CVE-2026-109618, CVE-2026-109619)

On October 20th, 2026, the PHP Security Team issued an advanced notice and security advisory disclosing two critical vulnerabilities (CVE-2026-109618 and CVE-2026-109619), both rated CVSS v4.0 9.2, affecting PHP installations.

Bring Your Own Identity Provider to Harness MCP

Learn how Harness MCP OAuth proxy mode enables enterprise developers to use their own identity provider without static tokens or shared credentials. OAuth proxy mode lets enterprises run Harness MCP behind their own identity provider, with no static tokens anywhere in the chain. Coding agents write the change. Harness agents take it through production, running the builds, tests, scans, and deployments that follow, with policy enforced on every action.

7 Best Code Review Platforms for Regulated Dev Teams (2026)

Regulated development teams face a unique code review challenge: every pull request has to satisfy compliance requirements, document an audit trail, and still merge fast enough to keep your sprint on track. The right code review platform closes that gap between governance and velocity. GitKraken gives regulated teams a unified DevEx platform that connects visual pull request workflows, AI-assisted review, and organization-wide security controls in one workspace.

AI Changed How We Work. It Didn't Change What Your Platform Needs to Do.

If you've spent any time in an engineering Slack lately, you've probably noticed that AI comes up in just about every conversation. Someone's using an assistant to scaffold a new service. Someone else has an agent triaging alerts overnight. And at least one person is asking whether all of this means the team can finally skip the "platform stuff.".

What's new and coming in Redgate Monitor: AI, CIS compliance and cloud migration

This webinar covers what's new and coming in Redgate Monitor: AI with Redgate Assistant and the Redgate Monitor MCP server, CIS benchmark compliance checks and security alerting (Enterprise), AWS cloud migration advice for SQL Server workloads, and the roadmap into 2027. Redgate Monitor has shipped a lot this year, and there's more landing before the end of it. This session walks through what's new, what's coming over the next few months and into 2027, and what it all means for how you run your estate. Roadmap items are current direction, not commitments.

Merge queue APIs now available in Bitbucket Cloud

Merge Queues help keep your busy branches stable by testing how changes work together before they’re merged. Today, we’re introducing public APIs for Merge Queues, available to all Standard and Premium workspaces in Bitbucket Cloud. The new APIs let your tools use the existing merge endpoint to queue pull requests, track their progress and respond to the outcome.

Optimize your test suite with two new agents

Flaky tests stall pull requests. Slow tests drag out builds. Outdated tests add maintenance work that’s easy to put off. To help optimize your test suite, we’re adding two new agents in Bitbucket, Test Optimizer and Test Cleanup and an improved Flaky Test Fixer. With these agents, your team will spend less time babysitting tests and more time shipping.

How to Let AI Agents Operate Production Infrastructure Safely

Yes, it can be safe to let an AI agent change production infrastructure, if the agent works through the same controls you would demand of a new engineer: scoped permissions, short-lived credentials, a tamper-proof audit trail, changes that roll out gradually behind health checks, and a fast rollback. The infrastructure also has to be built so that one bad change cannot take everything down.

Cloud Outage Tracker: Major AWS, Azure, Google Cloud, and Cloudflare Outages Since 2020

Last updated: October 21, 2026. This tracker lists every major AWS, Microsoft Azure, Google Cloud, and Cloudflare outage since January 2020, with each provider’s own stated duration, root cause, and source. It covers 62 major incidents. The median outage lasted 6h 12m, and the most common cause was a configuration or deployment change (20 of 62, 32%), not hardware failure. We add new incidents as providers publish their post-incident reports. Control Plane publishes this tracker.

CertKit now has 86 built-in deployment templates

There are lots of ways to get a certificate. Getting it onto your Cisco ISE, IBM i, or WatchGuard VPN is the hard part. We keep making that easier. Since July, CertKit has added 51 new deployment templates, more than doubling the library to 86. Each platform has a built-in deployment template, and most have a deployment guide for the setup details. Setup is just picking a certificate and setting a few variables.

Dispatching Ansible playbooks with CFEngine

In large organizations and infrastructures, it’s fairly common to use multiple configuration management tools. There are many reasons for this. Different teams may have different preferences, some tools suit certain use cases better than others, and existing systems can come with their own limitations. Whatever the reason, the tools don’t have to work in isolation. In this post, we’ll show how to run Ansible playbooks on CFEngine-managed hosts using Mission Portal.

Shipped: Views now save your full Explorer state

Many CloudZero users ask the same few questions. What did my team spend this month? How is our AI spend trending over the last 30 days? What does one MCP tool call cost? Now you can save the exact Explorer setup behind each answer as a View and get back to it instantly. It’s not just filters and grouping anymore, but the full picture. You can share a link with a teammate or finance and they see the same View, filtered to the spend their role allows.

Why Was an OpenAI Engineer Hiding a Recording Device?

An OpenAI engineer was arrested after a hidden recording device was discovered inside an executive conference room. Who was he trying to record, and who was the information intended for? Martin Reynolds and Adam Arellano break down one of the strangest AI security stories of the year, along with three major cybersecurity headlines. Microsoft just released more than 1,400 security fixes in a record-breaking Patch Tuesday. Is AI finding vulnerabilities faster than companies can actually fix them?

Shipped: Break down AI spend by your projects and teams, within minutes

Your company talks about AI spend in its own terms, like projects, teams, and products. Now AI Signals can show AI spend in those terms, too. Write a CostFormation rule in CloudZero that groups AI spend by categories you care about, and the new breakdown appears in AI Signals the same day you decide to track it. There’s no waiting for a full processing cycle.

Where to Find GPU Capacity in 2026: Hyperscalers, Neoclouds and Regional Clouds

Google, CoreWeave and Nebius all say they are short of GPUs. Here is where capacity still exists in 2026, which GPU clouds offer managed Kubernetes, how to connect a second cloud to your first one, and how to run GPU services on all of them from one platform. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

Building a resource optimization agent with Kubex: Patterns

The rise of large-language models (LLMs) that can understand and create text, and reason about problems has opened the door for software agents that use the reasoning power of LLMs to interact with the wider world and solve problems. At Kubex, our bread and butter is compute and GPU resource optimization, so it’s natural for us to ask how agents could help our customers more effectively optimize their resources.

GCP Out of Capacity? How to Offload Workloads to AWS Without Running a Second Platform

Google says it is compute constrained, and GKE teams now hit ZONE_RESOURCE_POOL_EXHAUSTED on CPU machine families, not only GPUs. Here is what the error means, what Google recommends, what AWS can and cannot offer, and how to offload workloads from GCP to AWS with one platform instead of two. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

Feature Spotlight: Replay Progress Tracking #kubernetes #mocktest #devops #appperformance

Learn how to track cluster performance in real time using the replay progress panel, which highlights key phases including provision, mock, app, load, analyze, and result. You will also discover how to easily troubleshoot failed runs by expanding component lanes to review specific step reasons and cluster events. Learn more: speedscale.com.

Self Healing Agentic Pipeline | Bitbucket Blitz | Atlassian

Ever had a broken test stop your flow? In this Bitbucket Blitz video, we look at how to setup self-healing pipelines using Bitbucket and Bitbucket Agentic Pipelines. Instead of just failing and waiting for a human, the pipeline triggers an agent when a build or test breaks on a feature branch. The agent reads the logs, finds the root cause in the source code, creates a fix branch, and opens a pull request ready for review.

Feature Spotlight: Automatic Testing with Proxymock MCP Skills #aiagents #mcpserver #softwaretesting

Learn how to integrate your AI coding agent with Speedscale using the MCP server to record, replay, tune mocks, and analyze reports directly within your workspace. Streamline your testing workflow by letting your agent automatically capture traffic, resolve failing responses, and optimize match rates. Learn more: speedscale.com.

How to End Tribal Knowledge and Make Every IT Practitioner an Expert

Every IT organization has a small group of people who hold the answers everyone else depends on, and that dependency carries a cost that never appears on a dashboard. It shows up in constant interruptions, on-call rotations that keep routing back to the same names, investigations rebuilt from scratch every time an incident resurfaces, and the pressure carried by the one person who knows how the environment behaves under stress.

Feature Spotlight: Testing GraphQL #graphql #apitesting #developertools #techtutorial #devops

Learn how to resolve failed GraphQL session queries by updating expired tokens before replaying your snapshot. This video demonstrates how to find the GraphQL operation, edit variable values by path, and successfully pass replay checks. Learn more: speedscale.com.

Managed DEX for Service Desk Optimization | Improve IT Support with Teneo

See how Teneo Managed Digital Employee Experience (Managed DEX) helps IT and service desk teams identify and resolve employee technology issues faster. By giving service desk engineers greater visibility into the digital employee experience, Managed DEX helps teams understand what is affecting users, investigate problems more efficiently, and move from reactive troubleshooting toward proactive IT support.

Feature Spotlight: Import & Export to Load Testing Tools #api #postman #openapi #loadtesting #devops

Proxymock allows you to import existing Postman collections, browser HAR files, and OpenAPI specifications to instantly create test requests and mock responses. You can also pull traffic directly from cloud storage buckets, or export your requests into load testing scripts for tools like K6, Gatling, and Locust. Coding agents can even manage these imports and exports using integrated MCP tools. Learn more: speedscale.com.

Managed DEX for Application Performance | Find and Resolve Issues Faster

See how Teneo Managed Digital Employee Experience (Managed DEX) helps IT teams identify the root cause of application performance issues and resolve problems faster. Teneo Managed DEX gives service desk and IT teams deeper visibility into application crashes, response times, hang time, wait time and user experience across different application versions. In this short video, see how Managed DEX can help teams.

Feature Spotlight: Session-based Replay #trafficanalysis #api #developertools #techtutorial

This video provides an overview of using Sessions to group traffic by actor credentials, track individual user journeys chronologically, and analyze request flows. It also covers how to check replay readiness for JWT sessions, replay recorded user journeys at their original pace, verify pass/fail counts, and save or sample specific sessions for easy sharing. Learn more: speedscale.com.

Service Mesh Observability: Istio, Linkerd and Envoy Metrics

Service mesh observability guide: the metrics Istio, Linkerd and Envoy proxies emit, what ambient mode changes, and why tracing still needs app changes. Sejal Pandey works on content and growth at Last9, writing about observability, reliability, and SRE practices.

ChatGPT Enterprise pricing in 2026: seat costs, minimums, and the new token rate card

ChatGPT Enterprise has no public list price. Reported 2026 contracts average about $60 per user per month within a $45 to $75 range, with 150-seat minimums and annual prepayment, putting the floor near $108,000 a year. Newer eligible agreements add usage-based billing under OpenAI's published token rate card.

How we used Agentic Pipelines to turn test coverage into a daily habit

Engineers write tests for the logic that worries them and let the small details slide. One of our commerce engineering teams now has a scheduled agent that finds the thinly tested files, writes the missing tests, and opens a pull request for review. Nobody decides to skip a unit test. The core logic gets covered, the small details don’t make the cut, and most days that’s a fair trade.

Shipped: See who changed a cost monitor, and when

A cost monitor is only useful if people trust its settings. When a threshold moves or a monitor goes quiet, the team needs to know who made the change and when. Every monitor in CloudZero keeps that record. You can check it yourself in a few seconds, confirm a change was intended, and put a setting back if it wasn’t.

Enterprise AI ROI: proving returns at scale

Enterprise AI ROI is the return on AI investment measured across a portfolio: dozens of initiatives, multiple business units, shared platforms, and one board asking for the total. It fails differently than single-project ROI, usually because baselines and unit costs were never established, and it's proven with per-initiative denominators rolled into portfolio-level reporting.

How to Troubleshoot TLS Handshake and Encrypted Traffic Issues with Packet Analysis

I remember the good old days, when troubleshooting application traffic often meant I could examine much of the conversation between a client and server in clear text. Not anymore. Today, nearly everything is encrypted. That is obviously a good thing for security and privacy, but it has also created a common misconception that packet analysis is no longer useful because engineers cannot see the application headers and payload.

Kosli joins the Plexal & Barclays Eagle Labs Scaleup Programme

Kosli has been selected for the fourth edition of the Scaleup Programme run by Plexal and Barclays Eagle Labs. Following a competitive application process, we’re one of 25 high-growth UK technology companies chosen to take part. The programme is built for companies where growth for scaleups starts to present new challenges, with particular focus on scaling commercial performance, customer expansion, funding, and capital planning.

Quick Load Testing & Mocking with Proxymock and AI #loadtesting #mocktest #softwaretesting #devops

Learn how to quickly set up a load testing foundation for your Node app using the free ProxyMock tool combined with an AI coding agent. This walkthrough demonstrates how to record traffic, mock dependencies, and analyze latency distribution results in just a few simple steps. Learn more: speedscale.com.

Introducing AI Budgets: A Policy You Can Watch Work

AI Budgets turns an AI cost policy into a limit customers can watch hold in real time, so overspend gets caught within days instead of surfacing on next month's invoice. With AI Budgets, the Cost Management Agent turns your AI cost policy from a document everyone signed once and forgot into a limit you can see working. ‍ In our last post, we showed why 73% of organizations have an AI cost policy, but only 13% can tell whether it's working.

Nobody Wants Your New AI Agent #devops #aiagents #softwaredevelopment #techtrends #ai

DevOps customers are rejecting standalone AI agents and web interfaces in favor of integrating context directly into their existing harnesses, such as Copilot or Claude. Rather than logging into separate tools, developers prefer combining models and technologies within a single context window to streamline software development and debugging. Learn more: speedscale.com.

Harness Launches VegaLoad: Open-Source Load Testing for Agentic Developers

VegaLoad is a free, open-source load testing tool for agentic developers. Your agent writes the test, runs it, and gives you a report. VegaLoad is a free, open-source load testing tool. You ask your agent for a test. It writes the file, runs it, and gives you a report.

Engineering ops review agendas for startups and enterprises

It’s 9 p.m. on Sunday, and an engineering manager is pasting PagerDuty counts and Datadog graphs into a slide deck for Monday’s engineering ops review. On Monday, the first incident readout eats half the hour, the VP drops off for another call, and nobody gets to last week’s action items. Two quiet weeks later, someone cancels the meeting because nothing broke.

We used our own product to cut our AI tooling bill without cutting AI usage

The problem: our AI spend was growing faster than our understanding of its ROI. Like most engineering organizations, Harness went from "a few people are trying out AI coding tools" to "AI tooling is a line item in the monthly finance review" in a matter of months. The cost itself wasn't really the problem.

7 Best Tools for Parallel AI Coding Across Repos (2026)

Running five AI coding agents in parallel across three repositories sounds like a productivity breakthrough. In practice, it creates a coordination headache: conflicting file edits, orphaned branches, and zero visibility into which agent finished what. Parallel AI coding tools exist to solve exactly this, and Kepler by GitKraken gives you one surface to orchestrate every agent from backlog to merged pull request. This guide compares seven tools built for multi-repo, multi-agent development.

What Happens When You Outgrow a No-Code AI Agent Builder?

A no-code AI agent builder can get a defined agent into production quickly. The risk appears when added branches, exceptions, integrations, and controls exceed the visual canvas. Organizations should look for a platform that lets teams extend individual steps with reusable code without rebuilding the agent or abandoning its governance.

The hidden cost of environment drift

Two teams, same company, same platform, same quarter. Team A ships to production three times a day. Their environments are defined in code, provisioned the same way every time, and a new engineer can get a working setup before lunch. Team B ships once every two weeks, if the release window holds. Their staging environment has diverged from production in ways nobody fully remembers approving. Getting a new engineer set up takes a week of Slack messages to whoever still remembers how it was done last time.

Best Multi-Cloud and Multi-Region Failover Solutions (2026)

The best failover solution keeps your application serving users from another location without a manual cutover. The strongest approach is active-active across two or more locations, where every location already serves live traffic, rather than restoring from backups after an outage.

Harness AI Agents

AI is writing code faster than ever. But what happens after the code is written? Harness CEO Jyoti Bansal introduces four AI agents built to automate the software delivery lifecycle: Software Delivery Agent – Automate builds, deployments, and infrastructure management. Security Testing Agent – Find, prioritize, and fix vulnerabilities with AI. Runtime Protection Agent – Protect applications, APIs, and AI agents in production.

Load Test One Endpoint, Watch the Rest

What happens to transaction posting when statement traffic gets expensive? That’s the question a bank’s platform team actually needs answered before a busy month-end. It’s also a question most load tests can’t ask, because they turn one dial for the whole recording. Statements get heavier, posting gets heavier, and the average latency across both looks fine right up until customers can’t move money.

AI wrote the bug. You need production data to reproduce it

A pull request lands with a function an AI assistant generated. It reads cleanly, passes the existing tests, and gets merged. Three weeks later it breaks, but only for accounts with a specific billing history. Nobody wrote a test for that condition because nobody was thinking about it when the code went in. Now someone has to debug logic they didn't reason through, against a failure they can't picture without the exact data that triggered it. Debugging someone else's code has always worked this way.

How SGP.32 unlocks next-generation IoT deployments

Every time a smart utility meter transmits consumption data, a connected vehicle updates its telemetry, or a fleet of logistics trackers crosses international borders, seamless and uninterrupted connectivity is vital. Yet for years, managing Internet of Things (IoT) devices at scale has been constrained by physical SIM logistics, operator lock-in and remote SIM provisioning standards that were simply never built for autonomous, resource-constrained hardware.

Unable to get local issuer certificate, explained

Your site loads in Chrome fine. Then a deploy script, a webhook, or integration calls the same URL and gets this: Python says certificate verify failed: unable to get local issuer certificate. Node says unable to get local issuer certificate, or unable to verify the first certificate. It’s all the same problem. It’s a misconfiguration between your certificate and a trusted root. Either the server isn’t sending it, or the client doesn’t have it.

From personas to archetypes: a living, shared understanding of the people we build for (Part 1 of 2)

Personas are easy to create but often ignored. This is the first of two posts about how we developed archetypes to keep our personas fresh at Canonical. These are shared, machine-readable descriptions of our users that multiple teams and their agents can use. This post explains the system, its purpose, and its structure. The second post’ll cover how we maintain and update it. Personas should be functional tools.

Try the Qovery Console Without Signing Up

The Qovery Console demo is open to everyone at console-demo.qovery.com. No account, no credit card, no cloud credentials: the full Console on sample data, with seven short product tours. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

Introducing Qovery Training: Learn the Console by Doing, Before You Touch Production

Qovery Training is now generally available to every Qovery customer. It is a sandbox copy of the Console on fake data, with 18 tracks for software engineers, DevOps, platform and security teams, a simulated terminal and AI agent, and training spaces where admins pick the lessons and follow their team's progress. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

The 10 Best MCP Servers for DevOps and Cloud Infrastructure in 2026

The best MCP servers for DevOps depends on what you want an AI assistant to do: read code and pipelines, plan infrastructure as code, call one cloud’s APIs, observe production, or deploy and operate workloads. The safest setups combine scoped permissions, a read-only mode for investigation, confirmation before destructive actions, and an audit trail of every change.

Cloud Cost Optimization in 2026: 10 Levers That Cut Your Compute Bill

Most cloud compute waste comes from paying for capacity your workloads do not use: over-provisioned requests, idle nodes, standby capacity, and per-service add-ons. The biggest savings come from changing how capacity is reserved and packed, not only from discounts or dashboards.

Enterprise Vibe Mode: Deploy AI-Built Apps to Production | Harness Demo

Vibe coding makes building applications easier than ever. But how do you take an AI-generated app and safely deploy it to production? In this demo, see how Harness brings Vibe Mode to the enterprise, allowing anyone to deploy applications while automatically applying your organization's security policies, governance, compliance requirements, and deployment configurations. See how Harness enables teams to.

Harness Cost Management Agent | How to Set and Enforce AI Spending Budgets

Control AI spending across your organization with Harness Cost Management Agent's AI User Budgets. In this demo, see how Harness helps teams set, monitor, and enforce AI spending limits across tools like Claude, Cursor, and Amazon Bedrock, all from one centralized control plane. What you'll learn: Set weekly AI spending budgets for users and teams Track AI consumption across multiple tools and models.

MCP Server Monitoring: Tracing Tool Calls with OpenTelemetry

MCP server monitoring guide: spans, metrics and logs to record for tool calls, why failed tools look healthy, and how to trace requests from client to server. Sejal Pandey works on content and growth at Last9, writing about observability, reliability, and SRE practices.

SNMP Traps as Logs and Network Troubleshooting | Logs for Lunch

SNMP traps as logs, AI log anomaly detection, and network troubleshooting are the focus of Logs for Lunch: August 2026, for network and IT ops teams and LogicMonitor users. Tom Chavez introduces LM Logs, which keeps logs and metrics together. Cameron Compton troubleshoots dropped tunnel packets from a network operations dashboard, and Ron Scinta ingests SNMP traps through the Collector. Patrick Sites and Kerry DeVilbiss answer questions on load balancing, OTel and Cribl forwarding, MSP log sources, and search performance.

Cloud Log Monitoring & Root Cause Analysis | Logs for Lunch

Cloud log monitoring in LogicMonitor connects a service alert to the log event behind it. This Logs for Lunch July demo is for ITOps, CloudOps, and SRE teams. Tom Chavez hosts Ismath Mohideen (Product Marketing) and Nick Doane (Senior Sales Engineer). They cover cloud observability and multi-cloud monitoring across AWS, Azure, GCP, and OCI in LM Envision, using cloud provider APIs with no extra collectors.

7 Best Enterprise ADEs for Secure Multi-Agent Coding (2026)

Your engineering team runs five AI coding agents across three repositories. One is stuck waiting for input, another just overwrote a file the third one was editing, and nobody knows which branch belongs to which task. Sound familiar? Agentic development environments solve this coordination problem by giving you a single surface to orchestrate, review, and merge agent-driven work. This guide compares seven enterprise-ready ADEs built for secure, multi-agent coding workflows.

LM Logs Tips: Alert-to-Logs Workflow for Ops Team | Logs for Lunch

LM Logs troubleshooting starts at the alert. This Logs for Lunch session shows ITOps teams an alert-to-logs workflow and lesser-known LM Logs tips. Ryan Matuszewski demos a Tomcat application error. From the alert's Logs tab, he moves through log anomaly detection, All Logs, Log Patterns, and Log Analysis sorted by sentiment. He then opens the Logs page with the alert time range, and the same steps work for any alert type.

CI/CD Pipeline Observability: GitHub Actions, Jenkins and ArgoCD

CI/CD observability guide: the OpenTelemetry CI/CD conventions, tracing GitHub Actions and Jenkins runs, queue time, failure vs error, and deploy markers. Sejal Pandey works on content and growth at Last9, writing about observability, reliability, and SRE practices.

Autonomous IT: Data, Context, and Governed Action | 2H Announcement from LogicMonitor

Autonomous IT requires three things: complete, AI-ready data; connected context; and governed action. In LogicMonitor's 2H announcement, we show enterprise IT and ITOps leaders how each layer works. LogicMonitor is the AI-first platform for Autonomous IT. This update covers the three layers behind autonomous IT operations as the category moves from systems of intelligence to systems of action. Your team decides when Edwin AI moves from recommending an action to taking it.
Featured Post

AI Is Making Infrastructure Easier to Create and Harder to Operate

AI is rapidly changing the economics of software engineering. Tasks that once required hours of engineering effort can increasingly be completed in minutes. An AI agent can write an application, generate Terraform, produce Kubernetes manifests, configure a CI/CD pipeline, and interact directly with cloud APIs. For infrastructure teams, this sounds like an enormous productivity win. And on Day 1, it is. But generating infrastructure has never been the hardest part of running it.
Featured Post

The hidden cost of IT sprawl: how fragmented infrastructure drains business performance

Most IT estates grow through years of individual decisions instead of a single plan. A cloud account gets opened for one project. A data centre contract stays in place because switching is a migration project the business keeps deferring. Those choices get made workload by workload, and the estate that results rarely holds together as one plan.

Running a Green CI Pipeline Isn't the Hard Part Anymore

AI writes code faster, but CI still repeats costly work. See how Harness CI cuts unnecessary tests, recompilation and dependency downloads. Six months ago, your team adopted an AI coding assistant. Pull requests doubled. Generated code started landing in branches faster than reviewers could read it. The CI pipeline kept up for about three weeks. Now the queue backs up by mid-morning. Builds take 38 minutes. 4,000 tests run on every commit when 60 are relevant.

AI Agents Hacked 395 Organizations. How Do You Stop Them?

AI agents just changed the speed of cyberattacks. Are security teams ready? In a massive AI-orchestrated cyberattack, hundreds of autonomous AI agents exploited vulnerabilities in PaperCut software, compromising 440 servers across 395 organizations in 48 countries. But the bigger question isn't how these attacks happened. It's how human security teams are supposed to respond when attacks move faster than they can react.

Devart ODBC Drivers update brings SQL Server 2025, MySQL 9.7, and new Snowflake authentication methods

The latest release of Devart ODBC Drivers is here, bringing support for Microsoft SQL Server 2025, MySQL 9.7.x, and NexusDB 4.75.20, along with new authentication methods, advanced data protection features, and improved compatibility with development tools and operating systems.

Automate Configuration Management and Drift Remediation at Scale

Learn how Puppet Enterprise by Perforce automates configuration management, enforces desired state, and enables automatic drift remediation across Windows servers at scale. In this demo, Matthew, Associate Sales Engineer at Puppet, shows how to use Puppet Enterprise to deploy and manage Windows registry configurations across multiple servers from a single console. See how infrastructure as code helps eliminate manual configuration tasks, reduce human error, and maintain consistent system configurations across your environment.

GitLens 19.4: Explore the Commit Graph Without an Account

GitLens 19.4 makes it easier to get into your repository, understand your Git history, and start working without extra setup. The biggest change is simple: the Commit Graph is now available without a GitKraken account for public and local repositories. Open GitLens, open the Graph, and start exploring. No sign-in required. For private repositories, GitLens also gives you a 3-day preview of the Commit Graph without requiring an account, so you can experience the workflow before deciding what comes next.

Vercel Ship 2026: 3 Takeaways, and What Vercel's BYOC Still Keeps Outside Your Cloud

Vercel Ship 2026 made three things clear: Vercel wants your backend, agents now trigger most deployments, and Bring Your Own Cloud on AWS is GA. Here is what each announcement means for platform teams, what Vercel BYOC actually runs in your AWS account, and what it leaves on Vercel. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

Is Redgate Monitor a multi-platform tool or SQL Server only?

Redgate Monitor is a multi-platform database monitoring tool, not a SQL Server only tool. It monitors SQL Server, PostgreSQL, Oracle, MySQL and MongoDB from a single dashboard, on premises or in the cloud. This demo shows SQL Server, PostgreSQL and Oracle instances in the Redgate Monitor live demo environment.

How CFOs can control AI spend and prove AI's value

Neil Sawyer, Senior Vice President and Managing Director for HP Europe, Middle East and Africa, recently published “Scaling AI Without Losing Control” in Forbes Business Council. His starting point will be familiar to any finance leader. AI pilots looked affordable on pay-per-token and pay-per-query pricing, and that same pricing can get far more expensive at enterprise scale. Gartner forecasts worldwide AI spending will reach $2.7 trillion in 2026, up 49.5%.

AI infrastructure costs in 2026: what the stack is, what each layer costs, and how much to commit

AI infrastructure costs span four buying tiers in 2026: API-only teams spend hundreds to tens of thousands per month on tokens, GPU renters typically pay $2 to $10 per GPU-hour by chip class, committed-capacity buyers sign six-to-eight-figure reservation contracts, and owners spend millions per rack. The stack has six layers, and most budgets underestimate everything below the GPU line.

When AI Attacks at Machine Speed, Configuration Management Becomes Cybersecurity

The Australian Medicare AI agent incident highlights a broader shift in cybersecurity. AI does not need to create new vulnerabilities to increase risk. Its ability to continuously discover, test, and pursue existing weaknesses places greater emphasis on maintaining secure configurations over time, not just fixing issues once. Security teams are used to the idea that determined attackers will keep looking for a way in.

How to lower Android development costs by removing hardware from the critical path

As an Android developer, you’ll almost always have access to a device. However, when handling hardware, the device that you actually need often happens to be already in use, set up incorrectly, stored in another lab, or simply waiting to be reset. That’s when Android development costs start to increase.

Burnout Is Rising. Here's What You Can Fix

The faster teams deploy, the more releases fail, and burnout climbs right with it. What 700 engineers told Harness about AI-scale delivery. Lenny's Newsletter put out its 2026 tech workforce survey this year, and you should read the whole thing. The headline stats: significant burnout jumped from 44.7% to 55.7% of tech workers in a year. Career optimism dropped from 54.8% to 48.7% over the same period of time.

AI Coding Assistants: Trust Is the Attack Surface

Explore how AI coding agents can be exploited through trusted files, hooks, and MCP tools, and learn how to secure agent workflows against hidden instructions and persistent threats. Why the most dangerous instructions aren't the ones you type into the chat box For the past decade, autocomplete guessed your next line. It was helpful, annoying, or flat-out wrong, depending on the day.

Stacked PRs: what they are and how to run CI on a stack

Large pull requests can be a pain to review. When a change touches dozens of files and adds hundreds of lines of code, reviewers have a lot to work through before they can approve it. And if something needs to change, the whole PR goes through another round of review. Stacked PRs let developers split a large change into smaller, dependent pull requests that can be reviewed separately.

How to Avoid Cloud Vendor Lock-In: A Practical Guide for 2026

You avoid cloud vendor lock-in by keeping the parts that are expensive to move portable: the compute runtime, identity, data, networking, and deployment tooling. You accept proprietary services only where their value clearly exceeds the exit cost, so that leaving or adding a provider is a configuration change rather than a rewrite.

Canonical releases Ubuntu 26.10 Stonking Stingray

Today Canonical announced the release of Ubuntu 26.10, codenamed “Stonking Stingray,” available to download and install from ubuntu.com/download. Building on previous releases, Ubuntu 26.10 advances enterprise security features, completes the rollout of the Rust-based uutils coreutils, and strengthens integrations for user authentication using Microsoft Entra ID.

JFrog Business Value Center: Celebrate the ROI of Your Software Supply Chain

You already know the effectiveness of the JFrog Platform – blocking risky packages, speeding up builds, securing the supply chain, providing end-to-end governance and so much more. But when it comes time to renew the license, a new VP may ask: “What are we actually getting in return?” or finance wants to understand the ROI: can it really be proven by the numbers?

Stop Adding HR Tools. Start Using the Platform You Already Have | Atlassian Webinar

Tired of spreadsheet trackers, lost Slack requests, and SaaS sprawl? Learn how to turn your existing Atlassian stack—Jira, Confluence, and Jira Service Management—into a unified HR hub for recruiting, zero-touch onboarding, and compliance. Most companies run on Atlassian, but HR workflows often remain scattered across spreadsheets, endless email threads, and disconnected SaaS tools. The answer isn't another point solution or a costly rip-and-replace—it's connecting the systems you already have.

What is The Spark? Why Civo is building Britain's sovereign AI infrastructure

Every age has had its spark, the moment an idea stops being an idea and becomes something a whole country can build on. Steam, electricity and the web all began with people who could see what was possible, but each one only changed the world once someone built the infrastructure to make it real. Britain has never been short of those people. Our universities produce world-leading AI research, our engineers are among the best anywhere, and our founders build companies the rest of the world wants to buy.

AI Is Writing More Code. So Why Are Teams Getting Smaller?

AI Is Writing More Code. So Why Aren't Teams Moving Faster? AI can generate 10x, 100x, or even 1,000x more code. But there's a problem: companies aren't necessarily delivering software any faster. As AI accelerates development, it's exposing the bottlenecks, technical debt, and outdated processes that have been slowing engineering teams down all along. So what happens when the solution isn't more developers or better AI tools, but actually smaller teams?

Governing AI with Guardrails and Evaluation before Bad Decisions Reach Production

In July 2025, nine days into a public build experiment, Replit’s coding agent deleted a user’s production database. The user had declared a code freeze and told the agent not to make changes without his approval. The agent ran destructive commands anyway, wiping records on more than 1,200 executives and over a thousand companies, and then wrongly reported that the data couldn’t be rolled back. The instruction was clear, and the agent had it in context.

Your engineers already wrote your platform roadmap

At EVOLVE, Cortex’s annual engineering leadership conference, Nathen Harvey (Google Cloud’s DORA lead) asked the audience to name the biggest friction point in their software delivery lifecycle. Of 69 people who voted, none picked “building”. Reviewing changes and measuring impact nearly tied for first. Risk, security, ownership, and trust topped the EVOLVE audience's list of what keeps AI-built software out of production, and all four are platform problems.

Best open-source LLMs in 2026: ranked by cost to run

The best open source LLMs by family: DeepSeek V4 for frontier reasoning under MIT, Qwen3.8 and Gemma 4 for clean Apache 2.0 licensing, GLM-5.3 for coding, Kimi K3 for long context, Llama 4 for single-GPU scale. The real ranking depends on your deployment lane and token volume, and this guide prices all three lanes. At CloudZero, Bill Buckley, our SVP of Engineering, gives every engineer a $5,000 monthly AI token budget and published the math behind it.

Shipped: Find the GCP buckets with high cross-location read charges

You can now see which of your Multi-Region Cloud Storage buckets have cross-location read charges worth acting on, and start with the ones where a cache would save the most. It runs automatically for every organization with GCP Cloud Storage, so there’s nothing to set up. Google bills network data transfer when a Google Cloud service in one location pulls data from a Multi-Region bucket in another.

How to Turn Off GitKraken AI (GitKraken Desktop and Organization-Wide)

Let's talk about 2 ways to turn off GitKraken AI: for your own account in GitKraken Desktop, and for everyone in your organization from gitkraken.dev. Turn off GitKraken AI for your account (GitKraken Desktop) Turn off GitKraken AI for your organization (admins and owners) Optional: limit AI providers On the same Security controls page, under Enforce AI providers, turn off any provider you don't want your organization to use.

Connect Bitbucket Cloud to your AI tools with Atlassian MCP

Developers use Bitbucket Cloud every day to turn plans into working software. Code lives in repositories, feedback happens in pull requests, and Bitbucket Pipelines helps teams validate changes before they move forward. For an AI assistant to help with this work, it needs access to the same information. Without a direct connection, developers have to gather pull request details, pipeline results, logs, and links before the assistant can help.

What Infrastructure Do You Need to Run an Inference Layer? A Production Guide

A production inference layer needs GPU compute sized to the model, a serving runtime such as vLLM or SGLang, orchestration that autoscales on queue depth, one endpoint with health-aware routing and failover, model weights cached near the GPUs, and observability, security, and cost controls.

How to Build Active-Active High Availability Across Regions and Clouds

Active-active means two or more locations serve live traffic at the same time, with the application running in each and its data replicated across them, so no location sits idle waiting for a failover. You build it in five layers, and data is the hardest.

CVE-2026-74580: Possible VM Escape via the Vghost Vulnerability

CVE-2026-74580 is a high-severity Linux kernel bug in vhost, the subsystem that accelerates I/O for virtual machines. It gives a local user a reliable path to root on the host, and in some VM setups it lets a guest write into host memory. The CVE record has existed since August 21, 2026, but the full technical write-up, nicknamed "Vghost", only went public on October 12. It came with working exploit demos for both a local root escalation and a VM escape.

Data Center Rack Density Just Crossed 11kW. Do You Have the Tools and Data to Keep Up?

Uptime Institute's Global Data Center Survey 2026 found that the average modal rack density exceeded 11 kW in 2026, up from 9 kW in 2025. “Modal rack density” means the rack density that is most common within a data center. Arguably, the more important trend is that rack densities are becoming more varied, with more facilities supporting a mix of conventional and high-density racks.

Is VPA "Good Enough"? How Kubex Delivers Enterprise-Ready Workload Optimization

Kubernetes workload rightsizing is one of those tasks everyone agrees is important and almost nobody enjoys doing by hand. Set requests too high and you pay for capacity that sits idle; set them too low and you invite CPU throttling, out-of-memory kills, and late-night pages. It’s no surprise, then, that many teams reach for the Vertical Pod Autoscaler (VPA) as their first step toward automated rightsizing.

Observability Never Really Shifted Left

We made software development faster. Now we need to make validation faster, too. For the last decade we have shifted development left. Testing, security, performance, and CI/CD all moved closer to the developer. Observability mostly did not. It still starts after deployment (we covered the incident side of this in Your Observability Stack Found the Fire), which means the people writing the code rarely have meaningful production behavior to observe while they build.
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Chaos Monkey Won't Find Your Bug

We shipped a chaos feature that never caused any chaos. Our mock server has had a fault-injection effect for years with a straightforward job: withhold the response entirely and see whether the caller copes. Last week I audited it against the actual code path. It had never withheld anything. The handler returned early without writing a response. Go's net/http then did what it is designed to do, which is synthesize a 200 OK and flush the recorded body. Every experiment anybody ever ran with that effect handed the application a perfectly good answer, and every one of them passed.

Monitoring as Code with Icinga: Approaches, Tools and Trade-offs

Monitoring as code means defining hosts, checks, thresholds and notification rules in version-controlled files, and deploying them through review and automated validation, the same way infrastructure as code handles servers and networks. With Icinga you can do this with plain configuration files in Git, the Ansible collection maintained by NETWAYS, the Puppet modules maintained by Vox Pupuli, the Icinga Director, or the REST API from tools such as Terraform.

Deployment alerts: know when a renewed certificate doesn't land

Renewing a certificate is the easy part. Getting it onto the server is where automation breaks. Somebody rotates the API token on the firewall. A service account password expires. A VM gets rebuilt and the agent never comes back. The certificate renews right on schedule, the deployment fails, and the server keeps serving the old certificate until it expires. Renewed and deployed are not the same thing.

Stop Letting Deployment Approvals Slow Down Your Releases

Learn how to streamline deployment approvals with Harness CD native approval steps and configurable policies to reduce manual effort, improve consistency, and accelerate releases. Approvals shouldn’t cost you a shift. With Harness, the approval step lives inside your pipeline, so you get sign-off without the waiting and the glue code.

How we accelerated code review in a large monorepo using Agentic Pipelines

Last quarter, our AI reviewer told a developer who was fixing a CSS bug to rethink how their component fetched data. The comment was well written and confidently worded. It was also about code they hadn’t touched. That’s what tends to happen when you hand an agent every team’s review guidelines at once.

How to Add a Neocloud to AWS or GCP Without Running a Second Stack

There is no single best neocloud for AWS or GCP teams. The right one depends on the workload. Bursty fine-tuning and batch jobs reward flexible billing and low hourly rates. Always-on inference and agents reward capacity you can keep plus a second place to run, and data-heavy pipelines reward cheap data movement.

Fixes available for CVE-2026-92392 and other curl vulnerabilities

On 7 October 2026, Daniel Stenberg published a blog post describing a plan to release a new version of curl on 14 October 2026 in order to address 22 known security vulnerabilities. These vulnerabilities have varying severities, with a single vulnerability assessed as high (CVE-2026-92392), while the others have a low or medium severity. The curl maintainer has coordinated with downstream vendors, including Ubuntu, under embargo and the vulnerabilities have been publicly disclosed on the planned date.

Shipped: Drill into your cloud bill up to eight levels deep

Most cost questions have more than one layer. Which team spent the most, which services drove it, and which accounts were behind those services? Previously, following that path meant changing dimensions, adjusting filters, and re-running the query at every step. Multi-dimensional drill-down has been one of the most-requested features in Explorer. The team shipped two-level group-by earlier this year, collected feedback, and kept going. Now the path goes eight levels deep.

Dave Killeen: What to Do When Execs Demand AI

Dave Killeen will tell you, on record, that his relationship with AI has crossed into unhealthy territory. He also says he has never felt more alive, that he is 50 and feels 30, and that he sometimes waits for his two small children to go to bed so he can start a coding session. In between, he gives Axel Sooriah the most practical answer on this show yet to the question every product team is facing: your exec says "we need AI," and you have no idea what they actually want.

Is Trust the UK's Real AI Bottleneck? | Civo Navigate London

Why can't the UK make its own AI chips? David Sullivan argues that the biggest gap isn't chips, compute or electricity. It's trust. If people won't let AI near their finances, the best model in the world goes unused, and that's where the UK has a real chance to lead. Civo makes complexity a thing of the past.

Are Open Source Models the Answer to AI Sovereignty? | Civo Navigate London

Open source models are closing in on the frontier. But is running them the same as being sovereign? David Sullivan explains why true sovereignty means owning the whole model lifecycle, and why that's where prototypes stall before production. James Faure shows how distilling small, task-specific models can slash costs. Dr Rosemary Francis argues it's ridiculous to use the most expensive model for every task, and that your harness and engineering process matter more than which model sits at the top of the leaderboard.

A Hacker Used Claude to Attack 9 Banks. This Is Just the Beginning

A Hacker Used Claude to Attack 9 Banks. This Is Just the Beginning. A hacker reportedly used Claude Code and an open-source AI penetration testing agent to attack nine South Korean banks. But the most surprising part? The AI-assisted attack also helped investigators identify the suspect. Is this the beginning of a new era of AI-powered cybercrime, where attackers can launch sophisticated attacks with fewer skills and resources?

AI wrote the code. Can you prove it followed the rules?

AI agents now write, review and ship code, and our supply-chain security can't tell how that code was made. A green build and a clean scan don't tell you which model or tools the agent used, whether it had your security guidelines, or whether a human actually reviewed the change. In this talk I introduce Agentic Process Evidence, a proposed open community standard. It records the AI development process as structured, signed evidence that is attached to the commit and linked back to the full agent session logs, so release policies can enforce it automatically as policy as code.

What Is the Harness Software Delivery Agent?

AI can write code. But can it actually ship it? The Harness Software Delivery Agent helps automate the entire software delivery process, from building and testing code to provisioning infrastructure, deploying changes, and troubleshooting failures. All while following your team's approvals, policies, and guardrails. AI helps you write code. Harness helps you ship it.

The Heroku Experience for the AI Era

Ask a developer who used Heroku what they remember about it and you'll usually get some version of the same answer: you pushed your code and it ran. That feeling is back in the conversation, mostly because AI tools have made building software faster than its ever been. But speed was only half of the Heroku story. The other half, the part teams ran into a year or two later, matters just as much today.

From bug report to verified fix in a single workflow

Most debugging content shows one feature in isolation. This walkthrough covers the whole path. The bug: a discount code stopped applying for customers on annual billing plans. It passed every existing test, worked for monthly accounts, and failed only for a subset of real annual customers. Nobody had reproduced it outside production. Here's how it went from ticket to verified fix.

Every change has a story: introducing Object Level History in Flyway Desktop

You open a stored procedure to make what should be a quick fix, and something doesn't add up. There's a filter you don't recognize, or a column that has changed type, or a join that looks like it was added in a hurry. Who changed this? When? And, most importantly, why? We're excited to announce that object level history is now available for Redgate Flyway Enterprise users of Flyway Desktop.

We gave cloud agents a phone to QA

Our cloud agents now test mobile pull requests on cloud simulators and leave screenshots and a recording behind. The agent collects the evidence, and a person decides whether the change is right. More and more of the code in that app is written by coding agents. Of the 144 pull requests opened against it in the last two weeks, 99 were opened with Claude Code or Cursor. The agents are good at writing the change. What they couldn't do was show it to you.

Best Code Review Platforms for Enterprise Teams

If your engineering team operates under compliance constraints, code review is about more than catching bugs. It’s where security policies get enforced, audit trails get documented, and institutional knowledge gets shared. Choosing the right code review platform determines how quickly your developers move from pull request to production. GitKraken gives enterprise development teams a unified DevEx platform that connects code review, pull request management, and collaboration into a single workflow.

Cycle MCP 2026.10.14.02: Server Configuration, Shared File Systems, and a Clearer View of Capacity

The first update to the MCP server since launch is out now, and the theme this time is servers. Your AI assistant can now change a server’s host-level settings, set up shared file systems for your containers, and show you what’s running on each machine and how much room is left.

The hidden cost of inconsistency in engineering teams | The Simple Talk Podcast

Engineering teams' time and money are often drained by mismatched tooling and poor habits, among other things. The Redgate Advocates share their own stories of this in reality - from a mysterious 47-second retry, to the one 'rogue' engineer who derails a team. They also discuss how to get everyone pulling in the same direction without forcing everything to be identical, and whether AI helps or hurts.

12 Confluence Cloud Setups Every DevOps Team Needs

DevOps teams generate documentation constantly, and most of it is written under pressure. Runbooks are typed at 2 a.m. during an incident. Architecture notes appear in chat threads. Release steps live in one engineer's head until that engineer goes on holiday. The research backs up the cost. DORA, the program behind the Accelerate State of DevOps reports, measures documentation quality with eight metrics covering clarity, findability and reliability, and found it drives the implementation of every single technical practice it studied.

Analyze Data & Create Reports Across Databases with dbForge Edge

Analyze, visualize, and report database data across multiple database systems and cloud services with dbForge Edge. Write SQL queries or generate them with AI Assistant , analyze data with Pivot Tables, explore related records with Master-Detail Browser, visualize findings in charts, and create clear database reports — all within one multi-database solution.

Your AI Economics Pulse for October 2026

Across a same-store panel of 422 CloudZero customer organizations, AI reached 3.02% of the median company's cloud bill in September 2026, up 37 basis points from 2.66% in August, the largest monthly gain since we began tracking. The 75th percentile rose to 12.55%. The share of organizations spending at least $1,000 a month on AI barely moved, to 68.0%. Companies already spending drove the growth. Last month we called the median the least informative number in this report. September proved us wrong.

Shipped: Period-by-period costs in Explorer, no spreadsheet required

Finance teams reconcile cloud spend period by period. They want each month, week, or day in its own column, so they can scan across a row and see how a service or team changed over time. Explorer’s Aggregate view already answers “what changed and by how much.” But when the question is “what did we spend in June, July, and August, line by line,” that summary needs to become a grid.

Kimi API pricing in 2026: the K3 ladder, the August retirement, and what Moonshot really charges

Kimi API pricing, per million tokens: the flagship Kimi K3 costs $3 input and $15 output with a $0.30 cache-hit rate and 1M context. Kimi K2.6 and the coding-tuned K2.7 Code both run $0.95/$4.00 on 256K context. Kimi K2.5 and the legacy V1 family were retired August 31, 2026.

Burnout Is Rising. Here's What You Can Fix

The faster teams deploy, the more releases fail, and burnout climbs right with it. What 700 engineers told Harness about delivery at AI speed. Lenny's Newsletter put out its 2026 tech workforce survey this year, and you should read the whole thing. The headline stats: significant burnout jumped from 44.7% to 55.7% of tech workers in a year. Career optimism dropped from 54.8% to 48.7% over the same period of time.

Spin up a full-stack preview environment in seconds, zero config

A pull request goes up. The reviewer wants to see it running, not just read the diff, so someone pings the team: can I get an environment for this? Depending on who's around, that could take an hour. It could take until tomorrow. By the time the environment exists, the reviewer has moved on to something else, and getting their attention back is its own task. What if the preview URL was already sitting in the PR before anyone had to ask?

Agentic code is changing how we think about code quality

Discover how Harness Builds combines Test Intelligence, code coverage, and quality signals to help developers and AI agents validate changes faster and improve code quality. AI has changed the speed at which we can write code. Developers can move from an idea to a pull request faster, agents can work through changes autonomously, and the amount of code moving through development pipelines is only going up. But writing the code is only the beginning.

When an AI Agent Goes Rogue, Who's Responsible? | Civo Navigate London

AI agents are taking real actions in production. So when one misbehaves, who's accountable: the model provider or the company running it? David Sullivan explains why a regulated bank can't outsource accountability to an AI lab. James Faure shares how Clairo AI uses hypothesis testing and quality gates before any agent reaches production. Dr Rosemary Francis argues that guardrails which amount to a strongly worded letter won't survive. What agents need are genuine sandboxes and a limited blast radius.

FinOps for Banks: Best Practices & Cost Control

Discover FinOps best practices tailored for banks. Optimize cloud costs while meeting compliance and security needs. Learn more. Financial institutions face unique challenges implementing FinOps due to strict regulatory compliance, security requirements, and complex legacy systems. This guide covers proven FinOps strategies for banks including cost allocation, governance frameworks, and automated controls that balance innovation with risk management while optimizing cloud spending.

Inside a governed software factory: Harness and Cosmos

Learn how Harness and Cosmos build trusted, governed software factories with automated, end-to-end agent orchestration and pipeline security. Software factories can greatly accelerate software development, but concerns about trust, governance, and predictability are limiting how broadly organizations deploy them.

Best Git Platforms for Jira Teams Compared

If your team runs on Jira, the Git platform you choose can either accelerate your workflow or slow it to a crawl. Commits that never show up in your sprint board, branches that don’t link back to tickets, and pull requests that exist in a parallel universe from your backlog: these are the friction points that stack up fast for Jira-centered teams.

10 AIOps Automation Use Cases Transforming IT Operations

AIOps is often discussed as a broad technology category. That framing can make it difficult for an IT operations leader to connect the concept with the problems consuming the team’s time today. The practical question is simpler: Where does your team repeatedly lose time between detecting an issue and resolving it? Maybe engineers are drowning in alerts.

CircleCI Smarter Testing Tutorial: Run Fewer Tests and Get Faster Feedback

CircleCI Smarter Testing is now generally available. In this tutorial, we’ll show you how Smarter Testing helps you run fewer tests, get faster feedback, and reduce unnecessary CI compute with three capabilities: Then, we’ll put it to the test. For the same code change, a traditional pipeline ran all 9,716 tests across 15 nodes. With Smarter Testing, CircleCI identified just 44 impacted tests and skipped the other 9,672, cutting test runtime from 3 minutes and 56 seconds to 22 seconds.

AI at scale: are your foundations ready?

What does it take to move from AI experimentation to real-world adoption, and where does sovereign AI fit into the picture? In Episode 2 of Season 2 of Perspectives from the Edge, Andrew Dutton,Enterprise Sales & Marketing Director at SCC, joins Pulsant’s Wendy Shearer to explore the challenges businesses are facing as AI moves from experimentation into production and scale.

Harness Cost Management Agents Slash Cloud & AI Spending

Where is all your cloud and AI spending going? Harness Cost Management Agent helps companies track, understand, and reduce spending across cloud infrastructure, AI models, tokens, coding assistants, and AI agents. See who's driving costs, identify wasted spend, and get AI-powered recommendations to optimize your budget or automatically take action. It's not just about seeing your bill. It's about understanding what's driving it and how to reduce it.

Where Is All Your AI Spend Going? | Harness AI Cost Management Demo

Where is all your AI spend going? From AI coding tools and LLM tokens to autonomous AI agents, understanding what you're spending and what you're getting in return is becoming increasingly important. In this demo, see how **Harness AI Cost Management** gives engineering teams visibility into AI spending across developers, models, and applications, helping organizations track costs, manage budgets, and measure AI ROI.

Monitor Query Costs & Verify Database Changes Automatically - Harness Database DevOps + DBmarlin

See how Harness Database DevOps and DBmarlin work together to give you full visibility into query performance, automated deployment verification, and AI-assisted database change authoring - all inside your CI/CD pipeline. Most teams deploy database changes blind - they push a schema migration and hope nothing breaks. This demo shows a better way: DBmarlin surfaces the cost and performance of every query before and after a change, while Harness CV uses AI/ML to automatically detect regressions and block bad deployments from reaching production.

Top 8 Agentic Operations Platforms for DevOps Teams

DevOps automation is moving from predefined workflows toward systems that can decide what to do next. Agentic operations platforms apply AI agents to this kind of work. The category now includes systems for autonomous incident investigation, remediation, CI/CD operations, change-risk analysis, cloud optimization, reliability engineering, and other production tasks. The more advanced platforms also provide the infrastructure needed to operate agents themselves, including shared context, memory, orchestration, permissions, evaluations, human approvals, and cost controls.

Data Analysis & Reporting Across Databases and Cloud Services With dbForge Edge

Analyze data and create reports across multiple database systems and cloud services with dbForge Edge. dbForge Edge brings SQL querying, data analysis, visualization, reporting, and automation into one multi-database solution. Use the built-in SQL development tools and AI Assistant to retrieve data, analyze large datasets with pivot tables, inspect related records with Master-Detail Browser, visualize findings in charts, and create clear and compelling data reports.

Understanding Agentic Development Environments

AI coding agents are rewriting the rules of software development, but running multiple agents across a real codebase creates a coordination challenge that traditional editors and terminals weren’t built to solve. That’s where agentic development environments come in. An agentic development environment (ADE) gives you a dedicated surface for launching, orchestrating, and reviewing the work of several AI coding agents at once.

The NSA said wildcard certificates are bad. Everyone uses them anyway.

In October 2021 the NSA published an advisory titled “Avoid Dangers of Wildcard TLS Certificates.” It reiterated what security consultants had been saying for years: don’t use wildcard certificates. Single-name certificates per host are safer. Five years later, we counted the certificates that are actually used. One in three domains has a wildcard on it. For.bank domains, where you need a security review just to register, it’s four in five. Operators aren’t careless.

Cut your debug time by reproducing production on demand

If a bug only shows up under real production conditions, the fastest path to a fix is removing the guesswork about those conditions, not layering on more debugging tools. This guide walks through what changes when every branch gets its own preview environment, a full clone of production available on demand, and what that actually looks like day to day.

Myna speech-to-text is now available as a technology preview

A few months ago, we introduced Myna, our project to bring private, local speech-to-text dictation to Ubuntu Desktop. Named after the speech-mimicking myna bird, Myna is an optional Ubuntu 26.10 feature that offers real-time visual feedback during speech recognition. Since then, Myna has grown into something you can install and use on your desktop. Today, we’re making it available as a technology preview to the wider Ubuntu community.

The Citrix Security Crisis Exposed a Bigger Problem

Citrix was facing a major security crisis before its official warning even went out. Companies were already pulling critical network devices offline as attackers exploited serious vulnerabilities in Citrix NetScaler ADC and Gateway systems. In this ShipTalk clip, Adam, Martin, and Starr break down the Citrix zero-day vulnerabilities, the race to respond, and the impossible decision facing security teams: keep potentially compromised infrastructure running or rush to deploy a patch.

DevOps Team Extension: Qovery engineers watching your infrastructure every month

DevOps Team Extension gives growing engineering teams a named Qovery engineer, a continuous infrastructure scan, and a monthly remediation plan, so they can scale reliability, security and compliance without hiring a DevOps team first. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

Replacing ingress-nginx with Envoy Gateway on Hundreds of Clusters: What the Plan Missed

In February we planned to move every Qovery-managed cluster from ingress-nginx to Envoy Gateway by the end of March. It took until October. Here is the rollout model, every class of problem we hit, and what I would do differently. Benjamin is a staff engineer at Qovery focused on infrastructure automation, Kubernetes internals, and building the deployment engine that powers thousands of clusters.

Inside a DevOps Team Extension engagement: an infrastructure review and a Typesense architecture session

How Qovery assessed a growing B2B SaaS company's infrastructure across about 150 controls, what the review with their team changed, and why a Typesense high-availability project turned into a sharding plan. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

Digital Sovereignty Panel: Who Really Controls Your Data? | Civo Navigate London

Your data sits in the UK. But who has the final say over it? As AI raises the stakes on where data lives and who controls it, digital sovereignty has moved from policy debate to boardroom priority. At Civo Navigate London, Lord Paul Drayson, Simon Hansford, Richard Woodfield of DataVita, Dan Chester of VAST Data and Ed Barker of Havishams explore what sovereignty really means for governments, businesses and the infrastructure behind them, and what it will take for the UK to adopt AI without giving up control.

SecureBridge 12.1, EntityDAC 4.1, and dbExpress drivers: Support for RAD Studio 13 Florence Release 2, SQL Server 2025, and MySQL 9.7

New versions of SecureBridge, EntityDAC, and dbExpress drivers are out. All three now work with RAD Studio 13 Florence Release 2 and offer improved support for the Arm64EC target platform. Devart dbExpress drivers also add support for Microsoft SQL Server 2025 and MySQL 9.7, while SecureBridge gains SFTP upload resume, multipart/form-data support, and a new SSL/TLS demo.

What Is High Availability? How It Works and How Many Nines You Actually Need

High availability (HA) is a system’s ability to keep serving users when individual components fail, from a single server up to a whole cloud region or provider. It is measured in nines: 99.9% allows about 8 hours 46 minutes of downtime a year, 99.99% about 52 minutes, and 99.999% about 5 minutes 15 seconds. HA works by removing single points of failure through redundancy, health checks, automatic failover, and replicated data.

Why AI SRE Agents Need More Than Observability Data with Groundcover | Civo Navigate London

Your AI agent can read every log, metric and trace in seconds. It still can't tell you why things broke. At Civo Navigate London, James Herbert of groundcover explains why AI SRE agents need that context to travel the whole development lifecycle. He shows how agents embedded in the tools where software is built and run can move from isolated tasks to investigating and acting with the full picture.

Deploy Your First App with Harness CD in Under 15 Minutes

Deploy your first app with Harness CD in under 15 minutes. Learn how to build, configure, and execute a rolling deployment using a real sample application. TL;DR: Deploying shouldn't feel like crossing your fingers. With Harness CD, you set up your deployment once and get rollback and a full history of what shipped, without writing it all yourself.

From Git Repo to Docker Image: Building Your First CI Pipeline in Harness

Connect GitHub, let Harness generate your CI pipeline, then build and push a Docker image to DockerHub. No YAML required. Creating your first CI pipeline usually sounds simple until you actually start. You connect your repository, figure out what stages you need, configure the build steps, set up the runtime, add caching, testing, credentials, and then hope the first run actually works.

How we investigate Sentry errors with an AI agent

We built an AI agent on Qovery to investigate Sentry alerts before our team picks them up. Here’s how the workflow runs, what it delivers, and where engineers still need to step in. Rémi is a staff frontend engineer at Qovery. He writes about frontend architecture, developer experience, and building scalable UI systems for platform engineering tools.

Building AI SRE Agents, Part 3: Autonomous in the Cloud

Your agent has earned trust in shadow mode. Now it runs on its own: an alert fires, the agent starts, investigates and proposes a fix before anyone opens a laptop. Here is what it takes to make that safe, scalable and better every week. This is the third article in a series on taking an AI SRE agent from a weekend experiment to production. Part 1 built a local, read-only agent on a throwaway cluster and refined it against a synthetic eval set.

10 Best AI Agent Infrastructure Platforms in 2026

AI agent infrastructure is the set of platforms that run agents and the code they write. It has three layers: sandboxes that isolate untrusted, model-generated code, runtimes that run the agent and its services in production, and orchestration layers that save an agent’s progress so a long run can resume after a failure. Most production agents need more than one layer. This guide compares 10 platforms across all three, with isolation, state, deployment, and compliance for each.

When AI agents ignore the code freeze: governance that holds | EVOLVE 2026

AI can write 1,100 lines of code for a loading spinner in five minutes. Your change board still meets once a week. Karthik Jayaraman, VP of Information Technology at Fiserv, explains what happens when code generation speeds up and everything downstream stays the same. He covers why "human in the loop" doesn't scale, why handing all review to AI backfires, and why an agent told not to touch production needs a boundary it can't cross, not just an instruction.

AI is making software delivery less stable. DORA's Nathen Harvey on the fix | EVOLVE 2026

DORA's data shows that as AI adoption goes up, individual effectiveness rises, and so does software delivery instability: more rollbacks and more unplanned rework. Nathen Harvey of Google's DORA team explains why AI acts as an amplifier of whatever system you already have. He walks through the seven capabilities that separate teams getting real gains from teams drowning in downstream chaos. He also argues that the risks stopping you from shipping AI-built work should become your platform roadmap.

Shipped: Project this month's AI cost before the invoice closes

The question comes up on the 10th, the 15th, and again on the 25th. Where is AI spend going to end up this month? The invoice won’t tell you until it’s closes, and by then there’s nothing left to forecast. “If I’m looking at this on the 15th, I want to know where we’re going to land.” That’s how a finance lead put it during a persona session in September, and it’sthe whole job. You have half a month of real usage behind you.

Claude Opus pricing in 2026: every model, every rate, and whether it's worth it

Claude Opus pricing is $4 per million input tokens and $20 per million output tokens on Claude Opus 5.5, the current model, with cache reads at $0.20 and batch jobs at $2/$10. Opus 5 and the legacy 4-series bill at $5/$25. The 1M context window carries no surcharge. Every Opus model Anthropic shipped in 2026 held the same line: $5 in, $25 out, per million tokens. Opus 4.6 in February, 4.7 in April, 4.8 in May, Opus 5 in July. Four releases, one price. On September 22, 2026, the line broke.

AI Finds and Fixes Security Vulnerabilities | Harness Demo

What if AI could find a security vulnerability, determine whether it actually matters, write the fix, validate it, and open a pull request for review? In this demo, see how Harness Security Testing Agents work together to move from vulnerability detection to a verified fix with an audit trail along the way. The system uses three agents: Harness can analyze where vulnerabilities exist in your environment, determine whether they’re actually reachable, prioritize what needs to be fixed, and automatically create remediation pull requests.

What is Spotify Backstage?

Summary Spotify Backstage is a free, open-source framework for building internal developer portals, with a software catalog, templates, TechDocs, and a large plugin ecosystem. It’s a strong fit if you have a dedicated platform team that wants to build and run its own portal. If you want a current catalog, enforced standards, and org-level reporting without maintaining the infrastructure, a managed platform like Cortex is the better fit.

The Five Levels of the Enterprise AI Software Factory

Scroll LinkedIn for ten minutes and you'd think every engineering organization already runs an autonomous SDLC, with agents writing, reviewing, and shipping code while humans watch. Inside large enterprises, the picture looks different. Coding agents there have to work around sensitive customer data, recurring compliance audits, a larger attack surface, downtime that costs millions, and a CFO who wants to know what last year's token spend bought.

Managing Hybrid Infrastructure and Multicloud Without the Overhead

Building and managing hybrid cloud infrastructure is an increasingly common requirement for engineering teams. Some companies want to cut hyperscaler costs. Others have business continuity requirements that mean spreading infrastructure across several providers. Either way, more teams are taking hybrid cloud management into their own hands.

Redgate Monitor is a Leader in G2's Fall 2026 database monitoring report

G2's Fall 2026 Grid Report for Database Monitoring is out, and Redgate Monitor is named a Leader. G2 builds its reports from verified user reviews rather than paid placement, so this recognition comes from the people who use Redgate Monitor every day, and took time out of their lives to tell others what it's like. So, a big thank you to our customers, we're grateful for every review.

7 Layers of Agent Security (1 in 6 repos has leaked credentials)

I scanned 10,705 public GitHub repos for leaked credentials. After removing obvious placeholders, 3,543 still had something that looked like a key, and 1,680 held almost 7,000 credentials in recognizable formats like Stripe keys. If you're new to coding with agents (or you've been a dev for decades), this is the setup I'd want you to have before you ship anything public.

Harness acquires Augment Code to advance the Autonomous SDLC

Harness Cosmos Software Factory Agent automates engineering from idea to code, connecting code context with delivery, security, testing, and production workflows. The world runs on software. Better healthcare, more accessible financial services, more efficient businesses, and better everyday experiences all depend on our ability to build and improve it. AI is making that faster, but the outcome that matters is not simply how much code we generate.

Capacity Planning Under Constraints: An Off-Grid Analogy for Edge Deployments

When laptops, mobile hotspots, lighting, portable power stations, and other electronics all need to operate at an off-grid campsite, the question is no longer simply how many devices were packed. It is how much workload a limited pool of resources can support. From a capacity-planning perspective, this makes an off-grid campsite a useful analogy for an edge deployment: power is limited, connectivity is unreliable, physical space is constrained, and every component has to be deployed again on arrival.

The 5 levels of the AI software factory for enterprises | EVOLVE 2026 keynote

Everyone online seems to have a fully autonomous SDLC. Most enterprises are still at level 3, and they'll be there for years. In the EVOLVE 2026 opening keynote, Cortex co-founders Anish Dhar (CEO) and Ganesh Datta (CTO) lay out a practical maturity model for getting from AI coding agents to an AI software factory without blowing up cost, quality, or security along the way. They've watched hundreds of engineering orgs adopt AI over the last two years. This talk distills what separated the successful rollouts from the chaotic ones.

That 2am incident cost you more than downtime

It's 2:14am. A pager alert wakes an on-call engineer for a checkout failure hitting a slice of customers. By the time they've pulled the right logs, cross-checked the deploy history, and finally gotten the bug to happen again in front of them, the sun's coming up. The incident report will list two hours of downtime. It won't say anything about the day that engineer just lost, or the fact that nobody on your team could have told you in advance how long that reproduction step was going to take.

Certificate monitoring with TLS, chain, and post-quantum readiness

Most customers start CertKit with SSL host monitoring. On day one, you point CertKit at the systems you already run and get every certificate and when it expires. You start with confidence that you have everything under control. Then, you automate, letting CertKit take over the certificates as they need to be renewed. Each renewal is the last time you ever have to worry about that certificate.

10 Best Multi-Cloud Management Platforms in 2026

A multi-cloud management platform is software that lets you run, provision, govern, or optimize workloads across two or more environments, such as AWS, Google Cloud, Azure, and your own data centers, from one place. The products in this category do different jobs: some run your applications across clouds, some provision infrastructure as code, some govern hybrid estates, and some optimize cost. Most teams combine two or three.

Shipped: Views now work for every access level

Most people who open CloudZero care about one slice of the spend, like their team, their product, or their region. A View gives them that slice in one click, with the grouping and filters already set, so nobody has to rebuild the same Explorer query every week. Views now work for everyone in your organization, including people with scoped access.

Context Engineering for AI Agents: What to Feed an Agent and What to Leave Out

Picture a Monday at 03:10 UTC. An agent investigating an out-of-memory alert on payment-service works out the pattern: it runs out of memory every Monday between 03:00 and 04:00, and the spike lines up with the batch reconciliation job. The next Monday the alert fires again. A different agent picks it up and starts from zero, because nothing it can see holds what the first one learned.

How to Resolve Git Merge Conflicts in 8 Easy Steps (2026)

A Git merge conflict happens when two branches edit the same line of code in different ways. Git can’t decide which version to keep, so it pauses the merge and asks you to step in. The longer a conflict sits unresolved, the harder it becomes to untangle. This guide walks you through eight clear steps to identify, fix, and verify merge conflicts during your branch merging workflow. GitKraken gives you a visual merge tool that turns this process from guesswork into a few confident clicks.

Announcing Gremlin Foresight AI

Today we're launching Foresight AI, Gremlin’s agentic resilience product that analyzes and tests your systems for potential failures, fixes them, and verifies reliability at the speed of AI. I've spent most of my career on call. At Amazon and Netflix, I served as a Call Leader, the person running the bridge when something big broke. Those years taught me the same lesson we founded Gremlin on: the best incident is the one that never happens.

Why AI development creates a reliability blind spot for humans, and what to do about it

Application development and operations teams are adopting AI coding tools at an exponentially increasing rate, from a rounding error of 6% of code output by AI in 2023, to as much as 51%-75% for a majority of enterprises. Agents are making pull requests (PRs) faster than human developers could have ever dreamed. As features are pushed to market faster, there’s a sharp increase in production incidents, with 80% of development shops specifically tracing production outages to AI.

Air-Gapped vs Private Network Backup: Which Is More Secure?

Compare air-gapped and private network backup approaches for ransomware defense, data protection, and secure recovery. Ransomware doesn’t stop at production data. Attackers are increasingly targeting the backups organizations depend on for recovery, turning a manageable incident into a much longer outage. These attacks make the choice between air-gapped and private network backup important — but it isn’t an either-or decision.

Companies Are Ripping Citrix Devices Offline. Here's Why

Citrix NetScaler customers were pulling devices offline as attackers moved faster than the traditional patch and response cycle. What happens when cyberattacks move faster than security teams can react? In this episode of ShipTalk, Martin Reynolds and Adam Arellano are joined by Starr Brown, Director of Open Source Projects at OWASP, to break down the latest Citrix NetScaler ADC and Gateway security vulnerabilities, active exploitation, and the rapidly shrinking window between vulnerability discovery and attack.

AI Investigation for ITOps: Faster Root Cause with Edwin AI

AI investigation for IT operations finds the likely root cause of an incident and shows the evidence behind it. This video covers how deep AI investigation works for ITOps, SRE, and platform engineering teams using LogicMonitor's Edwin AI. Engineers lose time stitching together alerts, logs, and recent changes after an alert fires. Deep AI investigation hands that first pass to AI agents, so your team starts closer to the fix. Edwin AI, LogicMonitor's AI agent for ITOps, correlates alerts, identifies root causes, and recommends remediation.

pgvector for RAG: When you don't need a dedicated vector database

Dedicated vector databases have become such a standard part of the RAG conversation that teams often add one before they have proved they need it. According to studies, over 70% of companies using LLMs are using vector databases and RAG to customize their models. That shows how quickly the pattern has become normal. However, it does not mean every RAG application needs a separate retrieval system. If your application already runs on PostgreSQL, pgvector may be enough.

Holiday readiness: run your first load test with skills

Before you can answer whether checkout will survive Black Friday, you need a test you can rerun. In this demo, we used a coding agent and the Speedscale skills to record a Node app, mock its downstream API, and run a 30-second load test with 10 virtual users. That’s a small first step in holiday readiness. It gives you a working test and a result to inspect, with time left to fix what you find before a code freeze.

Beyond Traditional Observability: Turning Technical Insight into Operational Intelligence

Observability has become a central part of modern IT operations and for good reason. Metrics, logs and traces give technical teams detailed evidence about how applications, infrastructure and services are behaving. Such evidence helps them investigate performance degradation, identify abnormal behavior and understand what changed around the time an issue occurred.

Why We Built the Komodor Agentic Operations Platform: Q&A with CEO Ben Ofiri

Komodor spent years building an AI SRE platform before the category had a name. With the launch of the Komodor Agentic Operations Platform, it’s opening that engine up so enterprises can build, run, govern and optimize their own agents in production. Following the launch, co-founder and CEO Ben Ofiri sat down to talk about why now is the right time for agentic operations, what breaks between prototype and production, and where operations will head next.

Best Code Review Collaboration Platforms for AI Teams

Your team ships more code than ever, but are your pull requests keeping pace? As AI-assisted development accelerates output, code review collaboration platforms have become the difference between shipping confidently and merging blindly. The right platform connects your review workflows, surfaces context where you need it, and keeps collaboration flowing across distributed teams.

AI Agent Context Explained: What Agents Can't See in Your Infrastructure

The "C" word is a controversial subject in the US, but we have to talk about "context", and what it means to an AI Agent. For starters, agents can only act on what's in their context window. Everything outside of it is a guess. In application code that limit is usually an annoyance.

Manage Governance with Puppet Enterprise

Learn how Puppet Enterprise helps organizations strengthen infrastructure governance through role-based access control, audit-ready reporting, and controlled change management workflows. In this demo, Senior Sales Engineer Nelson Gomez walks through key governance capabilities in Puppet Enterprise, including: Whether you're supporting security initiatives, audit requirements, or operational governance, Puppet Enterprise helps teams maintain control while accelerating infrastructure automation.

Run your first workflow in minutes, no sales call

The regression nobody catches passes a busy review and ships. An off-by-one, a change that reads as sensible and quietly breaks something, gets a nod from a tired reviewer and lands in production, where it erodes trust one small defect at a time. You can have an AI code reviewer running on your own repository in the time it takes to read this page. Get started without having to book a demo or contact sales.

Canada Data Center Development: Measuring Responsible AI Growth

Western Canada is becoming a live test of whether sovereign AI capacity can be built responsibly at scale, and the answer will depend less on what operators promise than on what they can measure and show. Meta’s planned C$13-billion Alberta data center, BCE’s expansion of its Saskatchewan project to a 1.2-GW hub, and the federal Responsible Data Centre Development Principles all point to the same requirement: operational transparency that regulators, utilities, and communities can verify.

Shipped: See what your AI spend is actually paying for

Most AI spend comes in with no tags and no owner attached. Your provider console shows total spend, maybe broken out by API key or model. It won’t tell you that the sales team spent $1,700 on Claude this week, let alone what the work was. And the problem is growing. McKinsey found that 56% of organizations now use AI in three or more business functions. More teams means more spend, and most companies respond with a spending cap. Set it too low and you slow down the work you wanted AI to help with.

Ship faster, improve reliability, and control CI costs with Datadog CI/CD Optimization

AI-assisted development can increase the rate at which teams produce code, but teams only realize those velocity gains if CI can keep pace. More pull requests (PRs) mean more builds, tests, and pipeline executions. Slow jobs leave developers and coding agents waiting for feedback, flaky failures consume time in reruns and investigations, and unnecessary test execution increases runner demand as delivery volume grows.

How savepoints quietly throttled our Postgres queue

At incident.io we are huge fans of Postgres; we've written about it a lot over the years, including how to choose the right indexes and how we're proud of being boring (The Pet Shop Boys). We use Postgres as our primary transactional database, which as of today has ~900 tables, and counting! The vast majority of our codebase does something along the following lines: read some data from Postgres, execute some business logic, then write that data back to Postgres. It is not, however, always that simple.

How to Guarantee a Website or Service Never Goes Down (And What You Can Actually Promise)

No one can guarantee that a website or service never goes down. What you can promise is a measured availability target, and with a multi-location, active-active design you can reach 99.999% (five nines), about 5 minutes 15 seconds of downtime a year. That takes redundancy at every layer, automatic health-based failover across regions and ideally providers, safe deployments, failure testing, and outside-in monitoring. Control Plane is built for that tier.

Alibaba's AI Agent Went Rogue and Started Mining Crypto

An Alibaba-affiliated AI agent went full crypto bro. During reinforcement learning, the agent autonomously started mining cryptocurrency, downloaded the tools it needed, and created a reverse SSH tunnel to get around network restrictions. What starts as a funny story about an AI vaping and mining crypto gets a lot more serious when you realize how sophisticated the behavior actually was.

18: Building an Agentic Future: AI and Optimization with Sachin Gharge

On today's episode, Andrew Hillier chats with Sachin Gharge, Head of Cloud Platform at Scandinavian Airlines (SAS). They discuss AI, agents, Kubernetes, MCP, and optimization. Sachin shares how he and his team are optimizing cloud costs, leveraging automation, and experimenting with agentic AI, including bots and Slack integrations, to make operations easier and more effective for developers and the business.

Building a Self-Service Knowledge Base Employees Want to Use

Most organizations already have policy documents, troubleshooting guides, knowledge articles, resolved tickets, runbooks, and internal wikis. They're not starting at zero, but despite that investment, employees continue to open tickets for questions the organization has already answered. The problem is not always a lack of knowledge. More often, employees cannot find the right information quickly enough to trust self-service as their first option.

Where the Future Runs: Reinventing Infrastructure for the AI Era | Civo Navigate London

The data centre was built for a different era. Racks drawing more power than entire rooms once did, heat that air alone can't carry away, and inference that needs to run close to the work are forcing a rethink from the ground up. In this fireside chat from Civo Navigate London, Civo CEO Mark Boost, Anthony Sarno and Josh Mesout explore how the demands of AI are reshaping the data centre and challenging traditional approaches to cloud infrastructure.

Load Test PostgreSQL Instantly using Production Recordings

The first PostgreSQL post ran on a laptop: a demo app, a Docker container, and the proxymock CLI. That is the fastest way to see the idea. It is also not where your database problems live. Your real query mix lives in the cluster, where a Java service with a connection pool, an ORM and a schema migration tool sends the statements nobody wrote by hand. This post deploys an open source banking app to Kubernetes and records the queries one of its services sends to PostgreSQL.

Knowledge Graphs for Software Delivery: An Architectural Approach

Discover how software delivery knowledge graphs unify fragmented SDLC data, enable schema-as-code, and power deterministic AI reasoning across engineering teams. Software delivery knowledge graphs unify fragmented SDLC data across disparate tools by establishing explicit entities, typed relationships, and schema-as-code contracts. This transforms manual cross-system data stitching and non-deterministic AI reasoning into reliable, queryable knowledge. Key takeaways include.

How Agentic AI Could Change Global Network Deployment

From the Alibaba Cloud Apsara Conference stage, here's a look at how Agentic AI, APIs, and NaaS could simplify network deployment and automate routing decisions. At this year’s Alibaba Cloud Apsara Conference in China, I was honored to represent Megaport on stage to present our live demo session “Alibaba Cloud × Megaport: Making Agentic Networks Simpler”.

Shipped: Start every session where your work lives

Most people who use CloudZero spend their time in one or two places. For some it’s AI Signals, and for others it’s Optimize or Anomalies. If Explorer isn’t one of those places, every sign-in starts with a click to get where you need to be. Dates and numbers are another friction. A date like 04/07 means April 7 in the US and July 4 in much of Europe. When the platform shows a format your team doesn’t use, you end up having to convert each value before you can work with it.

The Next AI Breakthrough? Teaching AI to Shut Up and Decide

Jev is a new AI model from Type Safe built around a very different idea: instead of generating long answers, it makes fast, simple decisions. The team reportedly even demoed it playing Doom using nothing but split-second choices. After years of teaching AI models to talk, could the next breakthrough be teaching them to simply decide?

Watch an AI Agent Fix a Failed CI Build | Harness Worker Agents

What happens when an AI agent can do more than suggest a fix — and actually take action inside your CI pipeline? See Harness Worker Agents in action as an AI agent identifies a failed CI build, determines what went wrong, creates the fix, and gets the pipeline moving toward production again. Worker Agents bring AI-powered reasoning directly into your software delivery pipelines while maintaining the controls enterprises need, including sandboxed execution, scoped credentials, policies, and RBAC.

File, object, or block storage: what's the difference?

Choosing where your data lives is only half the question. How it's stored matters too. File, object, and block storage are each built for a different job. File storage uses the hierarchy you already know. Files live inside folders, and those folders can live inside other folders. Object storage gets rid of that hierarchy. Each piece of data is stored as its own object, which makes it easy to scale.

Distributed Tracing In Netdata: OpenTelemetry Traces

Back in 2020, when we laid out where Netdata was going, the plan listed anomaly detection, log collection and “application traces collection”. The first two shipped years ago. Traces took longer, because we wanted them to work the way the rest of Netdata works: collected and stored on your own nodes, with no separate backend to stand up. Distributed tracing is now available in Netdata.

Get your agents off laptops and onto shared infrastructure

There's a specific, recognizable point where a team's use of AI agents changes shape. Not when they adopt agents; most teams already have. It's when agents stop running on someone's laptop and start running on infrastructure that the whole team can see. This is a real technical shift, not a policy change or a maturity score. Here's specifically what's different on each side of it.

The Missing Piece in Your AI Coding Agent #aiagents #aitools #devops #debugging #softwareengineer

Stop making your AI coding agent guess how your app works with massive prompts. We feed live API traffic and runtime evidence directly into your agent so it can automatically detect bugs, run replays, and fix code fast! Learn more: speedscale.com.

Deutsche Bank leads the way on secure adoption of AI enabled software delivery

As AI accelerates software development and expands its scale, Deutsche Bank is taking a leading role in ensuring the technology can be adopted safely, securely, and responsibly across regulated industries. As an investor, Deutsche Bank’s Corporate Venture Capital arm participated in Kosli’s Series A funding round, reinforcing the bank’s view that automated governance will be a key enabler of AI-assisted software delivery in regulated industries.

What's taking DNS-PERSIST-01 so long?

In February, Let’s Encrypt announced that DNS-PERSIST-01 was coming, “some time in Q2 2026.” It’s October, and it’s nowhere close to ready. We’ve been waiting for DNS-PERSIST-01 since January, along with every other ACME client and lots of organizations. DNS-PERSIST-01 promised to simplify domain validation and make automation easier, but we had to wait on Let’s Encrypt. Let’s Encrypt is waiting on a redesign, a standards body, and maybe one more vote.

Judgment, not generation: rebuilding our AI API Classifier on Jev

Rebuild AI API classification with Jev to cut costs, reduce latency, improve calibration, and make production decisions more efficient without sacrificing accuracy. Replacing the judgment step in a production classification pipeline with a purpose-built decision model changes the economics of the problem entirely.

Who Built This Dashboard, and Are They Still Here?

You have lived it, no? When production is down, and you have that chart that says something really strange and peculiar, and nobody knows who did it or when. Production is bleeding. There is a spike on screen. And the chart answers everything except the question you actually have: who built this panel, what did they mean by it, and are they still here?

Where do you see organizations hitting their limits?

In this clip, Virtana Chief Product Officer, Amit Rathi explains why more data does not automatically lead to better operations. As system complexity grows, organizations are collecting more telemetry than ever while struggling to turn it into actionable insights. At the same time, rising observability costs are forcing some teams to monitor only part of their environments. Watch the video to learn why intelligence, not just visibility, is becoming essential for modern IT operations.

Your code says one thing. Your cloud says another. Meet EZ Control. #platformengineering

EZ Control brings env zero and CloudQuery together in one product. It discovers nearly 2,300 resource types across AWS, Azure, Google Cloud and Kubernetes, links each one to its code, owner, cost and policies, and closes the gap when what's running drifts from what you intended: drift, security, cost and availability, all under your policies. You choose how much it does, from observe-only to autonomous, with a full audit trail. The same guardrails govern AI agents.

GitKraken Desktop 12.6 Release: Stacked GitHub PRs, Multiple Terminal Tabs

Ready to interact with the stack? GitKraken Desktop 12.6 makes it easier than ever to ship large features and manage multi-task terminal workflows without context switching or losing track of your work. What's new in 12.6: Stacked GitHub Pull Requests: Start a pull request stack against a branch that already has an open PR to break large feature branches into smaller pieces. Stack Visibility Everywhere: View stack position, status, and sequence numbers across the Left Panel PR list, the Pull Request view, and the Commit Graph.

Best Version Control Platforms for Teams in 2026

Your distributed team just merged three branches at once, and the commit graph looks like a plate of spaghetti. Choosing the right version control platform determines whether that scenario ends in a five-minute fix or a full afternoon of detective work. GitKraken gives you a visual, cross-platform approach to Git that turns complex repository management into a clear, collaborative workflow.

What Is GitOps? Principles, Benefits, and How It Works

With GitOps, you can roll back your cluster with git revert and explain each approved change through a commit log. Routing normal changes through Git and running an in-cluster agent that detects drift from the repository gives infrastructure changes the same review and rollback discipline as application code, and Git preserves their history. This guide covers the four GitOps principles, the pull-based reconciliation workflow, and the tools and practices you need to get started.

Fully Autonomous Software Delivery Demo

See how Harness helps teams move from AI-generated code to production at machine speed. In this demo, Nick Durkin walks through a fully autonomous software delivery workflow inside Harness, showing how teams can review code, enforce policy, run security and LLM scanning, test intelligently, deploy agents, and use Change Advisor to automate approvals with human oversight when needed. You’ll see how Harness helps teams.

Why engineers ignore cloud cost governance (and fixes)

Discover why engineers ignore cloud cost governance and how to build developer cost accountability. Learn how Harness helps empower engineering teams. Engineers often overlook cloud costs due to friction in traditional FinOps tools and a lack of real-time visibility. By embedding automated guardrails and shift-left cost insights into developer workflows, organizations can drive accountability without slowing velocity.

Building Production-ready AI Infrastructure? Start With the Network

AI workloads depend on fast, secure, and scalable access to data across on-premises systems, colocation, cloud platforms, and GPU environments. Here’s how private connectivity can help enterprises move from AI proof of concept to production-ready infrastructure. AI pilots tend to be forgiving. Production isn’t. In the early stages, a team can usually get by with a simple path into a GPU environment, enough bandwidth to test an idea, and a security model that suits a limited group of users.

Intent-driven development: How to guide agents from idea to implementation

Intent-driven development (IDD) is an approach to AI-assisted software development where teams make the desired behavior, constraints, and criteria for success explicit, then give an agent freedom to determine how to achieve the result. As agents take on larger and more autonomous development and maintenance tasks, the implementation itself becomes easier to replace. The important question is whether the software still behaves the way the team intended.

Cloud Shell, New Integrations, and More

VirtualMetric DataStream now includes a PowerShell console in the browser, more than a dozen new integrations, and a new way to collect data from servers and virtualization hosts, where teams choose exactly what they collect. This update also brings guided learning for new users, built-in monitoring rules, and new controls for organizations managing branding and sign-in. Here’s what’s new.

Shipped: Get alerted when AI spend spikes, with the cause attached

AI spend now comes from every department, and it can double in a week without anyone deciding it should. The invoice arrives after the month closes. By then the usual response is a spend cap, which slows every team, including the ones getting real work done with AI. You need to know about spend that breaks its normal pattern while there’s still time to act. The alert should reach the person who can act on it, with proper context and detail.

Introducing Distributed Tracing in Netdata

Netdata now supports distributed tracing. In this webinar, we'll demo the new tracing capabilities for the first time: OpenTelemetry trace ingestion, the new tracing dashboard, and the UI built to let you move from a metric anomaly to the exact span that caused it. For years, teams have asked us to close the gap between infrastructure monitoring and application performance. This release does that. Netdata can now ingest traces via OTEL, correlate them with the metrics and logs you already collect, and surface them in a purpose-built interface designed for speed and clarity.

Fleet Monitoring with Netdata: Live Demo

A walkthrough of monitoring a distributed fleet with Netdata, using a simulated fleet of about 1,000 devices spread across regions. We show how the whole fleet reports into a single view: per-second metrics from every node, grouping by region and by customer, a map view that colors each device by health, filtering and saved views for different teams, and an AI-assisted investigation that scans the fleet for anomalies and points to likely causes.

AI Tooling Comes to Cycle - Announcing Cycle's Hosted MCP

TL;DR - We made a way to use Cycle with AI models for doing things like deploying applications faster and diagnosing complex issues. If you'd like to get started right away with Cycle's Hosted MCP, check out our documentation. Today, we're launching a brand new way to interface with the Cycle Platform, that just a year or two ago would have felt entirely like science fiction. Our first ever AI-oriented tooling, Cycle's Hosted MCP, is live today.

Megaport Advanced Services: From Network Design to Deployment

Network changes often stall after the design is done. See how Megaport Advanced Services helps teams move from planning to implementation and support. Ask a network team where their last big network change got stuck and you’ll rarely hear “we couldn’t work out the design.” The completed design is usually sitting in a document somewhere, reviewed and signed off. What stalls is everything needed after that. Somebody has to write the runbook. Somebody has to sit in the 2 a.m.

Best ADEs for Multi Agent Coding in 2026

Running one AI coding agent is productive. Running five of them at once across three repositories? That’s a coordination problem. Agentic development environments (ADEs) give you a single surface to orchestrate multiple agents, review what each one changed, and get code merged. Kepler by GitKraken is one of the most capable options in this growing category. It’s built around agent-agnostic orchestration and Git workflow control from backlog to merged PR.

The hidden costs of AI (and who ends up paying them) | The Simple Talk Podcast

AI budgets are escalating rapidly, yet few teams measure the value of their spend – and who ends up paying, anyway? The Redgate Advocates discuss that, LLMs, data centers, regulation, what happens to the next generation of engineers if they never learn to solve problems the hard way – and more.

Android belongs in your CI/CD pipeline

How on-demand Android environments turn validation into a repeatable pipeline stage In the first article, we looked at automation: how Android environments can be created and managed programmatically. In the second, we looked at scaling: how shared infrastructure can make those environments available to more developers, tests, and workloads. This third article looks at the next step: integrating those environments directly into CI/CD.

Cycle's Hosted MCP Release Announcement

We are stoked to announce that we have released our very own hosted MCP that allows you to use natural language to interact with and control anything you have running on Cycle.io. Alexander Mattoni, CTO and co-founder of Cycle, shares a few scenarios where the MCP can be useful. With the MCP, Cycle users can communicate with the Cycle platform directly from their preferred AI tool. In minutes, users can provision a new server, deploy an application, or troubleshoot an issue directly from their AI assistant like Claude, Claude Code, ChatGPT or Codex.

Building Investigations: what it takes to build an AI SRE

At incident.io, we've spent the last two years building Investigations, our AI SRE. When you get paged, it starts investigating straight away, looking across your telemetry, recent deploys, past incidents, docs and code, and posts what it's found in your incident channel (or on your phone, if it's 2am and you're still deciding whether you need to get out of bed). By the time you open your laptop, you're starting at step six of triage rather than step one.

EVOLVE 2026 Recap: Operational Excellence for the AI-Native SDLC

Last week we hosted our annual conference, EVOLVE, where global engineering leaders came to talk through the realities of building AI-native SDLCs. When asked to name the biggest friction point in their software lifecycle, attendees gave telling answers: ‘reviewing changes’ took 36 percent, ‘measuring impact’ took 35, and ‘building’ drew zero votes.

The new Civo dashboard is in beta: Try it today

First previewed on stage at Civo Navigate London, the new Civo dashboard is now in beta, and getting to it just got a lot easier. Starting today, you'll see a Try it now banner at the top of your current dashboard at dashboard.civo.com. Click it to head to the new dashboard, sign in with your usual Civo account details, and you're in. You can also go directly to dashboard-manager.civo.com. Look for the Try it now banner in your current dashboard.

How Hybrid WAN Is Transforming Enterprise Network Connectivity

Enterprise networks are evolving as businesses adopt cloud applications, remote work, distributed offices, and connected devices. A hybrid WAN solution can help organizations combine different connectivity options while supporting the performance, reliability, and flexibility required by modern business operations.