Operations | Monitoring | ITSM | DevOps | Cloud

statusgator

Help your Intercom AI agent answer outage questions with StatusGator

Oct 31, 2026 By Valeria Kurolapova In StatusGator
“Why aren’t my campaigns syncing to Salesforce?” “Your dashboard won’t load. Is something down?” When customers report a problem, your support team needs to understand whether it’s related to your product or a provider you depend on. Your AI support agent needs that context, too. By connecting StatusGator to Intercom through MCP, you can give Fin access to live status data and help it provide more useful answers during support conversations.
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meshiq

Banks Found AI Agents Inside Customer Accounts. Nobody Approved What They Did.

Oct 30, 2026 By Gourab Basu In meshIQ
Major US banks have found AI agents operating inside customer accounts, signed in with credentials customers handed over themselves. Nothing was breached. The agents authenticated correctly, and some of them still did things nobody asked for. That gap between having access and having authority is the agentic AI security problem every enterprise running agents now owns.
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AI SRE Agent Slack Integration: Ask AURA About Your Kubernetes Cluster | HQ

Oct 30, 2026 By Mezmo In Mezmo
Running an agent in your cluster should not mean opening it to the internet. AURA reaches Slack over an outbound socket, so the cluster stays locked down. Jeff Vogt connects an AURA deployment running in Kubernetes to Slack using AURA's direct Slack integration. The setup is a Slack app with an app token and a bot token, plus a few lines added to the deployment's configuration. The Kubernetes MCP server is already deployed and connected to AURA before the video starts.
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Get Started with SolarWinds Avior Agentic AI

Oct 30, 2026 By solarwindsinc In SolarWinds
Automate IT operations and resolve alert noise faster with Avior by SolarWinds. Managing mission-critical hybrid IT infrastructure requires rapid troubleshooting without sacrificing operational safety. In this video, we introduce SolarWinds Avior—a goal-oriented agentic AI designed to assist IT teams with autonomous root-cause analysis, alert optimization, and infrastructure triage under strict human oversight.
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logitio

AI-assisted log investigation on Logit.io today: Hosted OpenSearch MCP and onboarding AI prompts

Oct 30, 2026 By Logit.io Team In Logit.io
On 8 October 2026 Elastic announced the private preview of Elastic nightshift AI SRE, an AI agent built into Elastic Observability that detects and investigates issues and shows its reasoning. It is a sign of where observability tooling is heading: more of the first hour of an incident handled by an assistant that reads your telemetry. Short answer: Logit.io does not offer an autonomous AI SRE agent.
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qovery

Infrastructure for AI Agents: Migrate in Hours, Not Months (Live Replay)

Oct 30, 2026 By Romaric Philogene In Qovery
Replay and key takes from our October 20 live with TPC: why Day Two is 80% of infrastructure work, why shared staging breaks when agents write the code, how agents cut migrations from months to hours, and how to keep agents under control with policy tokens and audit logs. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.
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coralogix

Threat Advisory - Trojanized Claude Code Extension: SSH Backdoor

Oct 30, 2026 By Threat Detection & Response Team In Coralogix
A tampered build of the Claude Code editor extension (anthropic.claude-code 2.1.313) was published on the Open VSX store used by Vs code,Cursor and similar editors, quietly gives attackers persistent remote access to any computer that runs it, while the extension keeps working normally. Researchers don’t yet know how it was published (the listing belongs to an Anthropic employee) or who is behind it. They found no evidence that Anthropic’s official Marketplace release was affected.
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circleci

How to run coding agents in parallel without piling up PRs

Oct 30, 2026 By Jacob Schmitt In CircleCI
Running several coding agents at once is pretty straightforward. Give each a task, let them work independently, and you can make progress on multiple things at the same time. But the more agents you have working, the more changes you need to coordinate. Agents can edit overlapping code, make conflicting assumptions, or finish work that depends on changes another agent hasn’t completed.
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datadog

How we use Insights to improve the agent behind Insights

Oct 30, 2026 By Datadog In Datadog
Improving an AI agent means knowing which behaviors to change and where those changes will have the greatest impact. Insights in Datadog Agent Observability improves AI agents by analyzing agent traces to identify recurring cost and reliability problems. It then explains the causes of those problems, assesses their impact, and recommends fixes backed by evidence. At Datadog, we use Insights to improve the agent behind Insights.
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manageengine

AI observability: Why traditional monitoring isn't enough for AI systems

Oct 29, 2026 By Desaad Andrews In ManageEngine
Traditional monitoring watches four things: whether the system is up (availability), how fast it responds (latency), how often it errors (error rate), and how hard the underlying resources are working (resource utilization). This system works because software is deterministic: the same input produces the same output, so a deviation means something broke, and it announces itself as a timeout.
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datadog

Detect when your AI agent copies a self-replicating prompt injection

Oct 29, 2026 By Datadog In Datadog
In September 2026, OpenAI reported finding self-replicating prompt injections. These attacks hide instructions in content an AI agent retrieves, directing it to take unauthorized actions and copy those instructions into emails, files, or messages. Copied instructions can then expose other agents or later sessions to the same attack, giving it the potential to spread like a computer worm.
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datadog

Default to serverless for AI agents, then let production data decide what moves

Oct 29, 2026 By Datadog In Datadog
Serverless should be the first execution model teams evaluate for AI agent workloads. Many agents spend much of their lifetime waiting, and always-on compute forces teams to pay for every idle minute. In a study of more than 35,000 production coding-agent sessions, the median session ran LLM or tool calls for only 20% of its lifetime. The rest of the time, it sat idle between steps, with its sandbox still allocated.
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cloudzero

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

Oct 29, 2026 By David Aponovich In CloudZero
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.
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cloudzero

Amazon told its engineers to stop chasing tokens

Oct 29, 2026 By CloudZero In CloudZero
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.
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What Anthropic's 6:1 AI Work Ratio Means for Every Business

Oct 29, 2026 By Harness In Harness
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.
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Prove Your AI Gains, Then Improve Them | GitKraken Workshop

Oct 29, 2026 By GitKraken In GitKraken
Everyone feels faster with AI, but almost nobody can prove it. In this hands-on GitKraken workshop, Jeremy Castile, Scott Ferguson, and Justin Roberts show you how to get a real read on your AI agents: what they actually cost, what they produce, and whether they’re making your team faster, then how to take that data and improve it. You’ll see how to read an agentic workflow across adoption, autonomy, activity, cost, and outcomes in real time, how to spot where you’re overspending, and how to run and right-size multiple agents so you scale your agent work without scaling the bill.
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gitkraken

6 Agentic Development Environments Compared (2026)

Oct 28, 2026 By Jade Nangah In GitKraken
Your AI coding agents write functions, refactor modules, and generate tests in seconds. Running five of them across three repositories at the same time? That’s a coordination problem, not a code generation problem. Agentic development environments give you one surface to orchestrate multiple agents, review every diff, and get code merged without losing context.
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CloudZero in 3 Minutes: See What Your AI and Cloud Spend Actually Buys

Oct 28, 2026 By CloudZero In CloudZero
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.
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grafana

Evaluate AI models for observability: o11y-bench joins Fireworks' Specialized Intelligence Index and reaches v1.1

Oct 28, 2026 By Sean Porter In Grafana
When evaluating AI models for observability, generating a plausible query or explanation isn't enough. Teams need to know whether an agent's conclusions are supported by telemetry, whether its changes to dashboards actually work, and whether it can deliver reliable results consistently. This is why we built o11y-bench, Grafana Labs' open benchmark for evaluating AI models on observability and SRE tasks. And today, we're excited to share two updates.
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Can AI Do Your Software Testing? #softwaretesting #aitools #codingtips #devlife #tech #aiagents

Oct 28, 2026 By Speedscale In Speedscale
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.
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How AI Is Changing Cybersecurity and Exposing Decades of Bad Code

Oct 28, 2026 By Harness In Harness
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.
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elmahio

Why AI-Generated code still needs tests

Oct 28, 2026 By Ali Hamza Ansari In elmah.io
AI has made life easier for us developers. Dozens of AI tools are getting more advanced every day, shortening and speeding up the development cycle. Converting an idea into a concrete MVP is faster than ever before. Intelligent models turn your ideas into a working project with just a few prompts. End users or product owners can see the application, use the beta version, and give feedback on the spot.
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Measuring What Matters in AI Applications

Oct 28, 2026 By Datadog In Datadog
AI has become incredibly sophisticated and changed the way we build and power applications. But it has also introduced volatile complexity that challenges how we ensure reliability and protect user experiences. Join our panel of experts as they discuss the realities of building AI-powered applications. They’ll talk about how testing has evolved, share insights into how they do evals and experiments, and offer advice on how to get better visibility into how your AI is performing.
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coralogix

39% of Coralogix sessions are now headless

Oct 28, 2026 By Chris Cooney In Coralogix
We set out to understand how customers were using Coralogix from outside the web app. Olly answers questions about a system in plain language. Coding agents query logs, examine traces, read metrics and configure the platform through the Coralogix CLI and MCP server. We wanted to see how much of this was becoming part of everyday work. In the week of 20–26 October, 39% of Coralogix sessions included Olly, the CLI or MCP.
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AI Signals Demo: See Exactly What Your AI Spend Is Buying | CloudZero

Oct 28, 2026 By CloudZero In 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.
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sentry

Five things you can do with Sentry's Agent Tracing

Oct 28, 2026 By Anton Bjorkman In Sentry
AI-powered apps are hard to debug without observability. From one run to another, AI produces different results, goes down different paths, and you’re none the wiser as to why it’s happening. Agent Tracing bridges the gap between prompt, tool calls and final output, all within the context of your app. If things break (it always does at some point, we know from experience), you get everything in one complete trace.
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cloudzero

AI cost per customer: measure it and protect your margins

Oct 28, 2026 By Lyne Carolyne In CloudZero
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.
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harness

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

Oct 28, 2026 By Kevin Moy In 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.
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Keynote: Cloud Networking for AI Architectures | Roy Chua | Megaport Connect 2026

Oct 28, 2026 By Megaport In Megaport
AI is changing how networks are designed and operated. This session explores how GPU infrastructure, AI workloads, and automation are reshaping enterprise and cloud networking, and what these shifts mean for network architecture and the future role of network engineers. Recorded at Megaport Connect 2026. Chicago | Thursday 22 October ABOUT THE SPEAKER | Roy Chua, Founder and Principal, AvidThink.
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Managing AI Video Assets from Experiment to Approved Release

Managing AI Video Assets from Experiment to Approved Release

Oct 28, 2026 By OpsMatters In OpsMatters
The difficult moment in an AI video project often arrives after generation. Someone drops a promising clip into a team chat, another person requests a change, and a third person downloads a different version for publication. By the next morning, nobody is certain which file was approved. For teams already managing software releases, this is a familiar coordination problem with an unfamiliar kind of artifact.
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manageengine

Working from home in the AI era: Advantages, disadvantages, and the way forward

Oct 27, 2026 By Priyanka Gs In ManageEngine
Remote work has changed more than where we work. It has reshaped how teams collaborate, how organizations manage performance, and how employees balance professional and personal responsibilities. Now, AI is adding another dimension to this transformation. From AI assistants that summarize meetings to automation tools that handle repetitive tasks, technology is making remote work more efficient in several ways.
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onpage

10 Best AI ITSM Tools in 2026 (Compared)

Oct 27, 2026 By Michelle Chua In OnPage
Artificial intelligence (AI) is changing how IT teams manage service requests, troubleshoot technical issues, and respond to incidents. As IT environments become increasingly complex, traditional service management processes can struggle to keep up with growing ticket volumes, recurring incidents, and rising expectations for faster resolutions.
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resolve

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

Oct 27, 2026 By Zack Austin In Resolve
“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.
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sentry

How a beagle-shaped AI agent ships code to madewithvuejs.com

Oct 27, 2026 By Armin Ulrich In Sentry
This is a guest post from Armin Ulrich, a fullstack developer, and founder of placid.app. He also created the MadeWith* network where he shares his projects and allows other developers to share theirs. Two people and one beagle run the project showcase madewithvuejs.com. The beagle is actually an AI agent that we have added to our workflows, but we’re very fond of her by now. Milly is part of the team, scouting for content, building features and sniffing for bugs.
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cloudzero

AI cost per query: how to calculate and optimize it

Oct 27, 2026 By Lyne Carolyne In CloudZero
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.
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cloudzero

Shipped: AI dimensions, organized around how your team works

Oct 27, 2026 By Ronald Auclair In CloudZero
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.
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iOPEX

Your AI Agent Can Act Across Enterprise Systems. Now You Need Delegation of Authority

Oct 27, 2026 By iOPEX Technologies , In iOPEX
In 2025, attackers reached the Salesforce data of hundreds of companies without breaking into Salesforce. They used access tokens belonging to an AI chat agent. Google's threat intelligence team counted more than 700 potentially affected organizations, and because the tokens belonged to a trusted app, they carried the attackers past safeguards such as MFA. Enterprises already know how to manage this kind of risk for people.
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Building a local AI agent in Workshop on Ubuntu

Oct 27, 2026 By Canonical Ubuntu In Canonical
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.
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grafana

Agent Observability FAQ: Understand the value of monitoring, evaluating, and improving your AI agents

Oct 27, 2026 By Aishlee Kailey In Grafana
Agents have quickly become part of the tech landscape as organizations embrace AI across their businesses. But embracing agents also means embracing the monitoring best practices that have long been part of engineers' workflows: tracking performance, catching errors, and responding to incidents But it doesn't stop there. Agents also introduce new challenges.
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Komodor

What Is Agentic Operations and Why Ops Teams Are Adopting It

Oct 27, 2026 By Komodor In Komodor
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.
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Why AI Coding Agents Are Breaking Your Software

Oct 27, 2026 By Speedscale In Speedscale
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.
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bigpanda

Scaling Agentic ITOps: From AI pilots to autonomous IT operations

Oct 27, 2026 By Rob Pickering In BigPanda
For enterprise IT leaders, the question is no longer whether AI agents can help run IT operations, but how to scale them beyond pilots and into the everyday work of keeping the business online. It’s no coincidence that this year’s Gartner IT Infrastructure, Operations & Cloud Strategies Conference (IOCS) opens with a keynote dedicated to scaling agentic AI to enable autonomous IT operations. At BigPanda, we’ve seen a shift from the ITOps leaders we work with every day.
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Product Keynote: The Platform for Your Agentic Enterprise

Oct 26, 2026 By Splunk In Splunk
The future of operations is predictive, unified, and AI-powered. Dive into how Splunk and Cisco help organizations unlock cross-domain insights at massive scale, provide intelligent context across security and observability, and build trust in AI with end-to-end visibility. Hear directly from product leaders on the latest innovations shaping agentic enterprises.
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Welcome Keynote: Powering the Rise of the Agentic EnterpriseRise of the Agentic Enterprise

Oct 26, 2026 By Splunk In Splunk
Join Jeetu Patel, Head of Product at Cisco, and Kamal Hathi, GM at Splunk, alongside a special guest, to see how organizations transform security, observability, and operations with AI workflows that are proven at scale. Discover how Splunk and Cisco bring unified visibility, trusted AI, and intelligent automation to help organizations.
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iOPEX

When AI Shapes What Customers Buy, Brands Need Better Control.

Oct 26, 2026 By iOPEX Technologies , In iOPEX
Your next customer will likely meet your product inside an AI answer. More than 1 in 4 consumers already use generative AI to shop, according to McKinsey's State of the Consumer 2026. The traffic it sends is valuable. Adobe found AI referrals to US retail sites converted 54% better than other sources in May 2026. The answer that the shopper sees is assembled from your feeds, retailer listings, reviews, and third-party content.
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civo

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

Oct 26, 2026 By Luke Jimenez In Civo
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.
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datadog

Monitor Oracle AI Database across clouds with Datadog

Oct 26, 2026 By Datadog In Datadog
Organizations can use Oracle AI Database@AWS, Oracle AI Database@Azure, and Oracle AI Database@Google Cloud to run Oracle databases co-located with the cloud applications they support rather than managing the databases on premises. However, running applications in a cloud provider’s environment while hosting databases on Oracle Cloud Infrastructure (OCI) can lead to visibility gaps. When application performance degrades, identifying the source of the problem can be difficult.
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Microsoft Offers 60,000 Employees Buyouts. Here's the AI Problem.

Oct 26, 2026 By Harness In Harness
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?
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What Does AI Need to Know Before You Trust It? | AI SREDo you like this personality?

Oct 26, 2026 By BigPanda In BigPanda
AI can make decisions. But can it make the right ones across your entire IT environment? For enterprise SRE teams, trustworthy AI requires three things: operational context, institutional memory, and guardrails. Without them, autonomous action becomes a risk instead of an advantage. In our latest webinar, we explore what it takes to bring AI SRE capabilities to enterprise scale.
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cloudzero

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

Oct 26, 2026 By Lyne Carolyne In CloudZero
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.
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Agentic SOC Tools 2026 Buyer's Guide

Agentic SOC Tools 2026 Buyer's Guide

Oct 26, 2026 By OpsMatters In OpsMatters
As we write this in Q4 2026, the agentic SOC solution market consists of a very complex array of products. Solutions being sold as "agentic SOC" include standalone AI SOC analysts, agentic SOAR platforms, AI agents embedded in SIEM/XDR products, and managed SOC services using autonomous agents. This makes the buying landscape complex, to say the least. This guide covers the key factors to consider when evaluating agentic SOC tools and provides a concise overview of the leading solutions to help you narrow down your shortlist.
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Was Saudi Arabia Secretly Listening to OpenAI's Biggest Secrets?

Oct 25, 2026 By Harness In Harness
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.
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Microsoft Has a Bigger Problem Than Anyone Realizes

Oct 24, 2026 By Harness In Harness
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.
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AI Can Write Infinite Code. But Can We Ship It Safely?

Oct 23, 2026 By Harness In Harness
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.
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ilert

A walkthrough of a root cause analysis with ilert AI SRE

Oct 23, 2026 By Tim Gühnemann In iLert
It's 3am and a complaint has made its way to you: customers can't see product reviews. Nothing has crashed, and no alert points anywhere useful. Somewhere in your stack one service is failing, and the one showing the error is probably not it. Before you can fix anything you have to find it, and that search is most of your night. Now imagine you open the laptop, type one sentence and go grab a coffee. By the time you’re back, the root cause is ready, evidence attached. Your job is to check it.
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Create Custom Visualizations | Introducing Grafana Pages | New from Grafana AI

Oct 23, 2026 By Grafana In Grafana
Grafana Pages is now in public preview in Grafana Cloud. Tell Assistant what you want it to see , and Pages builds it: a custom visualization, an app, a slide deck, or even a game. Pages are for the moments a dashboard can’t cover, like walking leadership through a launch, starting your day with a view of the services you own, or turning an incident into a story everyone can follow.
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Operationalizing Microsoft 365 Copilot: Compliance, security, and scale

Oct 23, 2026 By Cribl In Cribl
Unmonitored AI is a massive organizational blind spot. Join Cribl's Field CISO, Ed Bailey, and Senior Product Manager, Daniel Pan to learn Cribl can help you affordably collect and store Microsoft 365 Copilot prompts and responses and share that data across your IT and Security teams to meet compliance requirements and gain real AI observability. We'll cover how to scale collection with less effort and build the AI-ready data architecture that solves today's challenges and sets you up for what's next.
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scout

What's New in Scout: October 2026

Oct 23, 2026 By Aspen Clevenger In Scout
October was about making Scout’s data easier for AI tools to use and easier for your team to trust. Scout is now in Claude’s connector directory, the MCP server got leaner and more careful about what it returns, and Scout Trails opened its beta. Anomaly Detection also became easier to read and better at catching short spikes. Here’s what shipped in October.
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Test AI-Generated Code with Real Traffic#aiagents #devops #observability #shiftleft #softwaretesting

Oct 23, 2026 By Speedscale In Speedscale
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!
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cloudzero

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

Oct 23, 2026 By Keith MacKenzie In CloudZero
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.
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cloudzero

Shipped: Slice AI spend eight ways in AI Explorer

Oct 23, 2026 By Kaitlin Woo In CloudZero
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.
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AI Visibility Checkers for Engineering-Led Teams: 7 Best in 2026

AI Visibility Checkers for Engineering-Led Teams: 7 Best in 2026

Oct 23, 2026 By OpsMatters In OpsMatters
Somewhere in your edge configuration there is a rule nobody remembers writing, and it is deciding whether ChatGPT can read your documentation. That is the thesis of this list: AI visibility, meaning whether assistants such as ChatGPT, Gemini and Perplexity name your product when a buyer asks for one, has become partly an infrastructure problem, and the two failure modes that matter most sit on the engineering side of the house. The first is reachability, because a WAF default that returns 403 to GPTBot or ClaudeBot removes you from retrieval as surely as a robots.txt disallow.
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datadog

Optimize AI costs with Agent Observability

Oct 22, 2026 By Datadog In Datadog
AI agent costs accumulate along more dimensions than a model-call count. Spend is a product of both which models you call and how the agent is architected: how many turns the loop runs, how many tools it invokes, how much retrieved context it carries, and how much of that context is re-sent on every turn. Provider bills tell you how much you spent, but they’re keyed to API keys and models instead of the applications and workflow steps that generated the calls.
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cloudzero

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

Oct 22, 2026 By David Aponovich In CloudZero
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.
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upsun

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

Oct 22, 2026 By Upsun In Upsun
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.
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Security Just Hit Machine Speed

Oct 22, 2026 By Harness In Harness
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.
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qovery

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

Oct 22, 2026 By Romaric Philogene In Qovery
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.
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cortex

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

Oct 22, 2026 By Mike Vanbuskirk In Cortex
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.
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From iPhones to AI Servers: Foxconn's Second Act

From iPhones to AI Servers: Foxconn's Second Act

Oct 22, 2026 By OpsMatters In OpsMatters
The AI boom continues to redistribute revenue within the technology industry. If previously the main investment interest was focused on chip manufacturers and model developers, now companies that serve the infrastructure supporting this growth are becoming increasingly prominent. One of the main beneficiaries has been Foxconn, which is gradually transforming from the largest assembler of Apple devices into one of the key suppliers of server hardware for artificial intelligence.
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cloudzero

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

Oct 21, 2026 By Kaitlin Woo In CloudZero
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.
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harness

Bring Your Own Identity Provider to Harness MCP

Oct 21, 2026 By Piyush Patel In Harness
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.
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Cycle

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

Oct 21, 2026 By Cycle In Cycle
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.".
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iOPEX

Agentic AI Projects Die in the P&L Review. Here's How Revenue Leaders Can Keep Them Alive

Oct 21, 2026 By iOPEX Technologies , In iOPEX
‍‍Gartner expects more than 40% of agentic AI projects to be canceled by the end of 2027. Its reasons read like a budget memo: escalating costs, unclear business value, and inadequate risk controls. For revenue leaders, the stakes run in both directions. MGI Research estimates that at least 3% to 5% of revenue leaks between contract and cash, through missed renewals, unbilled usage, and pricing errors. Agents are well suited to close those gaps.
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logz.io

Introducing AI Observability: Trace Every AI Agent Request from Prompt to Pod

Oct 21, 2026 By Amos Etzion In logz.io
TL;DR Logz.io AI Observability provides end-to-end tracing for AI agents and LLM applications. Built on OpenTelemetry, it lets you trace every request from prompt to backend service, visualize multi-step agent execution, isolate root causes across models and infrastructure, and track token usage per step, all alongside your existing logs, metrics, and traces.
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scout

Scout Monitoring Is Now in Claude's Connector Directory

Oct 21, 2026 By Aspen Clevenger In Scout
A customer messages support: checkout feels slow today. You open Scout, find the endpoint, open a trace, spot the query, copy it into Claude, and ask what’s wrong with it. Each step is quick, but together they add up to a lot of tab switching to answer one question. Scout Monitoring is now available in Claude’s connector directory. Connect it once and Claude can look at your production data directly.
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What's new and coming in Redgate Monitor: AI, CIS compliance and cloud migration

Oct 21, 2026 By Redgate Software In Redgate
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.
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control plane

How to Let AI Agents Operate Production Infrastructure Safely

Oct 21, 2026 By Noah Grinstein In Control Plane
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.
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bigpanda

Why 76% of AI agent pilots stall, and how your Agentic ITOps pilot can avoid the same fate

Oct 21, 2026 By Sam Osborn In BigPanda
The debate is no longer whether AI belongs in ITOps; it’s about how quickly it can be implemented, how to measure it, and who’s accountable when it acts. And although IT leaders across industries are scrambling to integrate agentic AI into their operations, those deployments are facing serious challenges. A new Harris Poll survey of more than 300 U.S. data and AI decision-makers puts a number on the problem.
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Why Was an OpenAI Engineer Hiding a Recording Device?

Oct 21, 2026 By Harness In Harness
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?
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qovery

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

Oct 21, 2026 By Romaric Philogene In Qovery
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.
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How to Actually Test AI Agents Before Production

Oct 21, 2026 By Resolve In Resolve
Fran Fernandez and Pramin Pradeep, co-founder and CEO of BotGauge AI, delve into how AI is changing software development, quality assurance, and enterprise IT. Pramin explains why faster AI-assisted coding has created new pressure on testing, why companies need visibility into every agent operating in their environment, and how red teaming, tracing, production observability, and human oversight can help organizations deploy agents safely.
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appsignal

AppSignal MCP Is Now a Claude Connector

Oct 21, 2026 By Serena Chou In AppSignal
AppSignal MCP went generally available last month. Until now, adding it to the Claude app meant pasting our endpoint URL into a custom connector form. Now you search for it like any other connector. Open Settings, go to Connectors, select the Discover tab, and search for AppSignal. That's the whole setup. For more detail on each step, follow the Claude app section of the setup guide. It works the same way in Claude on the web and in the desktop app..
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harness

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

Oct 20, 2026 By Uma Mukkara In Harness
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.
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harness

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

Oct 20, 2026 By Ravi Yadalam In Harness
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.
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resolve

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

Oct 20, 2026 By Derek Pascarella In Resolve
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.
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grafana

From production problem to proposed fix: Implement autonomous operations with Grafana AI

Oct 20, 2026 By Maurice Rochau In Grafana
You've just finished a deployment, and though your service is up, you start to notice some requests are getting slower. To address the lag, someone—or, more likely, some group of people on your team—needs to watch the dashboards, decide whether the change matters, investigate what happened, and turn the findings into a fix. At each step you're gathering context—and often explaining that context again to the next person or tool.
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honeycomb

Our Limits Are Not Our Imagination

Oct 20, 2026 By Jessica Kerr (Jessitron) In Honeycomb
Yesterday, my partner told me about his new automated pipeline from a conversation recording to publication of a whole podcast, with social media blurbs and graphics and everything. It did more than he'd predicted the agent could do. "We are limited by what we can imagine," he said. Cheesy, but it kinda gave me goosebumps because it's (almost) true. Most of the experienced developers I know are concerned.
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bleemeo

Ask Claude or Le Chat what is happening on your servers: the Bleemeo MCP server

Oct 20, 2026 By Ethan VF In Bleemeo
The first minutes of an incident are spent asking questions a monitoring tool can answer but rarely in the form you asked them: which servers are in trouble right now, is it the same thing as last night, what did memory do on the web servers before it started? Each answer is a few clicks away, on a different page.
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Harness AI Agents

Oct 20, 2026 By Harness In Harness
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.
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atlassian

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

Oct 20, 2026 By Arthy Vijayaraghavan In Atlassian
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.
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cloudzero

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

Oct 20, 2026 By Lyne Carolyne In CloudZero
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.
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Nobody Wants Your New AI Agent #devops #aiagents #softwaredevelopment #techtrends #ai

Oct 20, 2026 By Speedscale In Speedscale
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.
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cloudzero

Enterprise AI ROI: proving returns at scale

Oct 20, 2026 By Keith MacKenzie In CloudZero
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.
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gitkraken

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

Oct 20, 2026 By Jade Nangah In GitKraken
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.
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Automate Slack Support with Datadog Workflow Automation + Bits AI

Oct 20, 2026 By Datadog In Datadog
Automate Slack support questions with Datadog Workflow Automation and Bits AI Agent Builder. Datadog Workflow Automation can now trigger directly from messages posted in Slack. In this quick demo, Yuta Yoshida, Product Manager at Datadog, shows how to build an automated support workflow that: → Detects new support questions in a Slack channel→ Sends questions to a custom agent built with Bits AI Agent Builder→ Replies directly in the Slack thread with an answer and relevant documentation.
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harness

Introducing AI Budgets: A Policy You Can Watch Work

Oct 20, 2026 By Ravi Yadalam In Harness
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.
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upsun

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

Oct 19, 2026 By Upsun In Upsun
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.
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grafana

6 improvements that make Grafana Assistant better at helping your workflows

Oct 19, 2026 By Maurice Rochau In Grafana
When you ask Grafana Assistant to build a dashboard or investigate an alert, you're doing so because there's work to be done. To do that work effectively, you need the right data, changes you can inspect, and conclusions supported by evidence. You also want Assistant to avoid mistakes and act quickly. Over the past six months, our team has worked hard to improve what makes those outcomes possible.
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tigera

YouTube Let AI Prototypes Read Production. The Token Did the Work.

Oct 19, 2026 By Alister Baroi In Tigera
TL;DR: Google Cloud’s post of 22nd July 2026 on why AI apps fail in production describes how a YouTube team gets AI prototypes in front of user research in weeks instead of quarters: a prototyping stack that hands each prototype read-only access to live production data through a proxy, keeps its code out of the production binary, and throws the prototype away once the idea is proven.
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VictoriaMetrics

Observability Lessons NVIDIA and CoreWeave

Oct 19, 2026 By PF Pablo Fernandez In VictoriaMetrics
The best thing that can happen to an open-source project is to find its way into some of the world’s largest technology companies. In September 2026, this happened twice in one week: VictoriaMetrics is now officially bundled in the self-managed edition of NVIDIA’s Cloud Functions, and I learned that CoreWeave is using VictoriaMetrics as the metrics backend for all of its infrastructure customers. Both companies adopted VictoriaMetrics independently.
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control plane

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

Oct 19, 2026 By Noah Grinstein In Control Plane
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.
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Enterprise Vibe Mode: Deploy AI-Built Apps to Production | Harness Demo

Oct 19, 2026 By Harness In Harness
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.
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Harness Cost Management Agent | How to Set and Enforce AI Spending Budgets

Oct 19, 2026 By Harness In Harness
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.
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Modal scales the next generation of AI with unified observability from Datadog

Oct 19, 2026 By Datadog In Datadog
Modal is an AI infrastructure company rebuilding the cloud for AI, giving developers easy access to the compute needed to build and scale AI applications without managing the underlying complexity. Operating across more than 20 cloud providers and launching approximately 26 million containers daily, Modal relies on Datadog to unify observability across its infrastructure, applications, networking, and CI—helping its engineers detect 99% of incidents within five minutes, resolve 96% of issues before customer impact, and confidently scale one of the world’s most complex AI platforms.
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Aiven

AI inference, explained through one question

Oct 19, 2026 By Philippe Vincent-Royol | In Aiven
TL;DR Part 0 of a three-part series on building a documentation assistant with Aiven. This part gives you the vocabulary. Part 1 is the architecture. Part 2 builds the thing. Almost everything written about large language models explains how models get built. Very little explains what happens the other billion times, when a finished model sits there answering questions. That second thing is called inference, and it is where practically all of the engineering work actually lives.
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last9

MCP Server Monitoring: Tracing Tool Calls with OpenTelemetry

Oct 19, 2026 By Sejal Pandey In Last9
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.
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gitkraken

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

Oct 19, 2026 By Jade Nangah In GitKraken
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.
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Featured Post
AI Is Making Infrastructure Easier to Create and Harder to Operate

AI Is Making Infrastructure Easier to Create and Harder to Operate

Oct 19, 2026 By Daniel Bryant, Platform Engineer & Head of Product Marketing In OpsMatters
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.
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AI Agents Hacked 395 Organizations. How Do You Stop Them?

Oct 17, 2026 By Harness In Harness
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.
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The Growing Divide Between Digital Simplicity and Real-World Complexity

The Growing Divide Between Digital Simplicity and Real-World Complexity

Oct 17, 2026 By OpsMatters In OpsMatters
A banking app can approve a transaction in seconds. An AI assistant can produce a detailed report from a single instruction. Yet correcting a banking error or verifying an AI-generated report can take hours. This contradiction is becoming more visible as digital services grow easier to operate. Interfaces require fewer steps, but the processes behind them involve increasingly complicated systems, decisions, and responsibilities. The question is whether technology is eliminating complexity or simply moving it somewhere users cannot see.
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cloudzero

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

Oct 16, 2026 By David Aponovich In CloudZero
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%.
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cloudzero

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

Oct 16, 2026 By Lyne Carolyne In CloudZero
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.
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CriblCon 26 Keynote highlights: Cribl StreamAI, App Framework, Marketplace, and Detect

Oct 16, 2026 By Cribl In Cribl
This CriblCon 26 keynote highlight reel introduces Cribl’s AI platform for telemetry and highlights Cribl StreamAI, the Cribl App Framework, Cribl Marketplace, and Cribl Detect. It is relevant to IT, security, and observability teams exploring intelligent model routing, agentic app development, marketplace deployment, and security investigations using telemetry and context. The keynote also covers the SEC IT benchmark, the cost of investigating incidents with different AI models, and included inference for Cribl-native workloads.
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puppet

When AI Attacks at Machine Speed, Configuration Management Becomes Cybersecurity

Oct 16, 2026 By Puppet In Puppet
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.
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harness

AI Coding Assistants: Trust Is the Attack Surface

Oct 16, 2026 By Soujanya Namburi In Harness
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.
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atlassian

Connect Bitbucket Cloud to your AI tools with Atlassian MCP

Oct 15, 2026 By Hamreet Kaur In Atlassian
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.
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bigpanda

When five agents are looking at the same IT incident, which one makes the decisions?

Oct 15, 2026 By Rob Pickering In BigPanda
It’s 2:14 am, and checkout latency at your largest retail store has tripled. Your observability platform’s agent has already posted to Slack that there is a connection pool exhaustion on the orders database, with a link to the trace. Your cloud provider’s agent reports a degraded network path in one availability zone. The AI SRE tool one of your product teams adopted last spring points to a deploy that went out at 1:50.
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AI Is Writing More Code. So Why Are Teams Getting Smaller?

Oct 15, 2026 By Harness In Harness
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?
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Use less AI and show your effort in contributing to the OTel project

Oct 15, 2026 By VictoriaMetrics In VictoriaMetrics
Using more AI and adding lots of contributions, but not understanding the project, will not scale long-term. OpenTelemetry, like other OSS and cloud native projects, is looking for contributors who care about the ecosystem and genuinely want to learn and support the project. Resources for Further Learning.
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Aiven

Introducing Aiven AI Gateway

Oct 15, 2026 By Filip Yonov | In Aiven
At home I run fully automated coding loops on a few side projects. They use more than 100-million tokens a day. At Claude Opus 5.5 prices, that costs more than $5,300 a month. For hobby projects. The same usage on DeepSeek V4.1 Flash cost about $330 a month, one sixteenth of the price. If we want to keep scaling how much we use AI, most of those tokens have to run on open models, period.
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civo

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

Oct 15, 2026 By Mark Boost In Civo
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.
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datadog

Introducing Scout 1.0: A new SRE model powering Bits AI with frontier performance at a fraction of the cost

Oct 15, 2026 By Datadog In Datadog
Today, we’re introducing Scout 1.0, Datadog’s first AI model specialized for investigating production issues. Scout powers Bits Investigation, our AI SRE. We trained Scout to reduce inference cost so that investigations are cheap enough to run an order of magnitude more often and earlier in an incident’s lifecycle. Key highlights include: Close dialog.
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datadog

How Kubernetes DRA can improve GPU utilization and cut costs

Oct 15, 2026 By Datadog In Datadog
Organizations are spending more on GPUs as they move AI workloads into production, and improving GPU utilization is a key priority. But Kubernetes’s legacy device plugin model can limit those improvements because it constrains how workloads request and consume GPU resources. Teams must configure GPU partitioning before workloads are scheduled. Resource requests cannot distinguish GPUs by capability, and a workload can reserve an entire GPU while using only part of its capacity.
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meshiq

What Are AI Agents? How They Work, Why They Matter and Why They Need Governance

Oct 15, 2026 By meshIQ In meshIQ
An AI agent doesn’t just answer questions—it takes actions in real systems. As teams across the enterprise build their own agents, governance can’t be an afterthought. Learn how agents work, why they create new risks, and what controls are needed before they act, not after.
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logz.io

Best AI Observability Tools of 2026: Monitoring the AI You Build and the AI That Runs Your Ops

Oct 15, 2026 By Kevin Klein In logz.io
TL;DR “AI observability” now describes two different jobs. One is watching the LLM apps and AI agents your team ships: prompts, tool calls, token spend, and output quality. The other is putting AI agents to work on your production telemetry so incidents are already being investigated by the time an engineer logs in. Most engineering orgs in 2026 need both, and very few tools cover the two well.
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Komodor

Governing AI with Guardrails and Evaluation before Bad Decisions Reach Production

Oct 15, 2026 By Komodor In Komodor
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.
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cloudzero

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

Oct 15, 2026 By Lyne Carolyne In CloudZero
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.
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How to Turn Off GitKraken AI (GitKraken Desktop and Organization-Wide)

Oct 15, 2026 By GitKraken In GitKraken
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.
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InvGate

AI Prompts For IT Asset Management: Ready-to-Use Inventory Questions

Oct 14, 2026 By Ignacio Graglia In InvGate
AI prompts for IT Asset Management (ITAM) are the questions and instructions IT teams type into an AI assistant to get answers from their asset inventory. They're searched by IT asset managers, technicians and IT leaders whose assistant can already read inventory data and who want ready-made questions that return useful answers about devices, owners, warranties and costs.
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Dave Killeen: What to Do When Execs Demand AI

Oct 14, 2026 By Atlassian In Atlassian
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.
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Is Trust the UK's Real AI Bottleneck? | Civo Navigate London

Oct 14, 2026 By Civo In Civo
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.
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AI wrote the code. Can you prove it followed the rules?

Oct 14, 2026 By JFrog In JFrog
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.
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Cycle

The Heroku Experience for the AI Era

Oct 14, 2026 By Cycle In Cycle
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.
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A Hacker Used Claude to Attack 9 Banks. This Is Just the Beginning

Oct 14, 2026 By Harness In Harness
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?
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What Is the Harness Software Delivery Agent?

Oct 14, 2026 By Harness In Harness
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.
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logicmonitor

AI Agents Are Becoming Part of the IT Environment. They Need to Be Managed That Way.

Oct 14, 2026 By LogicMonitor In LogicMonitor
Agent Studio for Edwin AI gives administrators one place to see which agents are available, understand what each one does, control which agents are enabled, and manage their access to MCP tools. See how Agent Studio brings clearer administration and governance to agentic IT operations.
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Incident.io

We gave cloud agents a phone to QA

Oct 14, 2026 By Engineering In Incident.io
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.
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signl4

SIGNL4 Update: AI-Powered Event Routing, Alert Analytics, On-Call Coverage & More

Oct 14, 2026 By SIGNL4 In SIGNL4
This October, SIGNL4 is taking a big leap forward! One of our most comprehensive updates yet introduces AI-powered event routing, powerful new analytics to identify alert hotspots and trends, and instant visibility into on-call coverage gaps. Add smarter team and workflow management, plus enhanced security and compliance features, and there’s plenty to explore!
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Cycle

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

Oct 14, 2026 By Alexander Mattoni In Cycle
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.
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cloudzero

Your AI Economics Pulse for October 2026

Oct 13, 2026 By Keith MacKenzie In CloudZero
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.
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InvGate

AI Agent And Digital Certificate Inventory: How to Track Your Invisible IT

Oct 13, 2026 By Ignacio Graglia In InvGate
An AI agent and digital certificate inventory is a record of every AI agent and digital certificate an organization runs, with what each one does, who owns it, what it connects to and when it expires or needs a review. IT and IT Asset Management (ITAM) teams build one because both kinds of asset keep critical services running with no hardware to scan, no purchase order to trace and, very often, no owner on record.
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When an AI Agent Goes Rogue, Who's Responsible? | Civo Navigate London

Oct 13, 2026 By Civo In Civo
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.
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Autonomous Patch Management | Ivanti

Oct 13, 2026 By Ivanti In Ivanti
New vulnerabilities emerge every day and thousands of endpoints change constantly — it's a continuous race against time. Patching isn't just deployment; it's manual handoffs and incomplete visibility that leave organizations exposed. This video shows how Ivanti Neurons for Patch Management provides immediate, authoritative insights into your IT estate so you can close security gaps faster.
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Building an AI Assistant That Actually Understands Your Incidents

Oct 13, 2026 By Datadog In Datadog
When production breaks, the clues are everywhere but the story is scattered. RUM sessions, APM traces, metrics, and logs allow Datadog to tell you part of the story. What’s missing is your service ownership quirks, your team's conventions, or the three-year-old workaround buried in a comment that explains why a certain endpoint behaves the way it does.
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Democratizing Incident Response with AI at Riot Games - SRE Track

Oct 13, 2026 By Datadog In Datadog
Senior engineers are the pillars of SRE programs—not only do they have the leadership to manage incidents well, they also have the tribal knowledge to understand the technical causes of tricky issues. But when the know-how is confined to a few individuals, it greatly limits the effectiveness of your SRE team.
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Dismantling Datadog's Monolith with Agentic AI - Developer Track

Oct 13, 2026 By Datadog In Datadog
AI can write code, but how does it do with a large, organically built codebase with years of development? Datadog’s monolithic webapp had significant scale and support challenges, so we knew the time had come to break it up. But when the code has been written, revised and tweaked so many times (as we keep adding new features and capabilities), by so many teams, that becomes much harder.
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harness

Agentic code is changing how we think about code quality

Oct 13, 2026 By Rohan Bhaumik In Harness
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.
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sumologic

Introducing DojoAI Credits: Flexible, predictable AI pricing built for scale

Oct 13, 2026 By Margaret Selid In Sumo Logic
AI agents are quickly becoming the first responders on the most sophisticated SecOps and DevOps teams, pulling threads on a threat or making sense of a flood of telemetry before a human even logs in. But most AI pricing hasn’t caught up. Token-based models leave you burning through usage with no visibility into what’s driving the cost, while per-seat caps ration access like AI is still a nice-to-have instead of core to how your team operates.
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sumologic

The Root Cause Agent: Bring an agentic approach to observability

Oct 13, 2026 By Michelle Beastall In Sumo Logic
For years, engineering teams have faced the same challenge during incidents: the systems generating alerts are becoming more complex, but the investigation that follows is still largely manual. Monitors are good at telling us that something is wrong. The harder question is why. When an alert fires, an engineer still has to work out where to look, which signals matter, what hypothesis to test, and how the evidence across logs and metrics fits together.
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AI at scale: are your foundations ready?

Oct 13, 2026 By PulsantUK In Pulsant
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.
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Harness Cost Management Agents Slash Cloud & AI Spending

Oct 13, 2026 By Harness In Harness
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.
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Where Is All Your AI Spend Going? | Harness AI Cost Management Demo

Oct 13, 2026 By Harness In Harness
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.
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The Feature Flag Became the Kill Switch for AI Features

The Feature Flag Became the Kill Switch for AI Features

Oct 13, 2026 By OpsMatters In OpsMatters
Traditional code fails loudly. A null pointer throws, a query times out, a 500 lands in the logs, and the on-call engineer has a stack trace to chase. AI code fails on a different axis. The response is syntactically fine, the latency looks normal, the error rate is flat, and the output is wrong in a way only a human reading it would catch.
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The Rapid Rise of Generative AI and the Imperative for Detection Technologies

The Rapid Rise of Generative AI and the Imperative for Detection Technologies

Oct 13, 2026 By OpsMatters In OpsMatters
The digital landscape is undergoing a profound transformation driven by the explosive growth of artificial intelligence. In recent years, generative AI models have advanced from producing rudimentary text fragments and pixelated imagery to generating remarkably convincing essays, news articles, photorealistic landscapes, and synthetic portraits. While these tools offer unprecedented creative efficiency and technical accessibility, they also introduce significant challenges regarding authenticity, intellectual property, academic integrity, and digital security.
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Top 8 Agentic Operations Platforms for DevOps Teams

Top 8 Agentic Operations Platforms for DevOps Teams

Oct 13, 2026 By OpsMatters In OpsMatters
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.
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Alloy Software

Meet Allie, Your New AI Teammate

Oct 12, 2026 By Anna Markova In Alloy Software
Get a first look at your new AI assistant for IT teams, coming this fall. Coming to Alloy Navigator this fall, Allie is a versatile AI assistant that understands how you work and helps you get things done. It combines the context of your current task with years of knowledge accumulated across your system, broader expertise, and external sources you choose. Allie answers questions, analyzes information, and takes action, following processes tailored to your team.
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meshiq

Agentic AI Is Becoming the Enterprise's Connective Tissue. Governance Has to Move Into the Flow.

Oct 12, 2026 By Buddhiraj Chapalgaonkar In meshIQ
McKinsey's 2026 tech report calls agentic AI the 'connective tissue of the enterprise.' But agents that act at machine speed need governance at machine speed too. Static controls won't work for dynamic agents—active, in-flow guardrails must run before the action, not after.
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solarwinds

Ask Your Logs: The AI Assistant Comes to Papertrail

Oct 12, 2026 By Papertrail Team In SolarWinds
It is 2 a.m., and something is wrong. The answer is somewhere in your logs, but finding it means guessing keywords, remembering search syntax, and scrolling through thousands of lines. Your systems keep growing, so you have more data than ever and less clarity when it counts. Today, we are bringing the AI assistant, the SolarWinds in-product AI agent (also known as SW1 in earlier previews), to Papertrail. Ask your logs a question in plain English and get an answer, with a link back to the evidence.
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gitkraken

Understanding Agentic Development Environments

Oct 12, 2026 By Jade Nangah In GitKraken
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.
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Not All AI Tools Will Survive the Shakeout

Oct 10, 2026 By NinjaOne In NinjaOne
Not every AI tool has staying power, and the ones that last are the ones that fit your organization’s strategy. AI is following the same arc as the cloud push and the dot-com era: a massive boom, then a contraction. Before you invest, ask what will actually make a difference in your org, and build from there. Watch the full IT Leadership Lab session — linked above.
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Elastic Introduces Elastic nightshift AI SRE to Investigate with the Full Context Others Can't Afford to Keep

Elastic Introduces Elastic nightshift AI SRE to Investigate with the Full Context Others Can't Afford to Keep

Oct 9, 2026 By Elastic In Elastic
The AI SRE uses complete context from across the entire stack to continuously detect issues and learn from every incident, delivering evidence-backed answers engineers can trust.
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selector

Meet Rosetta

Oct 9, 2026 By Dallon Robinette In Selector
During an incident, the answers an engineer needs are spread across tools. Telemetry sits in one place, configurations in another, and tickets in a third. Building a complete picture means knowing which tool holds which piece and how to query each one, usually under time pressure. Rosetta is the conversational interface for Selector Foundry, the agentic NetOps platform built on Selector’s existing AIOps and Observability solution.
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datadog

Unify data across Datadog BYOC with cross-cluster queries for teams and AI agents

Oct 9, 2026 By Datadog In Datadog
Organizations may need to keep data in specific regions or infrastructure they control, whether because of data residency requirements, internal policies, or transfer costs. Datadog Bring Your Own Cloud (BYOC) extends the Datadog platform into those environments. Each BYOC deployment runs as a Kubernetes cluster with its own object storage, keeping data close to its source.
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onpage

8 Best AI SRE Tools in 2026 for Incident Investigation and Reliability

Oct 9, 2026 By Ritika Bramhe In OnPage
The best AI SRE tools to evaluate in 2026 include Sherlocks AI, Resolve AI, Traversal, Cleric, Rootly AI SRE, Komodor Klaudia, Datadog Bits Investigation, and Dynatrace Intelligence. Each addresses a different part of reliability work, from investigating alerts across multiple systems to diagnosing Kubernetes failures or validating production changes. Choosing the right tool starts with a practical question: where does your team lose time during an incident?
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onpage

10 Best AI Logging Tools in 2026: Features, Pricing & Comparison

Oct 9, 2026 By Michelle Chua In OnPage
As businesses increasingly integrate artificial intelligence into their applications and workflows, understanding what happens behind the scenes of these AI systems has become essential. AI-powered chatbots, large language models (LLMs), and autonomous AI agents can process thousands of requests, interact with external applications, and execute complex tasks. However, when something goes wrong, identifying the source of the problem isn’t always straightforward. Was the AI response incorrect?
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manageengine

How AI agents help teams deliver better digital experiences

Oct 8, 2026 By Sangavi D In ManageEngine
The moment your page slows down, two clocks start. One is yours: time to alert, time to investigate, time to fix. The other belongs to the user staring at the slow page. Yours is measured in minutes. Theirs runs out in seconds. That gap is what AI agents close. Zia Agents in OpManager Nexus detects an issue, works out the cause, and runs the fix on its own, often before your users feel a thing. This blog looks at how that changes the experience you deliver.
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control plane

10 Best AI Agent Infrastructure Platforms in 2026

Oct 8, 2026 By Noah Grinstein In Control Plane
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.
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When AI agents ignore the code freeze: governance that holds | EVOLVE 2026

Oct 8, 2026 By Cortex | Engineering Operations Platform In Cortex
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.
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AI is making software delivery less stable. DORA's Nathen Harvey on the fix | EVOLVE 2026

Oct 8, 2026 By Cortex | Engineering Operations Platform In Cortex
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.
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cloudzero

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

Oct 8, 2026 By Kaitlin Woo In CloudZero
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.
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cloudzero

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

Oct 8, 2026 By Lyne Carolyne In CloudZero
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.
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AI Finds and Fixes Security Vulnerabilities | Harness Demo

Oct 8, 2026 By Harness In Harness
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.
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cortex

The Five Levels of the Enterprise AI Software Factory

Oct 8, 2026 By Anish Dhar In Cortex
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.
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coralogix

Debug Production at the Speed of AI

Oct 8, 2026 By Shai Reznik In Coralogix
Your coding agent can debug production issues now. Yes… Not just “help you debug.” Actually run the investigation… FOR YOU! In this new era of agentic development, speed matters. And in the old days (you know… last week or so) we used to investigate production bugs ourselves. Manually. Like humans. But for a lot of incidents, we don’t need to do all of that anymore.
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harness

Harness acquires Augment Code to advance the Autonomous SDLC

Oct 8, 2026 By Jyoti Bansal In Harness
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.
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qovery

How we investigate Sentry errors with an AI agent

Oct 8, 2026 By Rémi Bonnet In Qovery
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.
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Komodor

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

Oct 8, 2026 By Nir Adler In Komodor
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.
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mezmo

Where Jev fits in ops

Oct 8, 2026 By Mezmo In Mezmo
If you're using agents and MCPs to get a better understanding of your environment or work through an investigation, you can get a lot of useful information back. You can pull logs, look at recent changes, and check how services are configured, but you're still the one deciding what to do with all of it. That part of the process still lives in your head. To see where Jev might fit, look at decisions your team already makes and work backwards from them.
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The Infrastructure Puzzle: How AI-Enabled Event Management Software Powers Complex Event Programs

The Infrastructure Puzzle: How AI-Enabled Event Management Software Powers Complex Event Programs

Oct 8, 2026 By OpsMatters In OpsMatters
When registration, attendee data, check-in, communications, and reporting stop working in concert, complex programs break. A connected online event management software setup gives teams one operating layer, not yet another stack of tools that complicates work.
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manageengine

Generative AI in Banking: Balancing innovation, risk, and operational readiness

Oct 7, 2026 By annisa.fauziyyah In ManageEngine
Generative AI (GenAI) is moving quickly into banking. According to a 2025 survey by McKinsey, 52% of financial institutions surveyed already consider GenAI a priority, while another 39% are interested but have not yet made it a top priority. As adoption grows, banks need to think carefully about what AI agents can access, which identities it uses, what actions it can take, and whether those activities can be traced when something goes wrong.
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meshiq

Governing AI Agents From the Inside: What We Learned Building AgentIQ

Oct 7, 2026 By Harshita Kulshrestha In meshIQ
When every employee is building AI agents, seeing what they did afterward isn't enough. AgentIQ's in-flow governance runs inside the agent's execution flow—pausing for human approval, enforcing policies by value, masking PII, and stopping runaway agents before costs spiral.
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Seer Agent: Get Answers. Take Action.

Oct 7, 2026 By Sentry In Sentry
This video walks through what it looks like to treat Sentry's Seer agent the way you already treat a chatbot, asking it plain language questions about your own production application. From Slack or inside your Sentry account, Seer Agent can answer questions with real context: the affected spans, the recent release, the likely cause. Seer doesn't stop at answering questions. Ask it to act on what it just told you and it completes that work inside Sentry, serving as an assistant to your projects, team workflows, and your future self.
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Solving AI Latency and Cost Problems with Valkey - Aiven Webinar

Oct 7, 2026 By Aiven In Aiven
LLM providers charge you for caching, and they do it on their terms. You can run it yourself for a fraction of the cost. In this Aiven webinar, Jay Miller (Staff Developer Advocate) shows how to use semantic caching and semantic routing on Valkey to cut prompt costs + latency. You'll see a working demo, "Template Scout", that searches GitHub for deployable repos and picks the cheapest model that can answer each question.
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meshiq

Governing AI Agents From the Inside: What We Learned Building AgentPatrol

Oct 7, 2026 By Harshita Kulshrestha In meshIQ
When every employee is building AI agents, seeing what they did afterward isn't enough. AgentPatrol's in-flow governance runs inside the agent's execution flow—pausing for human approval, enforcing policies by value, masking PII, and stopping runaway agents before costs spiral.
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AI-Powered Incident Communications

Oct 7, 2026 By PagerDuty Inc. In PagerDuty
Publish internal and external status page updates without leaving your Slack incident channel. SRE Agent brings in Scribe Agent to capture the bridge call and channel discussion, drafts the update from that context, and surfaces it in Slack for a responder to review and publish. Stakeholders stay informed. Responders stay on the fix. Now in rolling GA for customers using Slack and Status Pages.#IncidentManagement.
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honeycomb

OpenTelemetry Collector Configuration for LLM Observability

Oct 7, 2026 By Mike Goldsmith In Honeycomb
Your LLM application emits telemetry unlike anything else in your stack. Model calls, tool invocations, retrieval steps, and token usage arrive as spans whose attributes carry entire prompts and completions. That data is bulky, it's full of user content you may not be allowed to export, and depending on which instrumentation each service uses, the same fact can arrive under different attribute names.
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pagerduty

The Rundeck MCP Server: AI where your Automation lives

Oct 7, 2026 By Madeline Zemer In PagerDuty
This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how PagerDuty’s Runbook Automation / Rundeck MCP Server recently announced in GA builds towards this vision.
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pagerduty

Stop rewriting the same update with AI-Powered Incident Communications

Oct 7, 2026 By Cristina Dias In PagerDuty
This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how PagerDuty’s AI-Powered Incident Communications builds towards this vision.
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gremlin

Announcing Gremlin Foresight AI

Oct 7, 2026 By Kolton Andrus In Gremlin
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.
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gremlin

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

Oct 7, 2026 By Jason English In Gremlin
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.
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AI Investigation for ITOps: Faster Root Cause with Edwin AI

Oct 7, 2026 By LogicMonitor, Inc. In LogicMonitor
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.
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The 5 levels of the AI software factory for enterprises | EVOLVE 2026 keynote

Oct 7, 2026 By Cortex | Engineering Operations Platform In Cortex
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.
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devart

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

Oct 6, 2026 By Rosemary Asufi In Devart
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.
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InvGate

Shadow AI: How to Find And Control The AI Tools Your Company Didn't Approve

Oct 6, 2026 By Ignacio Graglia In InvGate
Shadow AI on company computers often starts with an AI agent that an employee installed on their own, signed in with a personal subscription and connected to internal systems through a Model Context Protocol (MCP) server. Shadow AI is one branch of shadow IT, with a shorter path from install to impact: these tools set up quickly, act on files and systems, and work under whatever account the employee chose. This guide skips the long definitions and goes to the practical part.
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Where the Future Runs: Reinventing Infrastructure for the AI Era | Civo Navigate London

Oct 6, 2026 By Civo In Civo
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.
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ilert

New features: ilert AI SRE GA, ilert CLI, Compass and more

Oct 6, 2026 By Sirine Karray In iLert
ilert AI SRE is now generally available. Alongside it, this quarter brings Compass, a lifecycle assistant that surfaces the next move during an incident, a dedicated space for postmortems, rich incident cards in Microsoft Teams and Google Chat, on-call schedules that follow support hours and holidays, a new CLI, and dark mode. Here's everything that shipped.
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gitkraken

Best Code Review Collaboration Platforms for AI Teams

Oct 6, 2026 By Jade Nangah In GitKraken
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.
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Alibaba's AI Agent Went Rogue and Started Mining Crypto

Oct 6, 2026 By Harness In Harness
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.
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18: Building an Agentic Future: AI and Optimization with Sachin Gharge

Oct 6, 2026 By Kubex In Densify
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.
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sentry

Unreal MCP now speaks Sentry

Oct 6, 2026 By Ivan Tustanivskyi In Sentry
Setting up crash reporting is rarely the most exciting part of shipping a game. Paste a DSN, flip a few checkboxes in Project Settings, turn on symbol upload, package a build, crash it on purpose and check that the event shows up in Sentry… It’s not hard to do (and important), but it’s the kind of work you’d happily hand off to someone else. With Unreal Engine 5.8, that someone else can be your coding agent.
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Aiven

PostgreSQL MCP: Manage Postgres From Your AI Assistant

Oct 6, 2026 By Tibs (Tony Ibbs) | In Aiven
TL;DR Most of the time we understand the tasks we're working on, but inevitably something comes up that we don't know much about, and we need just enough skill to cope. That used to mean reading paper documentation, then searching vendor sites and the web. Now it tends to mean a dialog with an LLM that has already ingested the documentation we don't have time to find and read. That's only half the problem, though.
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Komodor

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

Oct 6, 2026 By Ben Ofiri In Komodor
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.
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env0

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

Oct 6, 2026 By Zeen Rachidi In env0
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.
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hyperview

Canada Data Center Development: Measuring Responsible AI Growth

Oct 6, 2026 By Jad Jebara In Hyperview
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.
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observiq

How to Filter and Reduce AI Agent Telemetry with OpenTelemetry & Bindplane

Oct 6, 2026 By Adnan Rahic In ObservIQ
Why is the telemetry AI agents generate so intimidating? If you turn on Claude Code’s internal telemetry it’ll throw a wall of text at you. And, it’s very expensive to store. But, the bigger issue is that you can’t make sense of it. Luckily it’s all OpenTelemetry native. That means you can configure it to send, transform, and store what you really need. Which raises the only question that matters. What do you actually need?
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cloudzero

Shipped: See what your AI spend is actually paying for

Oct 6, 2026 By Kaitlin Woo In CloudZero
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.
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kosli

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

Oct 5, 2026 By Bruce Johnston In Kosli
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.
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harness

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

Oct 5, 2026 By Ritabrata Moitra In Harness
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.
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megaport

How Agentic AI Could Change Global Network Deployment

Oct 5, 2026 By Serena Toh In Megaport
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”.
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The Next AI Breakthrough? Teaching AI to Shut Up and Decide

Oct 5, 2026 By Harness In Harness
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?
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Watch an AI Agent Fix a Failed CI Build | Harness Worker Agents

Oct 5, 2026 By Harness In Harness
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.
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upsun

Get your agents off laptops and onto shared infrastructure

Oct 5, 2026 By Upsun In Upsun
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.
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motadata

10 Best AI Help Desk Software for 2026

Oct 5, 2026 By Ramya Shah In Motadata
Are your support teams spending too much time handling tickets and answering repetitive questions? As support requests increase, teams spend more time reading conversations, assigning tickets, finding relevant information, and preparing replies. These tasks can take attention away from complex issues that require human support. AI help desk software can help reduce this workload. It can answer common questions, summarize tickets, suggest replies, route requests, and assist with support tasks.
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9 Best AI Penetration Testing Companies for Enterprise Security Teams

9 Best AI Penetration Testing Companies for Enterprise Security Teams

Oct 5, 2026 By OpsMatters In OpsMatters
Enterprise security teams know the value of penetration testing. The problem is the schedule. A large organization may run hundreds of web applications, thousands of API endpoints, mobile apps, AI features, and a sprawling external attack surface, and much of it changes every week. An annual or quarterly pentest examines a snapshot of that environment, produces a report weeks later, and leaves most of the year untested.
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Stripe aims to power the next generation of AI-driven payments

Stripe aims to power the next generation of AI-driven payments

Oct 5, 2026 By OpsMatters In OpsMatters
Stripe has not only become a leader in modern online payment systems in just a few years, but has also set itself an even more ambitious goal: moving from e-commerce to AI commerce. Stripe wants to become the leading payment infrastructure for AI agents, and it has made that ambition clear with the acquisition of OpenRouter, a platform that routes requests from users and developers to more than 400 AI models from over 80 providers.
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Steer, Block and Audit Agent Behavior from One Place | SAO Agent Control Demo Cisco Agent Control

Oct 3, 2026 By Splunk In Splunk
Most teams keep an agent from regressing by hardcoding checks into its logic, an if-statement here, a regex there. Every new rule then becomes a code change, a review, and a deploy, and the person who spots the problem in production is rarely the person who can ship the fix. Agent Control moves those rules out of the code and into one hub. Steer, block, and validate agent behavior in real time, with rules any team member can update without touching the codebase.
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Block AI Agent Regressions Before They Ship | SAO Pre-Push Eval Gate Demo

Oct 3, 2026 By Splunk In Splunk
Every engineering team has unit tests. They tell you the code still works. They tell you nothing about what the model started saying. This demo wires a single eval gate script into a git pre-push hook, so Splunk Agent Observability scores every agent's output before the push is allowed through. Luna, an on-premise small language model, runs as a synchronous judge against fixed thresholds. Fail one, and the push is blocked.
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Agentic AI or CLM Compliance? A Buying Test for Financial Services

Agentic AI or CLM Compliance? A Buying Test for Financial Services

Oct 3, 2026 By OpsMatters In OpsMatters
Consider a hypothetical bank negotiating a technology supplier agreement. An AI agent spots a change to the audit-rights clause, proposes replacement language and prepares the contract for approval. The review looks faster. Then someone asks which policy version the agent used, whether the replacement was approved, and what prevents the unsigned draft from becoming the operational record. Those questions should shape the buying decision.
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sentry

Seer, the Sentry MCP and CLI, or your own coding agent: where each one fits

Oct 2, 2026 By Paul Jaffre In Sentry
I’ve been getting some version of this question a lot lately, mostly in our Seer preview webinars. Different audiences, same handful of questions: Worth answering all three in one place. Honestly, I needed to write this down for myself too. Things are moving fast around all of us and answers seem to get more nuanced by the week. This is an attempt to codify the difference: what each option is and when it makes sense to reach for one over the other.
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AI Control Tower Live: Governance that moves at machine speed

Oct 2, 2026 By ServiceNow In ServiceNow
One question, ninety minutes: Do you know what AI agents you have running, what they're accessing, and what's their ROI? ServiceNow product leaders open with an overview of why legacy controls can't keep pace with AI agents. Then we'll showcase customer stories from Zespri and Booking.com, end-to-end demos of AI Control Tower, and a look inside ServiceNow's own AI estate.
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megaport

Building Production-ready AI Infrastructure? Start With the Network

Oct 2, 2026 By Kevin Dresser In Megaport
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.
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tigera

HIPAA Wasn't Written for AI Agents. It Applies to Them Anyway

Oct 2, 2026 By Alister Baroi In Tigera
In short, healthcare is adopting AI agents faster than almost any other industry. More than 85% of Epic’s customers already use Epic AI, Epic’s Agent Factory will let every health system build agents of its own from 2027, and 43% of health systems were piloting agentic AI at the start of this year.
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A Simple First-Project Workflow for Trying Seedance 2.5

A Simple First-Project Workflow for Trying Seedance 2.5

Oct 2, 2026 By OpsMatters In OpsMatters
A first AI video project becomes difficult to evaluate when the idea includes several subjects, changing locations, camera moves, and a detailed story. If the output fails, a beginner may have no clear way to tell what went wrong. A small project gives each revision a useful purpose. Try Seedance 2.5 with one visible action and a simple ending. Treat the first output as a draft to inspect before editing.
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icinga

How to Make Claude Your UI Design Companion

Oct 1, 2026 By Florian Strohmaier In Icinga
When I first tried Claude Design, shortly after it was released, I wasn’t impressed. As an every day Figma user, I missed the option to manipulate elements directly, especially for fine tuning details. What I overlooked at that point was the fact that it is really good at generating different options efficiently. Most of them aren’t usable, but getting these options suggested helps when exploring and combining different approaches and ideas.
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scout

Best Monitoring Tools With MCP Servers for AI Coding Agents (2026)

Oct 1, 2026 By Scout APM In Scout
Your AI coding agent can read your code, run your tests, and open a pull request. Until recently it could not see what that code does in production. MCP servers from monitoring vendors close that gap. Connect one, and Claude Code, Cursor, or Copilot can pull the error, the trace, and the slow query behind a bug report without you copying anything out of a dashboard. Most major monitoring vendors now offer an official MCP server. But they aren’t interchangeable. Some only expose errors.
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BigPanda Analytics: AI-driven insights and faster answers across all your ITOps data

Oct 1, 2026 By BigPanda In BigPanda
See how BigPanda Analytics turns IT operations analytics into instant answers, no hand-built reports required. IT leaders are used to waiting on a report someone on the ops team had to hand build, and every follow-up question starts the cycle over again, while the business keeps moving. This demo shows how IT executives get direct access to IT operations analytics: prebuilt dashboards, AI-powered insights, and a natural language research tool that answers questions in real time.
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Endpoint Management with AIDriven Automation

Oct 1, 2026 By Ivanti In Ivanti
In just two minutes, learn how our AI-powered platform unifies control across Windows, Mac, Linux, Mobile, and even VR/XR headsets. Discover how to eliminate tedious tasks with automated patching, zero-touch onboarding, and self-healing capabilities—allowing your team to focus on strategy instead of firefighting. What you’ll see in this video: How to achieve full visibility across your entire environment. The benefits of risk-based patching and continuous compliance. Proactive user experience optimization powered by AI. How to reduce risk and scale IT efficiency on a single platform.
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Cycle's Hosted MCP Release Announcement

Oct 1, 2026 By Cycle Platform In Cycle
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.
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Incident.io

Building Investigations: what it takes to build an AI SRE

Oct 1, 2026 By Article In Incident.io
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.
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cloudzero

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

Oct 1, 2026 By Kevin Lamb In CloudZero
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.
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Your data says one thing. Your AI thinks another.

Oct 1, 2026 By Aiven In Aiven
Aiven and SFEIR walk through what a governed, AI-ready foundation for product data looks like, and what it actually takes to build one. We'll be joined by Céline Thooris, Managing Director of WEnvision (SFEIR group), and Stan Dmitriev, Product Director for Aiven Context, sharing a first-hand view from the field and a concrete next step. What to expect.
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Cycle

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

Oct 1, 2026 By Alexander Mattoni In Cycle
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.
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gitkraken

Best ADEs for Multi Agent Coding in 2026

Oct 1, 2026 By Jade Nangah In GitKraken
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.
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The hidden costs of AI (and who ends up paying them) | The Simple Talk Podcast

Oct 1, 2026 By Redgate Software In Redgate
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.
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Top 5 AI Pitch Deck Tools for Sales Teams That Cut Slide Creation Time

Top 5 AI Pitch Deck Tools for Sales Teams That Cut Slide Creation Time

Oct 1, 2026 By OpsMatters In OpsMatters
AI pitch-deck tools promise "60-second" creation, yet reps keep burning hours fixing fonts, charts, and brand colors. We benchmarked 12 contenders and timed every step-from first prompt to a client-ready PowerPoint or Google Slides file. Only five met our bar for deck quality, native editability, workflow speed, collaboration depth, value, and security. This guide shows which tool wins each sales scenario so you can choose based on data, not hype.
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