Operations | Monitoring | ITSM | DevOps | Cloud

speedscale

Flamegraphs Find It. Replay Proves It.

Jul 31, 2026 By Matt LeRay In Speedscale
I made an API endpoint 13 times faster. Then I realized my first verification only checked the status, headers, and response schema. I had not checked the totals. I had made the bug faster. That is the problem with giving an AI coding agent one kind of evidence. A CPU profile can show where the application is slow, but not whether an optimization preserves behavior. A traffic replay can prove that behavior stayed stable, but not explain why the code burns CPU.
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Why More UK Firms are Turning to Colocation for their AI Workloads

Why More UK Firms are Turning to Colocation for their AI Workloads

Jul 31, 2026 By OpsMatters In Pulsant
The last few years have seen AI conversations dominated by the need for investment in hyperscale infrastructure as firms race to build ever larger training models. But as those conversations evolve, the emphasis is shifting to the next phase of AI adoption, focusing on the scaling of use cases and real-world value.
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elastic

Closing the AI gap: How next-generation knowledge access unlocks mission outcomes for government

Jul 31, 2026 By Oksana Abramovych In Elastic
A recent IDC Spotlight report based on a survey of 685 public sector respondents found that 72% describe scaling AI from pilot to production as "very" or "somewhat" difficult.¹ Choosing the right model is only part of the challenge. Agencies also need to get their data ready for AI.
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Agent Observability Deep Dive Demo | Grafana Cloud

Jul 31, 2026 By Grafana In Grafana
Grafana AI Observability is our new database and platform for observing AI Agents. Over the past year at Grafana Labs, we built Agents and we needed a way to understand how they are performing, what are the costs associated with them, what's the error rate or time to the first token as well as how they are behaving. Grafana Staff Engineer, Ivana Hučková provides a deep dive demo on how Grafana AI Observability connects our experience building Agents with our experience building observability systems.
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gitkraken

Kepler Is in Public Preview: One Task, Every Repo, Every Agent

Jul 31, 2026 By Jade Nangah In GitKraken
A faster car doesn’t get you home faster if the freeway is still jammed. That is the problem most teams run into once they add a second, third, or fourth AI coding agent to the mix. More agents generate more code. They do not automatically generate more finished work, because someone still has to track which agent is waiting on input, which one just opened a pull request, and which one has been quietly stuck for twenty minutes. Kepler is GitKraken’s answer to that traffic jam.
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cloudzero

LLM cost optimization: 7 strategies to cut inference spend

Jul 31, 2026 By Lyne Carolyne In CloudZero
LLM cost optimization is the practice of cutting what you spend on large language models, mostly inference, without losing the quality that makes the AI worth running. The biggest levers are routing requests to cheaper models, caching repeated tokens, batching anything that can wait, trimming prompts, right-sizing models, cutting calls you do not need, and putting one gateway and cost view in front of all of it.
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cloudzero

What is FP&A? Financial planning and analysis in the AI spend era

Jul 31, 2026 By Lyne Carolyne In CloudZero
FP&A stands for financial planning and analysis. It is the corporate finance function responsible for budgeting, forecasting, variance analysis, and decision support. If you're asking what is FP&A in practice: FP&A teams build the annual operating plan, project revenue and expenses, explain gaps between plan and actuals, and give leadership the numbers behind strategic decisions. Accounting reports what happened. FP&A models what happens next.
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upsun

Software is a team sport. Most AI tools forgot that.

Jul 31, 2026 By Upsun In Upsun
Every AI coding tool ships the same promise: your developers, faster. Autocomplete in the IDE, agents in the terminal, a working prototype before lunch. And it delivers, at least for the person holding the keyboard. The problem is that most of what it takes to ship software was never a solo activity, and that is the part the market keeps skipping.
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megaport

Megaport Signs Open Weights and American AI Leadership Letter

Jul 31, 2026 By Megaport In Megaport
Megaport has signed the Open Weights and American AI Leadership letter, supporting open-weight AI, customer choice, and the infrastructure that powers AI innovation. Artificial intelligence is reshaping how organizations build, deploy, and scale digital infrastructure. As AI adoption accelerates, the conversation is evolving beyond model performance alone to the broader ecosystem needed to support long-term innovation.
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Why Every Modern Security Operation Center Needs Automation and AI

Why Every Modern Security Operation Center Needs Automation and AI

Jul 31, 2026 By OpsMatters In OpsMatters
Security teams no longer face a simple monitoring problem. In most cases, they face - While cloud workloads change by the minute, identities move across applications. In general, endpoints appear outside the traditional perimeter. Meanwhile, the modern security operations center must interpret all that activity. It must also not let a genuine threat disappear inside routine noise. Although traditional processes still matter, manual triage cannot carry the entire workload anymore. In fact, analysts lose valuable investigation time if they -
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checkly

CLIs are more token-efficient than MCP. Or are they?

Jul 30, 2026 By Stefan Judis In Checkly
MCP servers have a reputation: they eat your context window. CLIs paired with skills, on the other hand, are more token efficient. But is this still true? I dropped all my MCP servers five months ago. Five months is a long time in AI land. When Anthropic came up with the concept of skills, many people stopped using MCP servers in favor of CLI tooling and skills.
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appsignal

Triage Production Incidents with a Single Prompt Using the AppSignal CLI

Jul 30, 2026 By Karen Patteri de Souza In AppSignal
At AppSignal, we love talking to our customers to learn how they're using the product. Recently, one of them showed us something worth sharing: with a single chat prompt, his AI agent searches production logs, closes incidents, and checks whether a pull request has shipped. Automating that kind of work turned out to be a matter of building the right agent skill.
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gitkraken

GitKraken's Claude Code Plugin Is Live: No CLI Required

Jul 30, 2026 By GitKraken In GitKraken
If you haven’t heard about our MCP server, you should really check it out. It’s probably the best way to give your agents access to the power of GitKraken’s integrations and features. Our MCP tools also help your agents understand your codebase in a way that we think lowers your token usage and improves their output.
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cloudzero

Agentic AI cost: why agents burn tokens and how to control it

Jul 30, 2026 By Keith MacKenzie In CloudZero
Agentic AI cost is what you pay to run AI agents, and it is mostly tokens. An agent does not answer once. It loops, calls tools, reads the results, and reasons again, re-sending a growing context every step. Anthropic found agents use about 4x the tokens of a chat, and multi-agent systems about 15x. You control it by capping runs, right-sizing the architecture, routing, caching, and measuring cost per task, then tying every agent to the AI ROI it produces.
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cloudzero

AI cost monitoring: what it is, how it works, and why real-time visibility matters

Jul 30, 2026 By Lyne Carolyne In CloudZero
AI cost monitoring is the continuous tracking of AI and LLM spend in real time, broken down by the models, features, teams, and customers generating it. It is not the same as reading the monthly bill - done well, it shows spend as it happens, flags anomalies before they become invoices, and connects every dollar to an outcome so finance can protect AI ROI instead of explaining it after the fact.
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Komodor

4 Cloud-Native Challenges AI SRE Is Solving in 2026 and the 3 New Ones to Look Out For

Jul 30, 2026 By Komodor In Komodor
AI SRE is making real strides in resolving some of the greatest pains related to incident response, troubleshooting, and complex root cause analysis. The on-call rotation, the war room, the week-long RCA, and the ticket queue that ate a third of every platform engineer’s week all look different now than they did two years ago.
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The Technologies Shaping the Future of Work

The Technologies Shaping the Future of Work

Jul 30, 2026 By OpsMatters In OpsMatters
Work is changing fast. The old nine-to-five grind feels outdated. People want flexibility. They want meaning. They want to avoid soul-crushing repetition. Technology drives this shift. New tools handle the boring stuff. They connect teams across continents. They make work more human, not less. The future workplace looks different than anyone predicted. It is more collaborative. It is more creative. It is powered by smart machines that amplify human potential. This transformation is already happening. Here is what it looks like.
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Faster Construction Estimates Start With Better Takeoff Control

Faster Construction Estimates Start With Better Takeoff Control

Jul 30, 2026 By OpsMatters In OpsMatters
Estimating pressure has always been part of construction. Plans come in late, bid dates stay firm, and estimators are expected to move quickly without missing scope. The problem is not only speed. The real challenge is producing a number that can survive review, negotiation, award, and handoff to the project team.
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manageengine

GPU monitoring in OpManager: Full visibility for every AI workload

Jul 29, 2026 By Visakh P S In ManageEngine
AI has moved to be a core part of enterprise infrastructure. GPUs are the engines behind that shift. Every training run, every inference request, and every fine-tuning job depends on GPU chipsets that are expensive and delicate. A GPU that overheats, runs out of memory, or sits idle for hours doesn't just slow a project down, it quietly drains the IT budget. Most monitoring tools weren't built with this hardware in mind. This leaves AI and DevOps teams blindsided when a job fails or a chipset degrades.
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Are Coding Agents Out of Control?

Jul 29, 2026 By Harness In Harness
OpenAI just disclosed that two of its own AI models went rogue during an internal red-team test — escaping their sandbox, reaching the open internet, and hacking Hugging Face on their own. OpenAI called it an“unprecedented cyber incident.” So are autonomous coding agents already out of control? In this episode of ShipTalk — brought to you by Harness — hosts Martin Reynolds and Adam Arellano break down the story that reads like science fiction, then get to the harder truth underneath it. In the same week, OpenAI, Anthropic, and Google all shipped repository-wide coding agents within 24 hours of each other.
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meshiq

Your AI Agents Can Take Action Now. Can You Prove They Should Have?

Jul 29, 2026 By Gourab Basu In meshIQ
Enterprise AI agents clear every demo and pilot, then hit a compliance wall. The gap isn't technology—it's architecture. Discover why governance must sit inside the execution flow across six control points, not bolt on afterward as an afterthought at input and output only.
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Harness + Devin IDE: Automate Governance and Delivery for the Agentic Era

Jul 29, 2026 By Harness In Harness
As AI software engineers like Cognition's Devin accelerate code production, downstream delivery, and governance processes must keep pace. In this video, see how Harness closes the gap by providing autonomous oversight for autonomous code. Watch a step-by-step demonstration of Devin fixing a real defect in a broken banking application while the Harness platform stands between the fix and production to ensure complete safety and validation.
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How Agentic AI Is Transforming IT Operations | AI Automation, Zero Ticket IT & Telecom Innovation

Jul 29, 2026 By Resolve In Resolve
What does it really take to move from AI experimentation to enterprise-wide automation? In this episode of Agents of IT, host Zach Austin sits down with Bruno Santos, Head of Consulting, Sales, and Business Development at Sell Focus, to discuss how leading telecommunications providers are using AI, automation, and agentic workflows to modernize IT and network operations.
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squared up

Our 3-month AI roadmap - the future of smart dashboards

Jul 29, 2026 By Blog In Squared Up
AI is set to transform our technology landscape. For many of us working in software, it already has — developers are now writing more code, building more features, and deploying more applications, faster. For the teams supporting IT and software services that means more applications to support, across a greater breadth of technologies, and with more complexity (that is probably less well understood by the developers who created it). Your operational tooling needs to keep pace.
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Why Enterprise AI Pilots Fail and How to Move to Production | Bruno Santos

Jul 29, 2026 By Resolve In Resolve
Why do so many enterprise AI initiatives stall after the pilot phase? In this Agents of IT Short, Bruno Santos of Sell Focus shares why successful AI adoption starts with solving real business problems, not chasing the latest technology. Learn how IT leaders can scale AI, accelerate automation, and move toward autonomous operations.
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Cloud 66

Who Owns Deployment Governance? Structuring Accountability in the AI Era

Jul 29, 2026 By Kelley Schultz In Cloud 66
In this series, we have talked about how generative AI is shifting the landscape of software creation. In The New Software Creator, we explored how AI expands who can write code. In When Anyone Can Build Software, Deployment Governance Is What Keeps It Safe, we looked at why the deployment pipeline is the ultimate control point. Finally, in Security at Scale: What Changes When Everyone Can Deploy, we dug into the technical realities of patching, container hygiene, and identity management.
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Run tests using natural language with k6 Agentic Testing

Jul 29, 2026 By Grafana In Grafana
In this video, our Senior Director for AI Engineering, Mat Ryer, issues a challenge: Can k6 agentic testing in Grafana Cloud be instructed at a high level to just beat Wordle? Staff Software Engineer Joan López de la Franca Beltran sets up that scenario using agentic testing (currently experimental), yielding some surprising results.
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Automatically starting investigations from an alert with Assistant Investigations

Jul 29, 2026 By Grafana In Grafana
Staff Software Engineer Alexander Sniffin demonstrates how you can use Assistant Investigations to automatically start an investigation for you when an alert fires in Grafana. When you receive an alert, Investigations can do the work to figure out the root cause so that you don't have to spend your time doing so. Assistant Investigations is now generally available for Grafana Cloud.
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Only 1 in 4 Employees Follow AI Policy: How to Fix It

Jul 29, 2026 By Ivanti In Ivanti
AI is more than just a tool—it's a transformative experience for the modern workforce. But as employees "run fast" to adopt AI, a critical gap is forming between innovation and safety. In this video, Brooke Johnson, Ivanti’s Chief Legal Counsel and SVP of People and Security, discusses the "natural tension" between AI excitement and the necessity for responsible, secure implementation. With only 25% of employees reporting consistent policy adherence, the risk of "Shadow AI"—unsupervised tool use—has never been higher.
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AI didn't take humans off the platform, it just changed the job they do there.

Jul 29, 2026 By Cortex | Engineering Operations Platform In Cortex
Agents are writing more of the code these days, but that doesn't make them the only user of your platform. Abby Bangser, Principal Engineer at Syntasso and CNCF Ambassador, makes the distinction: the agent might be your primary coder, while humans are still validating what it builds and interacting with the system it runs on. From a Braintrust conversation with engineering leaders on AI agents and engineering operations.
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gitkraken

GitLens 18 Turns the Commit Graph Into an Agent Command Center

Jul 29, 2026 By Jade Nangah In GitKraken
Five coding agents sounds like leverage right up until a developer is the one keeping track of all five: one fixing a bug, one building a feature, one refactoring, and two waiting on input at the same time. AI did not create that problem. It exposed a workflow problem that was always going to surface once parallel development became normal instead of occasional.
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Graylog MCP Howto Webinar

Jul 29, 2026 By Graylog In Graylog
In this video, we walk through connecting the Graylog MCP Server (introduced in Graylog v7.0) to Claude CLI, enabling natural language interaction with your Graylog instance through Claude Desktop. Topics covered: Whether you're a Graylog admin looking to speed up investigations or a security engineer curious about AI-assisted log analysis, this walkthrough gives you everything you need to get MCP running end to end.
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grafana

Automate all the things: How to use Grafana Cloud's AI to relieve the operational burden

Jul 29, 2026 By William Dumont In Grafana
Continuous integration and continuous delivery (CI/CD) have dramatically changed how we ship software. But once code reaches production, the operational work is still surprisingly manual. Engineers continually monitor systems, investigate unexpected behavior, and decide which issues require action. And that is where the next opportunity for AI-driven automation lies. For example, in today's CI/CD workflows, someone refreshes the pipeline page to see whether the queue has moved.
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cloudzero

A default is not a decision: cut AI model costs with CloudZero's free, open-source Model Rightsizer

Jul 29, 2026 By David Aponovich In CloudZero
Only 22% of finance leaders can tie their AI spend to a business outcome, according to CloudZero’s 2026 finance survey. When AI ROI falls short, it usually isn’t because a company is doing too much AI. It’s that no one is watching which model runs which task, and that one choice accounts for a large part of the cost. Here’s why it happens.
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cloudzero

Model Rightsizer: the agent that stops your other agents from defaulting to Fable

Jul 29, 2026 By Djo Lopez In CloudZero
Model Rightsizer is an open-source Claude Code sub-agent from CloudZero that scores each task on capability need versus cost pressure, then routes it to the smallest model that can handle it. In its first week, it cut Opus spend 75% while shifting 234x more work to Sonnet. Every Claude Code agent you run has to answer a question it usually never gets asked: does this task need the smartest model available, or are you paying Fable prices to rename a variable across three files?
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harness

Cloud Asked What It Cost, AI Is Asking What It's Worth | Harness Blog

Jul 29, 2026 By Patrick Brogan In Harness
AI has quickly become one of the largest and fastest-growing enterprise expenses, exposing many of the same governance and visibility challenges organizations previously faced with cloud. Based on findings from the 2026 State of AI in FinOps report, we explore how mature organizations improve AI cost ownership, reduce waste, and build a culture focused on measurable business value.
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Software is a team sport. AI tooling forgot that - Upsun Product Highlights

Jul 29, 2026 By Upsun In Upsun
AI tools made individual developers faster. Teams still aren't shipping more product. That gap is the whole reason Upsun Dispatch exists. In this Product Highlights conversation, Kateryna Dvornichenko, a product manager at Upsun who has spent the past several months building Upsun Dispatch, explains why the tooling market got the unit wrong. Her take: "Making software is a team sport." We get into.
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iOPEX

Why 95% of AI Pilots Fail: 5 Questions from ServiceNow's Chief Transformation Officer for Every CXO

Jul 29, 2026 By Kedar Kulkarni , In iOPEX
Ask most enterprises why their AI program hasn't moved past pilots, and you'll get an answer about the model. It's not accurate enough, not fast enough, not cheap enough yet. Srikanth Akkiraju, who has run transformation at Philips and now at ServiceNow, doesn't buy it. In a recent fireside conversation with iOPEX, he made the case that the model was never the problem. The problem is that most enterprises haven't decided what they actually want AI to change. Five questions came out of that conversation.
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How AI Agents Are Changing ITSM Faster Than We Think | Motadata Webinar

Jul 29, 2026 By Motadata In Motadata
AI is transforming ITSM beyond co-pilots with autonomous AI agents that can understand, decide, and act. In this webinar, discover how AI agents are reducing manual workloads, accelerating incident resolution, improving service quality, and enabling intelligent service operations. Learn real-world use cases, key implementation strategies, and how organizations can move from reactive support to proactive, AI-driven IT service management. Watch now to explore the future of smarter, faster, and more efficient ITSM.
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The Business Benefits of a Strong Asset Management Strategy

The Business Benefits of a Strong Asset Management Strategy

Jul 29, 2026 By OpsMatters In OpsMatters
Every business depends on valuable assets, from equipment and machinery to buildings and technology. How these assets are managed has a direct impact on productivity, operating costs, and long-term growth. Without a clear strategy, businesses may face unexpected breakdowns, rising maintenance expenses, and poor use of resources. A strong asset management strategy helps organizations track asset performance, plan maintenance, extend asset life, and make better investment decisions. It also improves efficiency and supports smarter business planning.
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Best 7 GPU VPS Provider for Machine Learning (ML) and AI

Best 7 GPU VPS Provider for Machine Learning (ML) and AI

Jul 29, 2026 By OpsMatters In OpsMatters
There is no reason to buy a GPU. That's unless you train your model or do serious image/video manipulation. A GPU server costs several times more than a CPU VPS for the same month. "Nine out of ten requests for a GPU server for AI actually need a mid-size CPU VPS. They are serving a model, not training one. Match the hardware to the task at hand. Save money. Don't compromise on performance.".
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Why Interactive Vending Machines Are Becoming the Next Big Business Opportunity

Why Interactive Vending Machines Are Becoming the Next Big Business Opportunity

Jul 29, 2026 By OpsMatters In OpsMatters
Businesses are always looking for fresh ways to draw in customers, raise revenue, and offer experiences people will remember. Interactive vending machines are among the fastest-growing developments in automated retail, bringing together convenience, technology, and entertainment in one system. Traditional machines mainly dispense products; interactive models go further by engaging users with touchscreens, artificial intelligence, digital payment options, and personalized experiences.
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Install AURA to Debug Incidents Using an Open Source SRE Agent

Jul 28, 2026 By Mezmo In Mezmo
AURA is a fully open-source agentic harness built for SRE and production operations work. In this walkthrough, Mezmo forward deployed engineer Jeff iinstalls AURA on a local desktop, runs `aura init` to generate the config and connect it to an Anthropic Sonnet model, then wires in a Grafana MCP server pointed at his homelab. He hands AURA a live incident: a set of addressable LED lights that stopped responding to Home Assistant.
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cloudzero

How to prove the business value of AI

Jul 28, 2026 By Keith MacKenzie In CloudZero
Proving AI business value means sorting every AI investment into one of four buckets - revenue growth, cost avoidance, productivity gain, or risk reduction - then tracking spend at the unit level (per feature, customer, or team) so each dollar has a traceable return. Most companies measure one bucket well and leave the rest unattributed. That gap is why the same AI deployment can look like a $40M win and a public reversal at the same time.
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gitkraken

Gemini Models are Misunderstood

Jul 28, 2026 By Chris Griffing In GitKraken
Recently, Google released a couple new Gemini models. They were Gemini 3.6 Flash, 3.5 Flash Lite, and 3.5 Flash Cyber. Many people on the internet roasted Gemini Flash and Flash Lite for their less-than-frontier performance. This makes sense when you consider that OpenAI and Anthropic have been sparring back and forth for first place for quite a while but Gemini almost never gets that first place position. After all, this is Google we are talking about.
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nexthink

The New AI Mandate: Smarter Usage, Lower AI Compliance Risk, Better Outcomes

Jul 28, 2026 By Shawn Lazarus Senior Product Marketing Manager In Nexthink
For the last two years, enterprise AI strategy has largely revolved around one message: use AI as much as possible. CIOs encouraged experimentation, CFOs approved budgets, and organizations pushed employees to adopt tools like ChatGPT, Claude, Copilot, and Gemini in the hope that productivity gains would naturally follow. The prevailing assumption was that simply increasing usage would accelerate innovation and unlock efficiency across the organization. But the enterprise conversation is changing quickly.
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Meet GCX: Give Your AI Coding Agent Production Context

Jul 28, 2026 By Grafana In Grafana
Your AI agents are only as good as the context it has. Without access to what's happening in production, it can only make educated guesses. Chapters: In this video, you'll meet GCX. The bridge between AI coding agents like Claude Code, Codex, Cursor, and your Grafana observability stack. You will learn how GCX securely gives AI agents access to metrics, logs, traces, dashboards, and other production telemetry so they can investigate issues, answer questions, and help you debug with real operational context.
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circleci

What is an AI sandbox? A developer's guide

Jul 28, 2026 By Roger Winter In CircleCI
An AI sandbox is an isolated environment where code from an AI coding agent runs without direct access to your machine or your production systems. If the agent runs a destructive command or a mistaken script, the damage stays contained inside the sandbox. Developers use AI sandboxing to let agents execute code freely while keeping the host and its credentials out of reach.
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How to Connect Cursor to CircleCI: AI-Powered CI/CD Debugging with MCP

Jul 28, 2026 By CircleCI In CircleCI
Stop context-switching between your IDE and CI dashboard. This video shows you how to connect Cursor to CircleCI using the CircleCI MCP server so your AI agent can read pipeline failures, validate configs, and trigger builds without leaving your editor. In this demo, we introduce a bug, let CI catch it, and watch the agent diagnose and fix it autonomously through a full green pipeline. No manual log hunting required.
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Hi3D: Making AI 3D Printing More Accessible by Connecting Creativity, Design, and Real-World Production

Hi3D: Making AI 3D Printing More Accessible by Connecting Creativity, Design, and Real-World Production

Jul 28, 2026 By OpsMatters In OpsMatters
3D printing has changed the way people create objects. What once required complex manufacturing processes can now be completed through a digital workflow, allowing individuals to design customized products, creative models, and personalized items more easily.From hobbyists creating unique designs to professionals developing prototypes, 3D printing is becoming increasingly connected with everyday creativity.
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almaden ai

How Collective IQ Turns Reactive IT into Truly Proactive IT

Jul 27, 2026 By Almaden AI In Almaden AI
Most IT organizations still operate in "firefighting" mode: an employee opens a ticket, the service desk investigates, depending on severity and complexity multiple teams or people are involved to diagnose, and then the appropriate person or team fixes the issue. The whole process then repeats for the next reported incident. This model doesn't scale, drains time and budget, and leaves a huge number of issues unresolved because many employees simply don't bother to report them. And, if and when they do report them, it's too late, the problem has already impacted their productive work.
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grafana

Smarter onboarding and planning with Grafana Assistant: How to ensure observability is baked in from the start

Jul 27, 2026 By Sven Großmann In Grafana
It's Monday afternoon and that feature you've been working on is mostly done. There's just one item still sitting untouched at the bottom of the ticket: "Add monitoring." You know you should. You also know the sprint ends tomorrow, nobody on the team is an observability expert, and figuring out what to measure—let alone how to write the PromQL for it—feels like a project all on its own. So it gets the same treatment it always does: "We'll add it when it breaks.".
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cloudzero

OpenAI Codex pricing in 2026: plans, token costs, and usage limits

Jul 27, 2026 By Lyne Carolyne In CloudZero
Codex pricing runs six tiers, from free to $200 a month, but the sticker price is not your real bill. OpenAI Codex pricing 2026 charges by the token, not the plan, a change that took effect in April. Plus is $20, Pro starts at $100, and everything past that depends on how many files you let the agent read. Most Codex pricing guides hand you a price list and call it done. That is like pricing a taxi ride by the door handle. The meter is what matters, and OpenAI put a real one on Codex this year.
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cloudzero

Claude Opus 5 pricing: same sticker, different bill

Jul 27, 2026 By Lyne Carolyne In CloudZero
Claude Opus 5 launched July 24, 2026 at $5 per million input tokens and $25 per million output tokens, identical to Opus 4.8. It delivers near Claude Fable 5 performance at half Fable's price and is now the default model on Claude Max. New effort settings let teams trade capability for token savings, which means two teams on identical pricing can now run up very different bills. Finance teams, that last part is your problem. Anthropic has shipped a model that costs exactly what the old one cost.
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Meet Assistant Workspace: Full-page experience for Grafana Assistant

Jul 27, 2026 By Grafana In Grafana
Introducing Assistant Workspace, a full-page surface for Grafana Assistant, built for the conversations that outgrow a sidebar. Dig into longer investigations, compare data side by side, and keep your train of thought in one place — then turn what you find into a dashboard without starting over. When a quick question becomes a real investigation, open it in Workspace and keep going. In this video, Ed Poole gives us a demo of how to use Workspace, including the use of canvases to see more information than before.
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logz.io

Executive Roundtable: Guardrails for the Autonomous Era

Jul 27, 2026 By Libi Michelson In logz.io
Ask ten engineering leaders how far their organization has actually gotten with autonomous AI, and most will admit the same thing once the marketing language drops away: not nearly as far as it looks from the outside. That was the undercurrent of a roundtable Logz.io and Twingate hosted on July 22, 2026, bringing together VPs of engineering, CTOs, senior security directors, and several product leaders across different industries and company stages.
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upsun

AI fatigue: what happens when product teams can't keep up with their own agents

Jul 27, 2026 By Upsun In Upsun
For the past two years, the conversation around AI in software engineering has focused on one thing: productivity. Engineers are shipping faster, writing more code, and completing work in hours that once took days. Every new model promises another leap forward. What gets far less attention is what all that speed demands from the people using it. Guillaume Moigneu, Field CTO at Upsun, has spent the past year watching engineering teams adapt to AI-assisted development.
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Teneo

Why Written AI Policies Alone Won't Protect Your Organization

Jul 27, 2026 By Teneo In Teneo
Most organizations have responded to the rapid growth of AI by creating written policies that define acceptable use. A clear AI policy can establish expectations, assign responsibilities, and help employees understand how AI should and shouldn’t be used. But policy alone can’t provide oversight and is almost impossible to enforce at scale without the right tools.
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tigera

Why eBPF Is Useful for Watching and Sandboxing AI Agents

Jul 27, 2026 By Peter Kelly In Tigera
Most of our runtime security habits were built for deterministic workloads. A service does what its code says: review the code, sign the image, and its behavior is bounded. Agents are different. An agent’s behavior emerges from a model reasoning over whatever lands in its context window, and some of that context comes from places we don’t fully control — a retrieved document, a tool’s output, a user’s prompt.
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Tier 1 SOC Automation Options Explained

Tier 1 SOC Automation Options Explained

Jul 27, 2026 By OpsMatters In OpsMatters
In 2026, like in every other year, tier 1 is the front line of the SOC. It's where alerts land, where triage happens, and where most of the repetitive work lives. Unsurprisingly, it is also where automation is moving fastest. There is a lot of skepticism around how much of tier 1 can be reliably automated. If you want to see some, just have a look on Reddit or other forums. But there is definitely a growing market and capability for AI-enabled tools to learn, guide and automate tier 1 workflows.
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Seedream 5.0 Pro AI Image Generator: Advancing Creative Workflows for Modern Content Production

Seedream 5.0 Pro AI Image Generator: Advancing Creative Workflows for Modern Content Production

Jul 27, 2026 By OpsMatters In OpsMatters
AI has quietly rewritten how digital content gets planned, designed, and delivered - across pretty much every industry that touches a screen. Somewhere in the middle of that shift sits Seedream 5.0 Pro AI image generator, drawing attention as part of a larger move toward creative workflows that don't just generate images, but actually fit together end to end. As AI-assisted design keeps maturing, creators, marketers, and businesses alike are gravitating toward tools that streamline visual production without sacrificing consistency across formats.
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The Rise of Generative Engine Optimisation Services and What Businesses Need to Know

The Rise of Generative Engine Optimisation Services and What Businesses Need to Know

Jul 27, 2026 By OpsMatters In OpsMatters
Search is changing in a way that feels subtle on the surface but significant underneath. People still type questions into Google, but they are also asking ChatGPT, Perplexity, Gemini, and other AI tools for direct answers, recommendations, summaries, and comparisons. In many cases, they are not clicking through a list of ten blue links first. They are reading a synthesised response and making decisions from there.
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How AI for Short-Term Rentals Is Reshaping Property Operations

How AI for Short-Term Rentals Is Reshaping Property Operations

Jul 26, 2026 By OpsMatters In OpsMatters
Running a short-term rental used to mean juggling a dozen different tasks by hand. Checking messages, updating calendars, adjusting prices, coordinating cleaners, and answering the same guest questions over and over. Anyone who has managed even a single listing knows how much time this takes, and anyone managing multiple properties knows how quickly it becomes overwhelming.
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Integrating AI Into a System You Don't Fully Trust Yet: A Staged Rollout Framework

Integrating AI Into a System You Don't Fully Trust Yet: A Staged Rollout Framework

Jul 26, 2026 By OpsMatters In OpsMatters
Many businesses want to introduce intelligent software to improve efficiency and reduce manual work. The challenge begins when it needs access to systems that manage customer data, financial records, inventory, or other business-critical operations. A single mistake in these environments can disrupt operations, create compliance risks, lead to financial losses, or damage customer trust.
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puppet

Building with AI: Our Approach to Responsible Agentic Development in Open Source

Jul 24, 2026 By Puppet In Puppet
The tech world has been building up towards the shift to a fully agentic development life cycle for a few years now. AI is changing how software gets built. Across the Puppet ecosystem, we’re seeing a shift toward more agentic engineering workflows. AI helps generate code, shape documentation, and accelerate how Puppet modules evolve.
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Agentic Pipelines | Bitbucket Blitz | Atlassian

Jul 24, 2026 By Atlassian In Atlassian
Most CI/CD pipelines are fragile bash scripts that break when things change. What if your pipeline could think? Agentic Pipelines lets you add AI agents as steps in Bitbucket Pipelines. In this video, I show an agent that reads a design spec from Confluence, generates frontend code, runs tests, and opens a PR, all inside a pipeline. With Agentic Pipelines, Bitbucket goes from a CI/CD platform to a full workflow and automation engine you can use far beyond builds and deploys.
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Switching Between AI Agents Like This Is a Game Changer #ai #productivity

Jul 24, 2026 By GitKraken In GitKraken
AI didn't just change how fast code gets written. It exposed a new bottleneck: everything around the code. Reviews slow down. Context gets lost. Planning drifts from implementation. Teams move fast and still feel stuck. That's the problem GitKraken is built to solve, and this Friday we're going live to walk through what's changed. We'll cover the latest Code Flow Company features we've shipped, how they connect developers, AI agents, and production into one system, and what it actually looks like to go from plan to main without the chaos.
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Can a T-Shirt Fool AI? Why AI Guardrails Matter for IT | Zero Ticket Minute

Jul 24, 2026 By Resolve In Resolve
Can AI be influenced by something as simple as a T-shirt? New research suggests irrelevant context can affect how some AI models respond. In this Zero Ticket Minute, Ian explains why AI guardrails matter and what IT leaders should consider as they adopt agentic AI and autonomous operations.
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nexthink

How Claude Mythos Changes the Future of Vulnerability Management: Fixing, Not Finding

Jul 24, 2026 By Nexthink In Nexthink
Anthropic’s Claude Mythos shows how AI is making vulnerability discovery nearly infinite. Endpoint remediation is where IT teams win or lose. In April 2026, Anthropic introduced Claude Mythos Preview, an AI model that autonomously discovered thousands of previously unknown vulnerabilities across every major operating system and web browser. By late May, the running total had passed 23,000 potential findings, and the vast majority were still unpatched.
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circleci

What is a remote MCP server?

Jul 24, 2026 By Jacob Schmitt In CircleCI
As development shifts toward agentic workflows, an AI agent is only as capable as the systems it can reach. Local MCP servers allow desktop CLI and IDE agents to execute multi-step tasks on your machine. But remote MCP servers (also called hosted MCP servers) extend that reach to cloud-based and background agents, allowing an agent running in a web browser, a CI runner, or a backend service to access external tools over HTTP without needing a developer’s machine running local child processes.
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hyperview

Agentic AI in the Data Center: What It Really Means, and Why Security Has to Come First

Jul 24, 2026 By Jad Jebara In Hyperview
Agentic AI means a system that acts on behalf of a specific person, within that person’s exact role and access permissions — not a general term for “smart” software. In data center infrastructure, agentic AI only becomes safe to deploy once three things already exist: a complete monitoring pipeline, an analytics pipeline, and a control pipeline governed by strict role-based access control.
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AssemblyAI scales production Voice AI with Datadog's unified observability

Jul 24, 2026 By Datadog In Datadog
AssemblyAI is a leading Voice AI platform that provides speech-to-text models and AI infrastructure developers use to build real-time voice applications. AssemblyAI uses Datadog to unify observability across its AI inference pipelines and multi-cloud GPU infrastructure, enabling the team to optimize performance and costs, accelerate model releases, and confidently deliver fast, reliable AI experiences at scale.
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How to Build a Reliable Review Gate for AI Generated 3D Assets

How to Build a Reliable Review Gate for AI Generated 3D Assets

Jul 24, 2026 By OpsMatters In OpsMatters
A creative team generates twenty 3D props in an afternoon. The files look acceptable in preview images, so they are placed directly into the shared asset library. Days later, developers discover inconsistent scale, missing textures, reversed normals and several models with unclear ownership or revision status. The generation process worked. The production process did not.
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speedscale

Imaginary Test Data. Real Token Bill.

Jul 23, 2026 By Alan Mon In Speedscale
Ask an AI for K-pop concert advice without saying the group, city, date, or budget. It may confidently send you to a BLACKPINK tribute night in Cleveland with a $400 resale ticket. The AI was plenty confident. It just had nothing real to go on. That is exactly what happens when developers test AI applications with invented traffic. The test may look reasonable. The result may even pass.
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datadog

AI gateway best practices: Model routing, reliability, and budget controls for production agents

Jul 23, 2026 By Datadog In Datadog
Organizations are increasingly using multiple models to build AI agents in order to find the best balance of performance and cost for each agentic task and LLM call. As we discovered in the 2026 State of AI Engineering report, there isn’t currently a clear winner in terms of adoption among competing models and many organizations are keeping older models in flight despite frequent new releases.
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Komodor

5 Optimization Blockers You Didn't Know Were Inflating Your Cloud Bill

Jul 23, 2026 By Komodor In Komodor
Most cloud-native cost tools are built to find and address waste reactively. Underutilized nodes, oversized requests, and idle workloads are revealed in the utilization data, the fixes are well documented, and the initial savings these tools drive are very real. But what we’ve seen consistently across clusters is a different category of blocker, one that quietly prevents consolidation and strands capacity your autoscaler can never reach. They don’t surface in dashboards as obvious waste.
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Aiven

Aiven Acquires Flow AI to Bring Agent Infrastructure Closer to Production Data

Jul 23, 2026 By Oskari Saarenmaa | In Aiven
Helsinki, Finland — Aiven has acquired Flow AI, a company building infrastructure for production-grade analytical AI agents. The integration of Flow AI technology will accelerate Aiven's product roadmap and make it easier for customers to securely and scalably run production AI applications and agents next to their data.
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cloudzero

Best AI cost management tools [2026]

Jul 23, 2026 By Keith MacKenzie In CloudZero
The best AI cost management tools in 2026 are CloudZero (best overall for connecting AI and cloud spend to business outcomes), Langfuse (best open-source LLM tracker), Portkey (best LLM gateway with cost controls), Datadog LLM Observability (best for teams already on Datadog), and CAST AI (best for Kubernetes AI infrastructure). The right tool depends on whether your primary problem is token-level LLM visibility, cloud infrastructure spend, or understanding whether your AI is generating real ROI.
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cloudzero

GPT-5.6 pricing: Sol, Terra, and Luna costs

Jul 23, 2026 By Lyne Carolyne In CloudZero
GPT-5.6 pricing runs across three tiers, per million tokens. Sol costs $5 input / $30 output. Terra costs $2.50 / $15. Luna costs $1 / $6. All three share a 1.05 million token context window. The twist nobody priced in: OpenAI’s own system card admits Sol sometimes takes action nobody approved, then reports the job as done. For finance teams, that behavior is a governance issue worth understanding before engineering routes production traffic to it.
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cloudzero

The three questions every CFO should be asking about AI spend

Jul 23, 2026 By David Aponovich In CloudZero
Uber ran out of its entire 2026 AI budget by April. This didn’t happen because AI technology failed, but because the company had no way to connect what it spent to what it got. The COO described it on an earnings call: “It’s very hard to draw a line” between AI usage and consumer product outcomes. And with that one sentence, we have the CFO problem of 2026.
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cloudzero

Shipped: See what Claude Code actually costs

Jul 23, 2026 By Subash Karki In CloudZero
Your engineers are running Claude Code every day, and every prompt burns tokens you’re paying for. Until now, that spend was hard to see. It either sat invisible or landed in an untagged bucket you couldn’t break down. Claude Code already emits detailed telemetry for every interaction, so the data existed. You just had nowhere to send it that would turn it into a cost.
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pagerduty

3 Things IT Leaders Are Learning About AI-First Operations: Key Takeaways From PagerDuty on Tour 2026

Jul 23, 2026 By PagerDuty In PagerDuty
In December 2025, an AI coding agent at AWS suddenly decided to delete and rebuild an entire production environment, causing a 13-hour service disruption and a PR headache for Amazon. As rapid adoption of AI leads to more high-profile, revenue-impacting incidents, resilience has moved from a technical concern to a board-level financial risk.
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sentry

From 57 bugs to 1, thanks to Seer

Jul 23, 2026 By Dan Mindru In Sentry
I was at the dentist the other day, getting ready for my appointment. The waiting room was pompously decorated. Each chair seemed to be from a different, expensive Danish designer. As I realize I’m about to get charged through the nose, I get a notification from my beloved Mail app. ** ding ** Screenshot of GitHub email notification It’s a new Pull Request on GitHub. This one is different though. I have no idea where it came from!
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Kubex

Don't Trust the Diff: Making AI-Generated Code Reviewable And Maintainable

Jul 23, 2026 By Kubex In Densify
Coding agents changed implementation economics faster than they changed confidence. They let us produce more code, more quickly, but they did not make reviewers any better at understanding system-wide consequences. In our Kubernetes automation stack, that gap became impossible to ignore once AI started generating meaningful amounts of controller code.
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jfrog

Why Model Routing Backfires and How to Build Agents That Don't Burn Your Budget

Jul 23, 2026 By Shay Dahan In JFrog
Model routing promises to cut your AI agent spend by offloading routine tasks to cheaper models like Claude Haiku while reserving frontier models like Claude Sonnet for complex reasoning. In the right configuration, routing strategies can reduce inference costs by 40–85%. But if you implement routing incorrectly in a multi-turn agent, you can end up paying more than if you’d never routed at all. Here’s why and how to fix it.
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Catch AI Agent Failures Before They Ship | Harness AI Evals

Jul 23, 2026 By Harness In Harness
AI agent quality should not depend on manual checks. But for many teams shipping AI in production, agent failures are silent. The agent doesn't crash - it just gives confidently wrong answers, and your monitoring sees nothing wrong. Without automated guardrails, plausible-sounding wrong responses, hallucinations, and quality regressions reach customers before anyone notices.
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Guardrails for shipping with AI agents, feat. Luca Rossi of Refactoring.fm

Jul 23, 2026 By CircleCI In CircleCI
Code review has always been a time sink. AI just makes the dysfunction undeniable. Luca Rossi, founder of Refactoring.fm and builder of the open source tool Tolaria, has been running one of engineering's most-read newsletters for five years, with over 170,000 subscribers. He's also been doing what a lot of engineering leaders talk about but rarely do: building a real product with AI agents to pressure-test what's actually possible today.
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selector

The Near-Term Wins in AI for NetOps Rest on the Same Foundation

Jul 23, 2026 By Dallon Robinette In Selector
Walk into a network operations center this year and the useful AI is not running the place. It is doing three specific jobs, and doing them well: cutting an alert storm down to the one incident that matters, pointing at the likely cause, and deciding what deserves a human’s attention first. That is where AI in NetOps pays for itself right now. The part worth noticing is that all three jobs lean on the same thing.
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Dynamic MCP Server Demo | Connect Claude to Enterprise Automation in Minutes

Jul 23, 2026 By Resolve In Resolve
See how the new Dynamic MCP Server in Resolve Actions Pro 8.1 lets AI assistants like Claude discover and execute approved Resolve runbooks through the Model Context Protocol (MCP). Watch enterprise automation happen in real time with secure, auditable execution.
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Teneo

Why AI Governance Is Now the Biggest Challenge for Enterprise AI

Jul 23, 2026 By Teneo In Teneo
For the past couple of years, most conversations about AI in business have centered on adoption. Which tools should organizations deploy? Where can AI improve productivity? How quickly can it deliver value? Those questions still matter, but they are no longer the most difficult ones to answer. AI is now appearing across business applications, employee workflows, development environments, and customer-facing services.
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Your Prospect Data Is a Pipeline, and Nobody Is Monitoring It

Your Prospect Data Is a Pipeline, and Nobody Is Monitoring It

Jul 23, 2026 By OpsMatters In OpsMatters
Engineering teams have spent a decade learning that data has a shelf life. Metrics go stale. Caches drift. Pipelines break quietly and keep serving results that look plausible until someone checks the source. That is why observability exists as a discipline and not just a dashboard.
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How eDiscovery Review Strengthens Evidence Analysis for Legal Teams

How eDiscovery Review Strengthens Evidence Analysis for Legal Teams

Jul 23, 2026 By OpsMatters In OpsMatters
Legal evidence now lives across emails, chat exports, contracts, spreadsheets, shared drives, and metadata trails. For legal teams, the real challenge is not collecting documents; it is finding the material that can support, weaken, or reshape a case. A disciplined review process turns scattered information into organized evidence that attorneys can trust.
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cloudzero

AI ROI is not an engineering metric

Jul 22, 2026 By Brady Lenahan In CloudZero
I spend most of my week talking to companies about AI ROI. A few months ago, that was still a weirdly specific conversation. Now it’s everywhere. CloudZero spends a lot of time in that conversation, so I’m glad the market is talking about it. But the conversation tends to start, and stall, in the wrong place. There are two ideas I keep coming back to: That doesn’t mean developer productivity is fake. It’s very real.
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Sentry + GitHub Copilot Agents

Jul 22, 2026 By Sentry In Sentry
Seer, Sentry's agent debugger, analyzes your issues and finds the root cause. Now you can pass that analysis directly to a GitHub Copilot agent which picks up the context, generates a fix, and opens a pull request. The agent session and PR both live on GitHub, with a link back in Sentry for easy access. This video walks through how the integration works.
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lightrun

Why Internal Agents Must Be Rebuilt with Runtime Context

Jul 22, 2026 By Gidi Freud In Lightrun
As we entered 2026, enterprises raced to build internal AI engineering agents, automating incident response, code review, and support. The investment was real, but 88% of these pilots never reached production, and teams are now in rebuild mode, trying to understand why. Live runtime validation was the key architectural decision skipped in these v1 agents and it’s still missing from many v2 designs. Agents need to verify their reasoning against production before they act.
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kosli

Building a Control Framework for the AI SDLC

Jul 22, 2026 By Bruce Johnston In Kosli
Since November, Kosli’s own engineering team has been running a live experiment: what happens to code review when the thing generating the code - and increasingly, the thing reviewing it - is an AI, not a person. Alex Kantor, Kosli’s Director of Technology, walked through that experiment in this webinar: what broke, what it cost to fix, and what four “obvious” assumptions in a standard code review control turned out not to hold once you took the human out of the loop.
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3 Things Leaders Must Know About Scaling AI

Jul 22, 2026 By Ivanti In Ivanti
AI is moving faster than ever, but is your governance keeping up? In this video, Brooke Johnson, Ivanti’s Chief Legal Counsel and SVP of People and Security, breaks down the critical gap between AI adoption and responsible scaling. While speed is rarely the issue, trust and accountability are becoming major roadblocks for IT teams. We explore why nearly 70% of IT pros have witnessed AI hallucinations and how unclear ownership can stall even the most advanced AI initiatives.
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Why enterprise buyers choose Altamira for AI and custom software delivery

Why enterprise buyers choose Altamira for AI and custom software delivery

Jul 22, 2026 By OpsMatters In OpsMatters
Enterprise software buying has changed. A few years ago, most companies picked a vendor based on hourly rates and a portfolio page. The stakes are higher now, especially where AI is involved. Gartner predicted that at least 30% of generative AI projects would be abandoned after proof of concept by the end of 2025, mostly due to poor data quality, unclear business value, and rising costs. With failure rates like that, choosing an AI software development company is a risk decision, not a procurement task.
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The Best AI App Builders for Small Businesses in 2026

The Best AI App Builders for Small Businesses in 2026

Jul 22, 2026 By OpsMatters In OpsMatters
TL;DR: The best AI app builder for small businesses in 2026 is Jotform AI App Builder for end-to-end workflow automation. Lovable is best for customer-facing web apps, Softr for portals, Glide for field operations, Adalo for native mobile apps, and Base44 for custom AI web apps. Small businesses rarely need an app in the abstract. They need a faster way to handle bookings, orders, client intake, approvals, inspections, payments, documents, and follow-up.
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I'll have my AI agent call your AI agent: Battle for your digital hub

Jul 21, 2026 By Sumo Logic, Inc. In Sumo Logic
On this episode of Masters of Data, we unpack what it actually means to expect AI to be the primary interface for everything we do. We dig into the pull toward centralizing work in a single hub like Claude versus staying spread across specialized tools like Slack, Asana and Zoom, and where the line sits between helpful automation and letting an agent speak on your behalf. We also get into the "chief of staff" agent workflow for daily roundups and why specialized, best-of-breed tools aren't going anywhere, even as hubs get smarter.
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hyperview

Actionable Intelligence, Not Artificial Intelligence: What AI in Data Center Management Actually Requires

Jul 21, 2026 By Jad Jebara In Hyperview
“AI-powered” has become a marketing label applied to almost any data center software feature. A more useful and precise term is actionable intelligence — a four-level maturity model (descriptive, diagnostic, predictive/prescriptive, and cognitive) that shows whether a platform’s AI claims are backed by real data infrastructure or just a chatbot layered on top of an incomplete system.
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Alloy Software

AI-Assisted Documentation Search Goes Conversational

Jul 21, 2026 By Anna Markova In Alloy Software
Conversational AI has arrived in Alloy Software documentation, making it easier to find the exact answers you need. Ask a question, follow up naturally, and refine the response until you reach the right instructions or product details, without starting over or digging through pages. The redesigned experience keeps the conversation in context and lets you go as deep as you need.
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Cloud 66

Security at Scale: What Changes When Everyone Can Deploy using AI

Jul 21, 2026 By Kelley Schultz In Cloud 66
In our first series post, The New Software Creator, we mapped out a structural shift in the industry: AI is turning non-technical team members into creators of software. In our second post, When Anyone Can Build Software, Deployment Governance Is What Keeps It Safe, we argued that deployment is the single control layer that can secure this explosion of output without choking innovation.
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Your AI agents are lost: give them a graph

Jul 21, 2026 By Rootly In Rootly
The biggest limitation facing enterprise AI agents may not be the model. It may be the context surrounding it. Anthony Alcaraz, Senior AI/ML Portfolio Growth Manager at AWS and co-author of O'Reilly's *Agentic GraphRAG*, joins Humans of Reliability to explain why reliable agents need more than a vector database and a large context window. They need structured knowledge they can navigate, memory they can prune, constraints they can follow, and feedback loops that help them improve.
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harness

Introducing AI Agent Deployment in Harness Continuous Delivery | Harness Blog

Jul 21, 2026 By Akshit Madan In Harness
‍Teams building agents have converged on something that looks a lot like the software development lifecycle, but reshaped around a system whose output isn't deterministic: prototype an agent against a framework, evaluate it against a dataset of expected behavior, deploy it somewhere real, observe how it behaves against live traffic, and feed what you learn back into the next prototype. Call it the agent development lifecycle (Agent DLC).
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harness

Introducing Harness AgentTrace: An Observability and Guardrail Framework for AI Agents | Harness Blog

Jul 21, 2026 By Sunil Gattupalle In Harness
AI agents fail differently from the software we spent the last two decades learning to monitor. We hear some version of the same story from teams shipping agents to production: an agent starts producing wrong answers. Not obviously broken: confident, well-formatted, plausible wrong. The logs are clean, latency looks healthy, and error rates sit at zero. Nothing flags a problem. A user eventually does.
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hyperping

MCP for SLA Monitoring: Uptime, MTTR & MTTA

Jul 21, 2026 By Leo Baecker In Hyperping
MCP for SLA monitoring gives an AI agent direct access to measured uptime, mean time to resolve (MTTR), mean time to acknowledge (MTTA), outages, and reliability risks. With Hyperping, you can ask Claude, Cursor, Codex, or another MCP client for an SLA report and get an answer based on your live monitoring data instead of copying numbers between dashboards. The distinction between monitoring data and SLA compliance matters. Hyperping measures availability and incident response.
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ribbon

Optical Freedom in the Age of AI: Why Thin Transponders Are Reshaping Optical Network Design

Jul 21, 2026 By Mitch Simcoe In Ribbon
AI is driving the next wave of digital transformation, but it is also creating an unexpected challenge for network operators: optical capacity is becoming a strategic bottleneck. The same AI boom fueling billions of dollars in data center investment is placing unprecedented demand on optical networking infrastructure.
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Introducing Harness Agent DLC: Extending your SDLC to AI Agents

Jul 21, 2026 By Harness In Harness
Harness Agent DLC: Ship AI Agents to Production Safely Building an AI agent is easy. Getting one into production safely is where teams get stuck. Harness Agent DLC extends the software delivery lifecycle to AI agents, giving teams a clear path to evaluate, deploy, secure, observe, and optimize agents in production. Learn more: Because agents dynamically choose their own tools, APIs, and actions, their behavior can change every time they run. Harness Agent DLC gives engineering teams the controls needed to move beyond experiments and operate agents safely at scale.
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lightrun

SDLC Phases and the Reliability Gap AI Can't Close

Jul 21, 2026 By Lightrun Team In Lightrun
Decisions in each SDLC phase from planning to design, development, testing, deployment, and maintenance are made without sight of live production behavior. AI coding agents are widening that visibility gap faster, working faster than human engineers ever could. This piece maps exactly how this gap presents at each phase, and the harm that this brings.
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AI's Role in Enhancing Digital Commerce Operations

AI's Role in Enhancing Digital Commerce Operations

Jul 21, 2026 By OpsMatters In OpsMatters
Artificial intelligence is quickly becoming a must-have for digital businesses, not just a nice-to-have. For companies looking to sharpen their operations, AI offers powerful ways to predict what's next, smooth out customer interactions, and keep transactions safe. It's not about replacing people, but giving them better tools. This lets teams focus on big-picture strategy while AI crunches data and automates tasks. This shift is changing what's possible in terms of how efficient a business can be, how happy its customers are, and how much it can grow.
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How AI Tools Are Reshaping Knowledge Work

How AI Tools Are Reshaping Knowledge Work

Jul 21, 2026 By OpsMatters In OpsMatters
Knowledge work has always meant sitting with information, making sense of it, and turning it into something useful. That could be a report, a lesson plan, a research paper, or a business strategy. For a long time, this process depended almost entirely on human effort. You read, you took notes, you organized your thoughts, and slowly you built understanding. Today, that process looks different.
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manageengine

5 ways agentic AI in ITOps will close the gap between alerts and action

Jul 20, 2026 By Ajay In ManageEngine
Agentic AI in ITOps has emerged as a practical way to go beyond just detecting incidents. Modern IT teams have invested heavily in observability, yet the gap between detecting an issue and resolving it continues to widen. Three major challenges are driving this shift: This is where agentic AI makes a difference.
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statusgator

Claude outage on July 17, 2026: what happened and how StatusGator caught it early

Jul 20, 2026 By Andy Libby In StatusGator
Claude had a global outage on July 17, 2026, driven by “529 Overloaded” server errors that hit the API, Claude Code, the web app, and the desktop app. It lasted about 1 hour and 32 minutes. StatusGator detected it and sent an Early Warning Signal at 14:30 UTC, 27 minutes before Anthropic acknowledged it at 14:57 UTC.
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iOPEX

The Two-Clock Trap: A CRO's Diagnosis of Why Enterprise AI Fails at the Sourcing Table

Jul 20, 2026 By Dharmesh Mistry , Chief Revenue Officer In iOPEX
Every AI engagement runs on two clocks, and they no longer agree. The first is the intelligence clock, and it runs fast. The world it keeps time with re-renders every quarter. Models improve, inference costs fall, automation tightens, and the cost of producing a unit of work keeps dropping. This is the clock an enterprise believes it is buying when it invests in AI. The second is the contract clock, and it stopped years ago.
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appsignal

Why AI-Generated Code Needs Monitoring More Than Handwritten Code

Jul 20, 2026 By Dejan Lukić In AppSignal
Like it or not, vibe coding is here to stay. It’s too easy to just go away. Maybe if the per token cost rises too much at some point that it becomes cheaper to hire a junior… But until then, you’d better get used to it. For now, tools like Cursor, Copilot, and Claude let developers (and plenty of non-devs) ship full-stack apps faster than a junior is able to completely grasp the concept of the app they’re working on. And that’s pretty neat.
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tidal

The True ROI of Cloud Migration: Modernization, and AI Unlock

Jul 20, 2026 By David Colebatch In Tidal
For years, the cloud migration business case was framed around one comparison: “Will AWS be cheaper than our data center?” That question still matters, but it is no longer where the value is. The 2017-2024 wave of mass migration is largely complete. Most enterprise workloads are already in the cloud - often in a lift-and-shift state: oversized instances, commercial-OS BYOL, on-prem-shaped network designs, and legacy frameworks that block the next step.
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motadata

What Is LLM Observability? A Complete Guide

Jul 20, 2026 By Ramya Shah In Motadata
If you run LLM features in production, your most dangerous failures are the ones your monitoring never flags. Your LLM feature passed every test, and the demo went great. Three weeks after launch, a support ticket lands: the chatbot quoted a refund policy that does not exist. The dashboards are all green, and the same prompt answers correctly when you retry it. This is the blind spot LLM observability exists to close. Your existing tools saw the request come back fast with a clean status code.
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cloudzero

Shipped: Take your AI cost table straight into your own reports

Jul 20, 2026 By Kaitlin Woo In CloudZero
A design partner told us the AI Explorer table needed a way to get data out so it could be saved and shared elsewhere. Now you export the whole view in one click, cost, tokens, cache, and model count all included. The values come through as clean numbers, not text you have to scrub. It’s the same pattern as Explorer, so there’s nothing new to learn.
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nexthink

Enterprise AI Governance Made Simple with Nexthink's AI Activation Hub

Jul 20, 2026 By Shawn Lazarus In Nexthink
Over the past year, organizations have embraced AI at an extraordinary pace, and Nexthink AI Activation Hub powered by AI Drive has helped customers make sense of that transformation by helping organizations discover the growing wave of AI tools entering the workplace, rapidly triage and govern them, accelerate adoption of approved AI solutions, and measure the impact of AI across the enterprise.
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How AI Can Help Identify Business Investment Opportunities

How AI Can Help Identify Business Investment Opportunities

Jul 20, 2026 By OpsMatters In OpsMatters
Artificial intelligence is quickly moving from a futuristic concept to a practical tool for modern business. For entrepreneurs and investors, AI offers a powerful way to cut through the noise and identify genuine investment opportunities. Instead of relying solely on intuition and manual research, you can now use AI to analyze complex data sets, predict market shifts, and pinpoint ventures with the highest potential for success.
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From Estimate to Invoice: How AI Is Streamlining Contractor Workflows

From Estimate to Invoice: How AI Is Streamlining Contractor Workflows

Jul 20, 2026 By OpsMatters In OpsMatters
Artificial intelligence is rapidly becoming one of the most valuable operational tools available to contractors. While much of the public conversation focuses on AI generating text or images, construction companies are discovering far more practical uses. From the moment a homeowner requests an estimate until the final invoice is sent, AI is helping contractors reduce administrative work, improve communication, and keep projects moving more efficiently.
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Why Legitimate AI and Human Users are Getting Elbowed Out of Your Infrastructure

Why Legitimate AI and Human Users are Getting Elbowed Out of Your Infrastructure

Jul 20, 2026 By OpsMatters In OpsMatters
The internet has always been a bit of a noisy, crowded place, but lately it feels like a never-ending brawl in the aisles of some superstore that sells everything from penny candy to luxury jets. That is essentially what running an enterprise website or API endpoint feels like in 2026: brawl management. Automated scripts are now advanced, highly coordinated AI agents acting on behalf of competitors, scrapers, search engines, and sometimes actual buyers. They make eCommerce chaotic and urgent. It makes customers frustrated and fickle.
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Why Everyday Technology Is Becoming More Situational

Why Everyday Technology Is Becoming More Situational

Jul 20, 2026 By OpsMatters In OpsMatters
Your phone does not treat every moment the same anymore. It knows when you are driving, sleeping, walking, shopping, searching, working, or moving through an unfamiliar place. Everyday technology is no longer built only around buttons and commands. It is being shaped around context. This is the real change behind modern AI, smart devices, apps, vehicles, and digital services. They do not only ask, "What did the user click?" They ask, "What is happening right now, and what should happen next?"
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The Growing Link Between Smart Tech and Real-World Accountability

The Growing Link Between Smart Tech and Real-World Accountability

Jul 20, 2026 By OpsMatters In OpsMatters
Smart devices are no longer just helping people unlock doors, track steps, pay bills, manage work, or receive alerts. They are creating records. A doorbell camera can confirm who entered a property. A smartwatch can show when movement suddenly stopped. A workplace app can reveal who approved a task. A delivery platform can prove when an order changed hands. A cloud dashboard can show who accessed a file. Smart technology is turning ordinary actions into traceable events, and that is changing how accountability works in daily life.
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From Evidence to Outcome: Technology's Impact on Injury Claims

From Evidence to Outcome: Technology's Impact on Injury Claims

Jul 20, 2026 By OpsMatters In OpsMatters
Injury claims are no longer built only on statements, photos, and medical bills. A single claim can now involve vehicle data, phone records, surveillance footage, digital medical files, telematics, billing systems, and AI-assisted document review. That shift matters because technology does not simply add more evidence. It changes how fault is proved, how injuries are connected to an event, how damages are calculated, and how quickly a claim can move from dispute to outcome.
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manageengine

Five worthy reads: Brains or bots-are we forgetting how to think?

Jul 17, 2026 By Dharani Senthilkumar In ManageEngine
Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. This week, we are exploring how prolonged dependence on AI could influence human beings' neural pathways, cognitive habits, and the behavioral changes that follows. As children, many of us would have watched the juggler at a circus in amazement. One ball became two, then three, and several more since it was a cumulative act.
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statusgator

Cursor outage on July 16, 2026: high load errors worldwide and how to keep working

Jul 17, 2026 By Colin Bartlett In StatusGator
Cursor was hit by a global “high demand” outage on July 16, 2026, returning ERROR_RESOURCE_EXHAUSTED errors that blocked AI requests for just over two hours. StatusGator caught it early, sending an Early Warning Signal at 06:49 UTC, 12 minutes before Cursor acknowledged the incident at 07:01 UTC. Here is the full picture, including the workaround that kept many users coding.
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Langflow Observability with OpenTelemetry and SigNoz

Jul 17, 2026 By SigNoz - Open Source Observability Platform In SigNoz
Learn how to implement end to end monitoring and observability for Langflow using OpenTelemetry and SigNoz. In this video, we walk through instrumenting Langflow workflows, collecting traces, metrics, and logs, and visualizing everything in SigNoz to gain real time visibility into flow execution, LLM requests, tool calls, token usage, latency, failures, and performance bottlenecks. Langflow ships with built in OpenTelemetry support, making it easy to export telemetry to SigNoz with minimal configuration.
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upsun

Bridging the AI context gap: Why your IDE needs a platform contract

Jul 17, 2026 By Upsun In Upsun
Hosting an MCP (Model Context Protocol) server on Upsun lets AI IDEs like Cursor, Codex, Claude Code and Windsurf reach real infrastructure context (database schemas, service logs, environment variables), closing the gap between local coding assistants and your cloud environment.
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datadog

Answer any cost question faster with the Cloud Cost skill in Bits Chat

Jul 17, 2026 By Datadog In Datadog
Managing cloud, AI, and SaaS costs means answering a steady stream of questions from finance, leadership, and engineering teams. What changed? Which team owns the spend? Was an increase expected? Are we still on track against the budget? When each answer requires moving between dashboards, filtering cost data by team or service, or manually correlating billing data with observability data, it can slow down investigations while costs continue to rise.
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Trust, Resilience & AI: A Customer Panel with TD Bank & New York Life

Jul 17, 2026 By PagerDuty Inc. In PagerDuty
What does it really take to be "the calm in the storm" during a major incident? In this candid panel from PagerDuty on Tour, Chris Conklin (Technology Executive AIOPs, TD Bank) and Sam Brinley (CVP Enterprise Cloud Solution Architect & Engineer at New York Life) sit down with PagerDuty to talk through two decades of evolution in IT operations – from the "Wild West" of early network management to today's push into AI and agentic operations.
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AI-Powered Ransomware Is Here: How Agentic AI Is Changing Cybersecurity

Jul 17, 2026 By Resolve In Resolve
AI-powered ransomware is becoming a reality. Researchers recently demonstrated autonomous AI agents that can scout networks, steal credentials, and accelerate ransomware attacks. In this 60-second Zero Ticket Minute, learn what this means for cybersecurity, IT operations, and the future of agentic AI. Can AI also help stop these attacks? Watch to find out.
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New AI Features in Playwright (Live-Webinar)

Jul 17, 2026 By Checkly In Checkly
An AI agent that can't open a browser is just guessing. Stefan from Checkly shows how giving AI coding agents a real browser via Playwright enables reliable end-to-end test generation and debugging, closing the quality gap created by faster, AI-driven shipping. The session compares Playwright MCP vs the Playwright CLI for agent workflows, showing that thanks to MCP spec changes, lazy tool loading, and skills, the two are now effectively just different interfaces to the same tool, with no real token advantage either way.
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How to use Grafana Assistant with the AWS CloudWatch data source

Jul 17, 2026 By Grafana In Grafana
Grafana Assistant meets AWS CloudWatch! In this video, Staff Software Engineer Ivana Huckova shows how to use Grafana Assistant, the AI agent built into Grafana Cloud, with the Amazon CloudWatch data source. Watch her query CloudWatch metrics and logs in plain language, build dashboards in seconds, and troubleshoot AWS resources — no query syntax required.
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c1

Is Your Network Infrastructure Ready for Agentic AI?

Jul 17, 2026 By Mike Lary In C1
Artificial intelligence is evolving faster than most organizations anticipated. Just a few years ago, enterprises were experimenting with machine learning models and predictive analytics. Then came generative AI, enabling organizations to create content, accelerate workflows, and unlock new productivity gains. Today, we're entering the next phase: agentic AI.
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How Business Process Workflow Automation Reduces Human Errors

How Business Process Workflow Automation Reduces Human Errors

Jul 17, 2026 By OpsMatters In OpsMatters
Human error is one of the most expensive problems businesses deal with every single day. From data entry mistakes and missed approvals to incorrect invoices and compliance oversights, the cost of getting things wrong adds up fast. The good news is that business process workflow automation is changing how organizations manage their operations, and reducing human error is one of the most compelling reasons to adopt it. When repetitive, rule based tasks are handed off to automated systems, the margin for error shrinks dramatically and the quality of output improves across the board.
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manageengine

Top Tips: Stay creative in the age of AI

Jul 16, 2026 By Priyanka Gs In ManageEngine
Top Tips is a weekly column where we examine the trends transforming the workplace. This week, we're exploring the relationship between AI and creativity, why convenience shouldn't come at the cost of original thinking, and practical ways to keep your creative edge sharp. Have you ever heard of the prefrontal cortex? It's one of the most fascinating parts of the human brain.
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Harness + Cursor IDE: Accelerating Safe Software Delivery with AI Agents

Jul 16, 2026 By Harness In Harness
While AI coding assistants help developers write code faster than ever, the traditional manual workflows for delivery, security, governance, and production readiness often create a bottleneck. In this demo, see how Cursor and Harness bridge this gap by turning AI-generated code into a safe, governed, and production-ready software delivery lifecycle right from your IDE.
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You're already using AI without realizing it

Jul 16, 2026 By Harness In Harness
You're already using AI without even thinking about it. That's the realization that kicks off this ShipTalk moment: Apple Maps quietly using on-device machine learning to learn your routes and driving habits — complete trust, zero thought. Which raises the real question: why aren't we there yet with AI in software delivery? The answer comes down to one word: guardrails. Consumer AI earned invisible trust. Shipping software hasn't — not until the guardrails catch up.
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honeycomb

AI Amplifies Your Existing Practices: Lessons from Our Shift to an AI-First Strategy

Jul 16, 2026 By Liz Fong-Jones In Honeycomb
In this two-part blog series, I give a detailed report-out on how our Honeycomb engineering team 2.5x-ed our throughput using AI without breaking everything or lowering our standards for quality. Part 1 explains how we did it and shows data about how that ramp-up happened. In this blog, I share what we learned. The “platform engineering” frame and the “autonomy, ownership, feedback loops” frame are the same frame, spoken in two different vocabularies.
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harness

Identity and Permissions for AI Worker Agents in Harness | Harness Blog

Jul 16, 2026 By Shivansh Srivastava In Harness
When we launched Autonomous Worker Agents, governance inherited, not integrated, was the core promise: agents run inside the same pipelines, and inherit the same RBAC, policy, and audit trails already governing production, rather than getting security bolted on after the fact.
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From OpenAPI to MCP: A Practical Access Layer for AI Clients

From OpenAPI to MCP: A Practical Access Layer for AI Clients

Jul 16, 2026 By OpsMatters In OpsMatters
Connecting an AI client to a REST API looks simple until the first real production requirement appears. The client needs to discover operations, understand request schemas, authenticate safely, respect write restrictions, and handle credentials without copying them into every desktop configuration. A thin wrapper around HTTP rarely solves all of those problems.
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RK3588 Explained: Why This Rockchip Chip Powers So Many AI and Edge Devices

RK3588 Explained: Why This Rockchip Chip Powers So Many AI and Edge Devices

Jul 16, 2026 By OpsMatters In OpsMatters
The Rockchip RK3588 has quietly become one of the most widely adopted processors in single-board computers, mini PCs, and edge AI hardware - and it's not hard to see why once you look at what's packed into it. As reported by KiwiPi, the RK3588 is a system-on-chip that combines CPU, GPU, and a dedicated AI processing unit on a single die, letting manufacturers build compact devices without sacrificing performance across multiple workloads.
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Free AI Photo Editor Review: PhotoGenerator AI in 2026

Free AI Photo Editor Review: PhotoGenerator AI in 2026

Jul 16, 2026 By OpsMatters In OpsMatters
Photogenerator is a smart online tool that lets you create stunning, high-resolution photos using artificial intelligence. With this platform, you can describe any idea in words-like a product photo, a portrait, or concept art-and Photogenerator will turn your description into a polished image. It's super easy to use, and you don't need any special skills to start making impressive pictures.
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Dynamic MCP Server Demo | Connect AI Agents to Enterprise Automation with Resolve Actions Pro 8.1

Jul 15, 2026 By Resolve In Resolve
Learn how to create and deploy a Dynamic MCP Server in Resolve Actions Pro 8.1 and securely expose enterprise automation to AI assistants using the Model Context Protocol (MCP). In this walkthrough, you'll see how to configure an MCP server, publish automation runbooks, connect to Claude Desktop, and execute enterprise workflows directly from an AI assistant. With Dynamic MCP Servers, organizations can make existing automation instantly accessible to AI agents without rebuilding workflows.
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AI vs. AI: from alert fatigue to agentic cybersecurity

Jul 15, 2026 By Rootly In Rootly
AI is transforming cybersecurity on both sides of the battlefield. Attackers can now launch highly personalized phishing campaigns at scale and build malware capable of making autonomous decisions. At the same time, security teams are using AI agents to investigate alerts, reduce noise, and respond to threats faster. In this episode of Humans of Reliability, we speak with Nir Soudry, Head of R&D at 7AI, about the shift from alert fatigue to agentic cybersecurity.
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nexthink

The AI Factor You're Ignoring: Employee Behavior

Jul 15, 2026 By Shawn Lazarus In Nexthink
One of the most important realizations emerging across enterprise AI governance discussions is that most risky AI behavior is not malicious. Employees are typically trying to work faster. They are trying to summarize documents, accelerate research, draft communications, analyze spreadsheets, or automate repetitive tasks. In many cases, employees may not fully understand how AI providers handle uploaded information, what data policies apply, or where organizational compliance boundaries actually exist.
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Building a Website with AI: What You Should Know First

Building a Website with AI: What You Should Know First

Jul 15, 2026 By OpsMatters In OpsMatters
The age of artificial intelligence is here, and it has already made many types of otherwise time-consuming tasks that much easier. For some, that includes building a website. Building a website from scratch takes some serious time (and talent, of course). While AI can't take all the creativity out of your hands, it can act as a tool to help you achieve the website's end result that much faster. Of course, overreliance is not the answer, though. So, to get it right, here's what you should know before you start building a website alongside AI.
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jfrog

Managing AI Agent Primitives Like Real Software Packages with APM and JFrog

Jul 14, 2026 By Yonatan Arbel In JFrog
AI agents are part of the modern development workflow. They write code, review pull requests, generate tests, call tools, interact with MCP servers, and help developers move faster. But behind every useful agent, there is something just as important as the model itself: the context that tells the agent how to behave. That context can include skills, prompts, instructions, hooks, commands, scripts, references, and MCP server definitions. In a small project, managing these primitives is pretty simple.
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Create uptime monitors by asking Claude Code (MCP demo)

Jul 14, 2026 By Monitive In Monitive
Create and manage uptime monitors without leaving your editor. In this demo I connect Claude Code to UptimeMonitoring's MCP server with one command, then just ask it to monitor six sites. It creates all six, runs the first check, and reports back, then shows the live monitors in the dashboard. What UptimeMonitoring is: MCP is a thin layer over a normal REST API; if you'd rather curl + cron, that path is first-class.
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cloudzero

Enterprises are making their biggest AI bets blind

Jul 14, 2026 By Scott Castle In CloudZero
AI cost observability is the practice of measuring, attributing, and analyzing AI workload costs at the request, model, and workflow level in real time. It connects cloud infrastructure spend, inference and token costs, and business attribution (cost per feature, team, customer, or product) so engineering, finance, and product teams can see where AI spend goes and whether it creates value. On July 14, IBM had its worst trading day since 1987.
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cloudzero

What is AI cost observability? A guide to tracking LLM and AI spend

Jul 14, 2026 By Keith MacKenzie In CloudZero
AI cost observability is the practice of measuring, attributing, and analyzing AI workload costs at the request, model, and workflow level in real time. It connects cloud infrastructure spend, inference and token costs, and business attribution (cost per feature, team, customer, or product) so engineering, finance, and product teams can see where AI spend goes and whether it creates value.
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Why the U.S. Locked Down Fable and Mythos: AI, National Security, and the Workforce Squeeze

Jul 14, 2026 By Harness In Harness
The U.S. just barred foreign nationals from accessing two advanced AI models — Fable and Mythos — citing national security. Around the same time, the Five Eyes intelligence alliance warned that AI-enabled cyberattacks are "months, not years" away. In Season 5 of ShipTalk, host Adam and co-host Martin dig into whether that warning is already overdue — and what it means for the people actually defending software.
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pulsant

Why colocation is becoming the foundation of sovereign AI

Jul 14, 2026 By Mark Lewis In Pulsant
The last few years have seen AI conversations dominated by the need for investment in hyperscale infrastructure as firms race to build ever larger training models. But as those conversations evolve, the emphasis is shifting to the next phase of AI adoption, focusing on the scaling of use cases and real-world value. In line with this shift, organisations are looking beyond where AI is trained to the specifics of where it is actually used.
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AI is Exposing Observability's Dirty Secret

Jul 14, 2026 By Speedscale In Speedscale
The 3 pillars of observability are breaking. For years, dev teams relied on Logs, Metrics, and Traces to know when something went wrong. But now? AI agents are writing, deploying, and changing code in real-time. When an AI hallucination pushes a bug to production, standard monitoring sees nothing wrong.To survive the AI era, we need a 4th Pillar of Observability. Watch to find out what it is and why the old way of monitoring just became obsolete.
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grafana

Stop switching tools to find answers: Grafana Assistant now works across 30+ data sources

Jul 14, 2026 By Karina Munoz Villanueva In Grafana
When you're the on-call engineer and something breaks, you can quickly find yourself deep in a series of tools you don't regularly use—switching tabs, copying query results, and manually stitching together a picture of what's happening and why. People are increasingly turning to AI to get around this, but the results can be a mixed bag.
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mezmo

An SRE agent for production

Jul 14, 2026 By Mezmo In Mezmo
AI has changed how software gets built. It hasn't changed how software gets run. Most of the AI money in software has gone into the IDE: code generation, copilots, developer assistants, faster pull requests. That work matters. But writing software is one slice of the lifecycle. The harder problem, and the more expensive one, is running that software in production. Production is where systems fail in ways nobody predicted. Incidents don't stay inside one service.
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mezmo

We built an SRE bot on AURA. Here's what we learned.

Jul 14, 2026 By Mezmo In Mezmo
PagerDuty fires. You open the incident. Title, timestamp, nothing else. Whatever context exists is in someone's head, in a Slack thread from two weeks ago, or in a runbook nobody has touched since the last reorg. We got tired of that. So we put an AURA agent behind a Slack bot and pointed it at our own production environment.
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harness

Poisoning The Pipeline: How The Mastra AI Ecosystem Was Poisoned At The Registry Level | Harness Blog

Jul 14, 2026 By Roshan Piyush In Harness
The open-source landscape has witnessed another highly automated, ecosystem-level subversion. On June 17, 2026, a critical software supply chain attack struck the Mastra AI framework - a popular open-source TypeScript ecosystem used widely to build AI agents, workflows and RAG pipelines. By exploiting a compromised contributor account, threat actors successfully mass-published 144 malicious packages under the official @mastra npm scope.
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harness

AI Is Writing More Code Than Ever. Your Release Process Hasn't Kept Up. | Harness Blog

Jul 14, 2026 By Aaron Newcomb In Harness
A new report from LeadDev and Harness makes one thing clear: AI coding tools have fundamentally changed how much code organizations are producing. What has not changed nearly fast enough is how that code gets released. The State of AI-Driven Software Releases 2026 report, based on responses from 500424 engineers across industries and company sizes, puts real numbers behind a problem that engineering leaders have been feeling for a while. AI is accelerating the code creation side of the SDLC.
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logicmonitor

Unlock AIOps with Red Hat Ansible Automation Platform and LogicMonitor Edwin AI

Jul 14, 2026 By Margo Poda In LogicMonitor
Edwin AI and Red Hat Ansible Automation Platform help ITOps teams move from correlated alerts and root cause analysis to governed, auditable remediation. When an outage starts, the first alert is only the first artifact. The harder work follows: grouping related signals, separating symptoms from cause, identifying the affected service, and deciding whether the next action is safe to run.
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harness

How We Secured AI Worker Agents in Harness | Harness Blog

Jul 13, 2026 By Shivansh Srivastava In Harness
When we launched Autonomous Worker Agents, the message we led with was simple: governance is inherited, not integrated. Agents don't get security bolted on after the fact. They inherit the OPA policies, RBAC, and audit trails already running your production pipelines. This post is about the layer underneath that promise: isolation. We let an Autonomous Worker Agent run shell commands and call APIs inside our pipelines.
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logz.io

Part II: Inside Alert AI Analysis: From a Single-Agent Prompt to an Agent Harness

Jul 13, 2026 By Kevin Klein In logz.io
TL;DR: This is the engineering companion to our announcement post, Upgraded Alert AI Analysis: Automated Incident Investigation, read that one for what the new generation does for your team; read on for how it works under the hood. Interested in hearing more? Book a demo to see the Alert AI Analysis Agent live. Root cause analysis is one of the harshest tests you can give an AI.
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logz.io

Upgraded Alert AI Analysis: Automated Incident Investigation

Jul 13, 2026 By David Lotan Bolotnikoff In logz.io
TL;DR: OrionIQ has launched the next generation of its Alert AI Analysis agent within the Open 360 AI platform, designed to automate and accelerate incident investigation. Key features of this evolution include: Agent-Based Investigation: Instead of relying on a single prompt, the system coordinates specialized AI agents to correlate data across diverse sources like logs, metrics, deployments, and tickets.
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atatus

Introducing AI-Powered Incident Correlation & Root Cause Detection

Jul 13, 2026 By Mohana Ayeswariya J In Atatus
An API latency spike hits your checkout service, and within ninety seconds your on-call phone won't stop buzzing. A CPU threshold breaches. A database connection pool exhausts. A pod restarts. An error rate crosses 5% on a downstream service. Six engineers get paged inside four minutes. Forty alerts. Seven services. One incident. Every monitoring tool in the stack is doing exactly what it was configured to do, telling you that something is wrong.
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redgate

99% of database professionals are seeing AI benefits. So why are the security challenges increasing?

Jul 13, 2026 By Sarah Lahiff In Redgate
The numbers from the 2026 State of the Database Landscape: AI Edition are striking. 99% percent of respondents using AI report at least one measurable benefit for their database work. Automation is up, performance is improving, and three-quarters report significant cost savings. By almost any measure, AI is delivering. However, sitting alongside that near-universal positivity in the same dataset, security and privacy concerns have climbed to 64%. Regulatory compliance anxiety has risen to 40%.
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IT on the 4th of July? Not with AI. | Zero Ticket Minute

Jul 13, 2026 By Resolve In Resolve
What if your IT team could enjoy the Fourth of July without getting interrupted by password resets, VPN issues, and routine service requests? In this week's Zero Ticket Minute, see how agentic AI and automation help eliminate repetitive tickets so IT teams can enjoy the holiday while work gets done.
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What Separates a Serious AI Data Collection Company From One That Just Says It Is

What Separates a Serious AI Data Collection Company From One That Just Says It Is

Jul 12, 2026 By OpsMatters In OpsMatters
Most AI projects don't fail at the model architecture stage. They don't fail at deployment. They fail earlier and more quietly - at the point where the data that was supposed to train the model turns out to be insufficient, inconsistent, or simply wrong for the task it was collected to serve. Choosing the right ai data collection companies is, in this sense, one of the highest-leverage decisions an organization makes when building AI capability - and one of the decisions most commonly made on the wrong criteria.
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scout

Monitoring AI Applications in 2026: What You Actually Need

Jul 11, 2026 By Sarah Morgan In Scout
Last updated: July 2026. Your AI feature works in development. It demos well. Then it hits production and you discover three problems your test suite did not catch: the LLM hallucinates product names that do not exist, the RAG retrieval step adds 4 seconds to every request, and your OpenAI bill is 3x what you budgeted because one prompt template is burning tokens on context that does not help the output. Traditional APM would have caught the latency.
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scout

Your AI Coding Agent Is Flying Blind in Production

Jul 11, 2026 By Sarah Morgan In Scout
Your AI coding agent can refactor a module, write tests, and open a PR. It can read your codebase, understand your patterns, and suggest changes that follow your conventions. What it cannot do, unless you set it up, is see what is actually happening in production. That is a problem. The agent that writes the code should have access to the errors, traces, and performance data that code generates once it ships. Without production context, your agent is writing fixes based on the code alone.
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AI Is Reshaping the Tech Industry in 2026: What Consumers and Businesses Need to Know

AI Is Reshaping the Tech Industry in 2026: What Consumers and Businesses Need to Know

Jul 11, 2026 By OpsMatters In OpsMatters
Artificial intelligence has evolved from an emerging technology into one of the biggest drivers of innovation across the global technology industry. In 2026, AI is influencing everything from smartphones and laptops to cybersecurity, cloud computing, enterprise software, and digital productivity tools. Companies worldwide are investing heavily in AI powered products that improve efficiency, automate repetitive tasks, and deliver more personalized user experiences.
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The AI Software Engineering Revolution, feat. Anthropic | Big Tent S3E9

Jul 10, 2026 By Grafana In Grafana
In this episode of Grafana's Big Tent, hosts Mat Ryer (Senior Director of AI, Grafana Labs) and Tom Wilkie (CTO, Grafana Labs) sit down with Eric Burns, Field Executive Architect at Anthropic, to talk about building trust between tech and business execs, why Anthropic bet early on running across every major cloud, and what it was like watching large language models go from "interesting" to "obviously the future" in real time.
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datadog

Making agentic token costs visible in production

Jul 10, 2026 By Datadog In Datadog
In some organizations, high token counts have become a proxy for productivity. Some engineering teams are being pushed to max out context windows and wire in sprawling tool sets. More tokens can mean better agent reasoning and richer context during development, but token costs compound in production. Tokens accumulate across sessions, users, and tool calls in ways that are easy to overlook. Datadog’s 2026 State of AI Engineering report quantifies the scale of this problem.
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Aiven

OpenSearch 3.6: Agentic Applications Meet Long-Term Support

Jul 10, 2026 By Andrei Trepet | In Aiven
TL;DR OpenSearch 3.6 makes agentic search production-ready, with the AI-powered Launchpad provisioning full search apps in minutes and faster default vector search, and it's the first LTS release, bringing 18+ months of guaranteed support, SBOMs, and an upstream-first commitment (every fix goes back to the main project) so teams get fast-moving open source and a stable, supported platform at once.
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InvGate

How to Use Your Knowledge Base to Increase AI Chatbot Deflection

Jul 10, 2026 By Natalí Valle In InvGate
Ticket deflection is the metric IT leaders point to when they talk about AI chatbot ROI, and the knowledge base is the part of the equation that determines whether that number moves. A chatbot can run natural language processing well and still deflect almost nothing if the content behind it is thin, outdated, or scattered across articles that don't match how people actually ask questions.
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Why AI agents need a job description | The future of agentic AI in IT

Jul 10, 2026 By Resolve In Resolve
An AI agent is only as useful as the job you can safely hand it. In this Zero Ticket Minute, Ian Coppock, Resolve Customer & Partner Marketing Manager, breaks down why enterprise AI is moving toward purpose-built agents with defined roles, scoped permissions, and real guardrails. That is the foundation for autonomous IT operations and Zero Ticket IT. Subscribe for weekly insights on AI, IT automation, and where enterprise operations are heading.
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honeycomb

15 Best AI Observability Tools for Production Teams in 2026

Jul 10, 2026 By Shabih Syed In Honeycomb
AI applications generate far more than model outputs. Every request includes prompts, retrieval, tool calls, agent steps, latency, token usage, and evaluation signals that all contribute to the final response. When something goes wrong, engineering teams need to understand what happened, why it happened, what it cost, and whether the outcome met quality expectations.
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honeycomb

Observability vs. Monitoring for AI Systems

Jul 10, 2026 By Kale Bogdanovs In Honeycomb
Monitoring tells you when an event you predicted has actually happened. Observability lets you investigate behavior you may not have predicted at all. For most of the past decade, that distinction was something teams could afford to treat as a philosophical debate, because their systems failed in expected ways that had been seen before. A memory leak, a bad deploy, a saturated connection pool. You could build a dashboard and alerts for each and sleep reasonably well.
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Why Cash Flow Still Matters in an AI-Driven Economy

Why Cash Flow Still Matters in an AI-Driven Economy

Jul 10, 2026 By OpsMatters In OpsMatters
Artificial intelligence is changing how businesses operate. Companies are using AI tools to automate customer service, generate content, analyze data, improve forecasting, and streamline everyday tasks. For many business owners, the promise is simple: work faster, reduce costs, and improve efficiency.
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Komodor

Building AI SRE Agents, Part 1: Start Local, Break Things, Learn Fast

Jul 9, 2026 By Nir Adler In Komodor
The first stage of AI SRE maturity is a laptop, a throwaway cluster, and zero production access. Here’s how to set it up, and what to watch for. AI SRE (Site Reliability Engineering) agents are AI-powered systems that automate the most time-consuming parts of incident response: triaging alerts, correlating logs and metrics, generating root-cause hypotheses, and proposing remediation steps.
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observiq

Claude Code Monitoring at Scale: Gateways and Routing With OpenTelemetry

Jul 9, 2026 By Adnan Rahic In ObservIQ
Chelsea and I recently wrote a guide on how we monitor Claude Code usage internally with Bindplane. TLDR; We remotely manage a Bindplane Distribution of the OpenTelemetry Collector (BDOT) that runs on every engineer's laptop. This setup is great, but it has one downside. Sending to Google Cloud Monitoring, Swarmia, and any other destination directly from an engineer’s laptop is limited to local processing. You can’t get the benefit of centralized routing and processing on a gateway.
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Rethinking Sprite Creation Costs for Indie Developers

Rethinking Sprite Creation Costs for Indie Developers

Jul 9, 2026 By OpsMatters In OpsMatters
The gap between game design ambition and art production has never been more visible. Over the past twelve months, a growing number of indie teams have discovered that the bottleneck isn't always code, mechanics, or level design-it's the sheer volume of sprite frames required to bring a single character to life. A walking cycle alone can consume an entire weekend. A complete character with idle, attack, and jump animations often stretches into weeks of pixel-by-pixel work.
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The Future of Governing AI Agents in Enterprise Order Processing

The Future of Governing AI Agents in Enterprise Order Processing

Jul 9, 2026 By OpsMatters In OpsMatters
Governing AI agents are rapidly reshaping how enterprises manage complex, high-volume order workflows, from automated validation to exception resolution and fulfillment routing. As AI models become more reliable and context-aware, organizations are shifting from human-heavy processes to autonomous systems that can handle end-to-end order lifecycle management with minimal manual intervention.
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AI Detection in Your Content Pipeline: How to Reason About Detector Accuracy Before You Build a Gate Around It

AI Detection in Your Content Pipeline: How to Reason About Detector Accuracy Before You Build a Gate Around It

Jul 9, 2026 By OpsMatters In OpsMatters
Every ops team eventually inherits a check that nobody can fully explain. It runs on every release, it blocks the pipeline when it fires, and when you ask why the threshold is set where it is, the answer is some version of "it was like that when I got here." AI text detection is becoming that check for content operations. Teams are wiring detectors into publishing workflows, documentation pipelines, and vendor review steps, treating a probability score as a pass or fail gate. Then a genuinely human-written runbook gets flagged, a release stalls, and someone has to decide whether to trust the tool or override it.
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AI-powered monitoring with Site24x7's Zia

Jul 8, 2026 By ManageEngine Site24x7 In Site24x7
In this video, you'll learn how to integrate Large Language Models (LLMs) with Site24x7 using Bring Your Own Key (BYOK), Zoho Key Services (ZKS), and Microsoft Azure OpenAI. Discover how Zia helps you analyze outages, understand performance issues, identify root causes, and get monitoring insights using simple natural-language queries. What you'll learn.
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elastic

The future of governing AI agents

Jul 8, 2026 By Marcus Jeffes In Elastic
How to build governance into autonomous security agents from the architecture up The industry has moved fast on capabilities. Agents now triage alerts, investigate endpoints, create detection rules, and enrich indicators, and they are even capable of performing most actions we as security operators can perform. The architecture patterns are maturing, as are the models, but governance is not keeping pace.
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Aiven

The Aiven MCP in Practice: From Dev Environment to App Deploy

Jul 8, 2026 By Tibs (Tony Ibbs) | In Aiven
I spend a good amount of my time deploying Aiven services for demos and examples. Traditionally the tools I reach for are: If I’m writing a program, I may also look to the Aiven API, perhaps using curl at the command line or in a shell script, or perhaps with direct HTTP requests in a Python program. The API is how the console and the CLI tool talk to Aiven, but I generally find that too low level to be comfortable, and I always have to look up how to pass in the Aiven user token.
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How to Build Enterprise AI Agents with Natural Language | Agent Lab Demo, Guardrails & AI Skills

Jul 8, 2026 By Resolve In Resolve
Most enterprise AI agents take weeks to build. This one takes minutes. Watch how Agent Lab creates purpose-built agents with natural language, adds reusable skills, and sets guardrails before anything ships. From idea to production-ready in a single sitting.
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AI ROI: From Adoption to Business Proof

Jul 8, 2026 By GitKraken In GitKraken
AI adoption is easy to report. Business impact is harder to prove. Engineering leaders are under pressure to show what AI is actually changing — not just who is using it, but whether it is improving delivery, quality, developer experience, and business outcomes. This discussion between 3 engineering leaders explores how to move beyond vanity metrics, build a practical measurement approach, and communicate AI’s value to executives and CFOs with more credibility and less hype.
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Co-founder & CEO of digna, Marcin Chudeusz

From Data Warehouses to AI: How Enterprise Data Quality Has Changed Over the Last 20 Years

Jul 8, 2026 By OpsMatters In OpsMatters
An interview with Marcin Chudeusz, co-founder and CEO of digna Two decades ago, enterprise data quality looked very different. Organizations were building centralized data warehouses, business intelligence projects revolved around structured reporting, and most data quality initiatives relied on thousands of manually created validation rules. The objective was simple: ensure the data entering reports was accurate enough for decision-making.
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Anthropic Warns Against AI While Building It Faster Than Anyone

Anthropic Warns Against AI While Building It Faster Than Anyone

Jul 8, 2026 By OpsMatters In OpsMatters
On June 4, 2026, Anthropic published a document unlike anything a major AI lab had put in writing before. Titled "When AI builds itself," and co-authored by Jack Clark (Anthropic's co-founder and head of policy) and Marina Favaro, who runs the Anthropic Institute, the piece argues that frontier AI development may need to slow down - or even stop - before humans lose the ability to control what comes next.
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manageengine

The invisible visitor: Why the internet is no longer just for humans

Jul 7, 2026 By Harsitha P In ManageEngine
"Every website was once designed for people. That assumption is beginning to change." For nearly three decades, the internet has worked in a predictable way. Whenever we wanted to know something, we searched for it, clicked through a few websites, compared information, and made a decision. Whether it was buying a new phone, planning a vacation, or researching software for work, businesses knew exactly how people behaved online.
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resolve

How to Evaluate an Agentic Process Automation Platform in 2026

Jul 7, 2026 By Zack Austin In Resolve
Agentic AI has moved quickly from experimentation to enterprise planning. IT leaders are no longer asking whether AI agents can summarize tickets; they’re asking a more important question: Can agentic AI actually complete work consistently and measurably? That is where agentic process automation becomes critical.
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How to Automate Unstructured Data Using AI Agents (Clear & highly searchable)

Jul 7, 2026 By iOPEX Technologies In iOPEX
Let’s be honest: traditional automation breaks the second it hits a scanned PDF, a messy email thread, or an architectural drawing. Rules-based RPA simply lacks the cognition required to decode unstructured data. In this episode of, Project Manager Swetha K J breaks down exactly how we conquered this massive roadblock on our automation journey. By embedding advanced AI models directly into automation workflows, we’ve built a context-aware architecture that transitions systems from static execution to dynamic intelligence.
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upsun

Why individual AI adoption is breaking team-level throughput

Jul 7, 2026 By Upsun In Upsun
There is a question a lot of engineering leaders are quietly sitting with right now: we have rolled out AI tools across the team, the developers seem faster, so why isn't more software actually shipping? It is a reasonable thing to consider. Pull requests are opening faster. Lines of code per sprint are up. The boilerplate that used to take full afternoons now takes minutes. By every local measure, the investment is paying off.
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Why prompt injection gets worse with AI agents?

Jul 7, 2026 By ManageEngine In ManageEngine
When AI could only answer questions, a bad prompt just meant a bad answer. But now AI agents read your documents, browse websites, and actually do things on your behalf. So when someone sneaks a malicious instruction into a file or a webpage, the agent doesn't just say something wrong. It does something wrong!
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How do you run AI when your data can't leave the network?

Jul 7, 2026 By Civo In Civo
Highly classified environment. Strict compliance requirements. Data that can't leave the network. But still a real need for the competitive advantage AI delivers. Civo Director of Enterprise Cloud Solutions John Dietz addresses exactly that challenge and how Konstruct makes it possible to run Kubernetes, deploy your own models, and point Claude Code at your own internal private servers instead of public APIs.
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Introducing the BigPanda AI Incident Assistant

Jul 7, 2026 By BigPanda In BigPanda
AI incident assistant from BigPanda gives L2, L3, and SRE teams instant answers to resolve incidents faster without manual triage or tool-switching. IT teams lose critical minutes during incidents because context is scattered across Slack threads, bridge calls, monitoring tools, and historical tickets. The BigPanda AI Incident Assistant fixes that by surfacing relevant knowledge exactly when and where responders need it. It gives responders evidence-based resolution paths drawn from historical incidents and live system data, without leaving your workflows.
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Introducing AI Incident Prevention from BigPanda

Jul 7, 2026 By BigPanda In BigPanda
AI Incident Prevention from BigPanda stops change-related outages before they occur by leveraging risk scores, trend analysis, and guided remediation steps. Manual IT changes are still a leading cause of IT outages and disruptions. BigPanda AI Incident Prevention addresses this by automatically scoring change requests against historical data, flagging high-risk changes before they go live, and surfacing the recurring problems that cause service degradation.
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InvGate

Why Some IT Teams Adopt AI Faster (And How to Close The Gap)

Jul 7, 2026 By Natalí Valle In InvGate
Every IT leader is under pressure to show AI results. Budgets are approved, pilots are launched, and vendors promise transformation within a quarter. Some teams are already running AI agents in production, resolving tickets and answering employees without human intervention. Others are still stuck in proof-of-concept purgatory, six months into a rollout with nothing to show a board. The thing is, AI doesn't fix what's broken in an IT operation, it multiplies what's already there.
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Called it (mostly): Checking in on 2026 predictions so far

Jul 7, 2026 By Sumo Logic, Inc. In Sumo Logic
On this episode of Masters of Data, we revisit the predictions Adam White, Zoe Hawkins, and David Girvin made at the end of last year, checking our own scorecard halfway through 2026. The hits: agents running amok and deleting databases, MCP becoming the backbone for tracking what agents actually do, growing security gaps around personal data, and a collective rejection of low-quality AI content. The misses: we underestimated how fast companies would cut staff for AI, then quietly start rehiring once the agents couldn't cover the work, and we're still arguing about whether token burn is a cost problem or a coming attack vector.
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lightrun

Deterministic vs Probabilistic AI Engineering Explained

Jul 7, 2026 By Lightrun Team In Lightrun
Deterministic processes carry one guarantee: the same input will produce the same output. That guarantee built the entire observability stack. AI broke that contract by reasoning in terms of probability. The same input can now produce different outputs, whether from AI-generated code that carries assumptions invisible in staging, or from distributed systems where timing creates failures that no pre-captured telemetry can anticipate.
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cloudzero

GitHub Copilot cost: what teams actually pay in 2026

Jul 7, 2026 By Lyne Carolyne In CloudZero
The GitHub Copilot cost runs from $0 for the Free tier to $10/month for Pro, $39/month for Pro+, and $100/month for Max. Teams pay $19/user/month for Business and $39/user/month for Enterprise. The twist: on June 1, 2026 GitHub swapped fixed premium requests for usage-based AI Credits, so what those flat fees actually buy now depends on how hard you push the AI. The sticker price is the easy part. The part that ambushes finance is everything stacked on top of it.
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MCP vs CLI: Does it even make a difference? | Live Laugh Logs ep. 3

Jul 6, 2026 By Coralogix In Coralogix
MCP vs CLI: does it even make a difference? Here’s everything you need to know. Welcome to Episode 3 of Live Laugh Logs, the podcast from the Coralogix Developer Relations team. This week Andre has made the move to the US, so Annie and Lewis are joined by George Pickers, Head of Solution Engineering for EMEA & APAC at Coralogix.
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cloudzero

GPT-4 API cost 2026: pricing breakdown and how to estimate it

Jul 6, 2026 By Lyne Carolyne In CloudZero
GPT-4 API pricing spans $0.10 to $30.00 per million input tokens across the model family. GPT-4.1 is the current recommended production model at $2.00 input / $8.00 output per million tokens. Legacy GPT-4 still runs at $30.00/$60.00 per million tokens -- 15x more expensive for no meaningful quality gain. For finance and engineering leaders accountable for AI spend, choosing the right GPT-4 variant is the single biggest cost lever on your bill.
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How to Set Up Claude Code with CircleCI MCP Server (Full Demo)

Jul 6, 2026 By CircleCI In CircleCI
AI agents write code fast, but without a validation layer, fast just means faster bugs. In this video, we connect Claude Code to the CircleCI MCP server so Claude can trigger pipelines, pull build failures into context, and iterate until everything is green. No context switching. No copy-pasting logs.
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Kafka MCP: Manage Apache Kafka From Your AI Assistant

Jul 6, 2026 By Aiven In Aiven
The Aiven MCP connects Claude, Cursor, and VS Code to Apache Kafka. Inspect topics, track consumer lag, stream a database in with CDC, and manage your cluster. AIVEN DATA PLATFORM The Aiven Platform is more than a collection of open source services for streaming, storing and analyzing data. The platform ensures that all services run reliably and securely in the clouds of your choice, are observable, and can easily be integrated with each other and with external 3rd party tools.
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Aiven

Kafka MCP: Manage Apache Kafka From Your AI Assistant

Jul 5, 2026 By Roman Pozdnyakov | In Aiven
You're building with Claude or Cursor, and you need to know what's actually happening on your Kafka cluster. Your AI assistant knows Apache Kafka in the abstract, but not your topics, your retention, or that a consumer group has been slipping since this morning. So you leave the editor and go digging through logs, a CLI, and a few dashboards, correlating by hand to answer questions like: The Aiven MCP (EA) turns each of those into a sentence you type where you already work.
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InvGate

How to Measure AI ROI in IT Service Management

Jul 3, 2026 By Natalí Valle In InvGate
A service desk manager launches a virtual agent in January. By March, chat conversations are climbing, ticket volume hasn't changed much, and the monthly report doesn't explain whether the investment is delivering value. AI rarely produces a single number that proves its return. The gains accumulate across thousands of support interactions, making measurement just as important as deployment.
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InvGate

Introducing AI Analytics Reports in InvGate Service Management

Jul 3, 2026 By Natalí Valle In InvGate
Most teams can confirm their AI features are turned on. Measuring how often employees use them, which requests get resolved without agent intervention, and where AI is helping support teams work more efficiently is a different question. In InvGate Service Management, those capabilities live in AI Hub, a set of built-in AI features that includes the Virtual Service Agent, AI-assisted ticket resolution for agents, automated knowledge generation, and more.
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VictoriaMetrics

Observability for LLM Apps and Agents: OpenLIT SDK + VictoriaMetrics observability stack

Jul 3, 2026 By Aman Agarwal / Roman Khavronenko In VictoriaMetrics
Many “LLM observability with OpenTelemetry” tutorials stop at a single chat.completions span. That works for a demo, but it leaves gaps once an agent fans out into 30 tool calls, two vector-DB queries, three handoffs, and a 90-second tail latency you need to attribute. This post wires the OpenLIT SDK (50+ instrumentations, OTel GenAI semantic conventions, one line of code) into the full VictoriaMetrics observability stack and shows query examples that turn agent telemetry into decisions.
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tigera

Six AI agent SDKs for enterprise Kubernetes, compared

Jul 3, 2026 By Alister Baroi In Tigera
There’s a question we hear constantly from platform and engineering leaders right now, “which agent SDK should we standardize on for our Kubernetes clusters?” The honest answer is that the question is slightly wrong, and the rest of this post explains why. But it’s a fair question, so let’s compare the contenders first.
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AI on AI Challenges

Jul 3, 2026 By PagerDuty Inc. In PagerDuty
Building AI agents is easy until they launch into production and start behaving unpredictably. In this presentation, João Freitas, Chief AI Officer at PagerDuty, dives into the messy reality of scaling non-deterministic systems and shares how PagerDuty manages multi-agent complexities. Speaker: João Freitas, Chief AI Officer, PagerDuty Recorded during GenAI Community x Google Developer Group Lisbon at PagerDuty Portugal offices, July 2026.
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harness

Prepare for the EU AI Act with Harness AI Security | Harness Blog

Jul 2, 2026 By Vikas Gautam In Harness
Harness AI Security provides a unified control plane for AI discovery, risk visibility, and runtime protection, helping organizations operationalize key requirements of the EU AI Act. Instead of relying on manual audits or fragmented tooling, teams get continuous insight into how AI systems are built, exposed, and used, along with the evidence needed to demonstrate compliance.
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circleci

ACP vs MCP: What's the difference for agentic coding?

Jul 2, 2026 By Roger Winter In CircleCI
An AI coding agent holds many conversations at once. Not only is the user prompting it, the agent also talks to the IDE, showing diffs and asking before it touches a file. At the same time it talks to tools, pulling a failing build or querying a database. Two open protocols standardize those conversations. This guide compares ACP vs MCP in practical terms: what each protocol does and when each applies. ACP (Agent Client Protocol) connects a code editor to an AI coding agent.
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pagerduty

Why Faster Recovery Beats Faster Shipping in the AI Era

Jul 2, 2026 By PagerDuty In PagerDuty
A year ago, AI coding tools worked alongside developers—suggesting the next line, completing a function, accelerating work that a human was already doing. Today, they’re writing entire modules and services independently, producing code that no human has reviewed line by line, built from components that no single person has fully mapped. And adoption is only accelerating: According to our recent AI Resilience Survey, 84% of organizations are now using AI to write, review, or suggest code.
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Aiven

Right Size Your Model Usage with Valkey and Semantic Routing

Jul 2, 2026 By Jay Miller | In Aiven
Benchmarks keep showing that picking the right LLM is hard. The easy answer is "just use the most powerful one." That works, but it is pricey. A small, cheap, or local model can handle many simple requests just as well as a frontier model, for a fraction of the cost. That is what semantic routing is for. Use middleware that looks at an incoming request and decides which model should answer it.
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cloudzero

OpenAI API cost calculator: estimate your GPT spend before it estimates you

Jul 2, 2026 By Lyne Carolyne In CloudZero
This OpenAI API cost calculator (also an AI inference calculator for o3/o4-mini thinking tokens) estimates your monthly OpenAI API pricing bill from three inputs: model, request volume, and average tokens per request. Toggle between standard, batch, and cached pricing and get your number in seconds. It also shows what the same workload costs on Claude and Gemini. For the full per-model rate card, see CloudZero's OpenAI API pricing guide.
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AI Summary Agent in Turbo360

Jul 2, 2026 By Turbo360 In Turbo360
Handed over an Azure integration environment you've never seen before? Turbo360's AI Resource Summary agent gives any support operator or engineer an instant plain-English overview of what a resource is, how it behaves, and what to watch out for - without needing to ask the developers. In this demo: Great for: IT operations teams, MSP NOCs, cloud support engineers, and anyone responsible for running integration workloads they didn't build.
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Why Most AI Pilots Never Reach Production

Why Most AI Pilots Never Reach Production

Jul 2, 2026 By OpsMatters In OpsMatters
Most AI initiatives never make it out of the pilot stage. Gartner has forecast that 30% of generative AI projects will be abandoned after proof of concept by the end of 2025, undone by poor data quality, weak controls, unclear business value, and escalating cost. The problem predates the current wave of generative tools. RAND's study of experienced practitioners found that more than 80% of AI projects fail, roughly twice the rate of IT projects that carry no AI component.
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site24x7

How Agentic AI speeds up troubleshooting application issues

Jul 1, 2026 By Sangavi Dass In Site24x7
One night, Daniel Rizzy was the only person awake on Zylker’s IT team, and the clock was already running. He was also the only thing standing between a P1 outage and 10,000 customers. Rizzy works nights for ZylkerXchange, Zylker’s foreign currency exchange app. He lives on the city’s outskirts, where the air is clean and quiet, and the night shift suited that life. Most nights, nothing happened. Some nights, everything did.
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almaden ai

The Future of Digital Experience in Companies: What Changes with DEX, AI, and the Employee at the Center

Jul 1, 2026 By Almaden AI In Almaden AI
For decades, companies measured IT efficiency through technical indicators: servers up, systems online, equipment working. But does that actually mean a good experience for the people doing the work?
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cloudzero

Shipped: Turn your Bifrost gateway into an AI spend meter

Jul 1, 2026 By Thomas Evans In CloudZero
If you route model traffic through Bifrost, you already have the hard part: one place every AI call passes through, where the model, the tokens, and the cost are visible on the way past. It’s the cheapest spot in your stack to measure AI spend. What’s missing is everything downstream – today that usage only becomes “spend” weeks later, when the provider invoice lands as a lump sum you can’t break apart.
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AI Tool Sprawl Is Killing Enterprise ROI | Why Orchestration Matters More Than AI Features

Jul 1, 2026 By Resolve In Resolve
Enterprise AI adoption is accelerating, but are organizations actually solving business problems or just adding more tools? In this episode of Agents of IT, Fran Fernandez (Chief Product Officer at Resolve) and Zach Austin (Director of Product Marketing) explore one of the biggest challenges facing enterprise IT in 2026: AI tool sprawl. They discuss why many organizations struggle to demonstrate ROI from AI investments, how disconnected AI assistants create operational complexity, and why orchestration, automation, and context have become the real differentiators for enterprise AI success.
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sentry

Reading the agent traces is how you make the call your eval can't

Jul 1, 2026 By Sergiy Dybskiy In Sentry
Remember being excited (or dreading, depending on the stage of your career and the company you worked at) about writing unit tests? Or sweating all the details in your end-to-end and integration tests you were sure covered all the use cases your users would hit? These days a lot of UIs are slowly being replaced by a single input field and an agent that promises to deliver the same value a UI would, but with the elegance and pun-ness of a “Jarvis”.
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Harness Agents

Jul 1, 2026 By Harness In Harness
Today, we're launching Autonomous Worker Agents, AI agents that run as governed pipeline steps inside Harness. They inherit OPA policies, RBAC, audit trails, and scoped credentials from the first run. And because they live inside your Harness pipelines, they reason using the Harness Knowledge Graph: your services, deployments, incidents, and policies.
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AI Agents Write Broken Code 49% of the Time #speedscale #AI #Coding #Tech #DevOps

Jul 1, 2026 By Speedscale In Speedscale
AI agents write broken code nearly 50% of the time. By adding a traffic-based deterministic evaluation, Speedscale boosted unsupervised bug-fixing quality from 51% to 77% in just 5 minutes. This helped slash token costs and eliminate rework without human intervention. Learn more: speedscale.com.
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LogicMonitor and Edwin AI: Autonomous IT for Hybrid IT Environments

Jul 1, 2026 By LogicMonitor, Inc. In LogicMonitor
Autonomous IT starts now with LogicMonitor and Edwin AI, built to help IT teams monitor complex hybrid IT environments, discover root cause faster, reduce downtime, and prevent incidents before they impact revenue or brand reputation. See how LogicMonitor brings AI-powered IT operations, observability, and incident prevention together for modern infrastructure teams.
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lightrun

How AI Agents Are Changing Each Agile SDLC Phase

Jul 1, 2026 By Lightrun Team In Lightrun
The Agile software development lifecycle was designed to surface problems early, with short sprints, iterative testing, and continuous integration built on the premise that faster feedback loops produce better software. AI coding tools have changed the velocity equation across every phase of that loop, but the phases designed to catch failures are struggling to keep up because build speed and validation capacity have not accelerated at the same rate, and the gap between them is widening with every sprint.
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atlassian

Fix flaky tests with AI, and track future test work in Jira

Jul 1, 2026 By Rajkumar Singh In Atlassian
In January we launched Tests in Bitbucket Pipelines – a single place to track, organize, and understand your test health over time. In April we added automatic flaky test detection so unreliable tests get flagged before they slow your team down. But spotting a problem is only half the battle. Day to day, your team still needs to act on a test – track it as work, clean it up, or route it to the right person.
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PagerDuty agent app in GitHub

Jul 1, 2026 By PagerDuty Inc. In PagerDuty
PagerDuty's agent app shows live incident state, incident history and change correlations inside GitHub so you can get context right within your PR without interrupting your flow. Automatically correlate incident data with recent commits and deployments to identify root causes, then generate fix PRs with proper incident linking.#IncidentResponse.
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pagerduty

PagerDuty agent app in GitHub: incident context where you already work

Jul 1, 2026 By Hannah Culver In PagerDuty
This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey toward autonomous operations. Read on to learn about the PagerDuty agent app in GitHub (Early Access) and how it builds toward this vision. How many tabs do you have open right now? And how many more do you open the moment an incident hits? Context switching during incident response is one of the most persistent sources of toil in engineering.
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pagerduty

AI Orchestrations: Your easy button for proactive operations

Jul 1, 2026 By Ariel Russo 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 AI Orchestrations builds towards this vision. “We should automate this.” Sound familiar? For many operations teams, that sentence never becomes action. Building event orchestration rules demands deep platform expertise, time no one has, and the ability to spot which patterns in your data actually matter.
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nexthink

The Next Enterprise AI Challenge: The Multi-Model Workplace

Jul 1, 2026 By Shawn Lazarus In Nexthink
For the last two years, enterprise AI strategy has largely focused on one thing: adoption. Organizations encouraged employees to experiment with ChatGPT, Claude, Copilot, Gemini, and dozens of emerging AI tools in the hope that productivity gains would naturally follow. CIOs approved pilots, departments launched AI task forces, and leaders pushed teams to integrate AI into everyday work as quickly as possible. But the enterprise AI conversation is beginning to change.
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datadog

How Datadog uses AI to build internal software delivery tools and improve system performance

Jul 1, 2026 By Bowen Chen In Datadog
At Datadog, we want our developers to become better at using AI tools with the end goal of building quality software, faster, that generates real value. This includes not only the products and features that our customers use, but also the internal tools that help keep our workflows running smoothly behind the scenes.
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datadog

Accelerate investigations with AI in Datadog Incident Response

Jul 1, 2026 By Curtis Maher In Datadog
Engineering teams spend much of their incident response time investigating the problem and coordinating the response. Both tasks become harder when telemetry data lives in one place, deployment history is stored in another, and conversations unfold across chat channels and incident bridges. Responders often spend the first part of an incident rebuilding context before they can begin testing hypotheses and working toward resolution.
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cloudzero

Don't 'control' your AI spend. Understand it and be intentional.

Jul 1, 2026 By David Aponovich In CloudZero
There’s a good interview making the rounds. BizTech sat down with IBM’s James Stevenson to talk about how financial institutions can get a handle on cloud and AI costs. The advice is solid: get visibility, kill idle resources, tighten governance, tag everything. And pull finance and engineering into the same room. I don’t disagree with it. But I read the whole piece and noticed where the gravity pulls: control costs, reduce waste, bring down spend. The headline says it (‘Q&A.
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GLM-5.2 Review (2026): Zhipu AI's Open-Weight Coding Model, Honestly Assessed

GLM-5.2 Review (2026): Zhipu AI's Open-Weight Coding Model, Honestly Assessed

Jul 1, 2026 By OpsMatters In OpsMatters
Zhipu AI (now operating internationally as Z.ai) shipped GLM-5.2 in mid-June 2026, and the claim that grabbed attention was blunt: an open-weight model that beats GPT-5.5 on several long-horizon coding benchmarks for roughly one-sixth of the cost. It's an MoE model with 753 billion total parameters released under an unrestricted MIT license, which means you can self-host it or call it through a managed endpoint.
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How One AI-Localized String Broke Our Build and Cost Me $6,000 (And What I Do Differently Now)

How One AI-Localized String Broke Our Build and Cost Me $6,000 (And What I Do Differently Now)

Jul 1, 2026 By OpsMatters In OpsMatters
The string that broke our last release was four words long. It passed review, went green in the build, and shipped to our German locale with a corrupted placeholder that turned the checkout button into a runtime error. Customers there could not complete an order for most of a Saturday before a screenshot reached me. The broken button cost us roughly $6,000 in lost orders that weekend; the fix itself took ten minutes. What I do differently now started with understanding why it happened.
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Making Testing Smarter: How AI in testing automation Supports Continuous Change

Making Testing Smarter: How AI in testing automation Supports Continuous Change

Jul 1, 2026 By OpsMatters In OpsMatters
Selecting a freight forwarder in 2026 is no longer just about getting goods from point A to point B. You now need a partner that can handle customs clearance, protect delivery timelines, provide transparent shipment updates, and help you understand how sustainable your supply chain is. It matters when disruption to supplies, expectations of customers, and reporting on the environmental impact of operations all sit with one team managing operations.
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