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233 articles · page 3 of 5

DevOps.com, Friday, May 1st, 2026

The Trust Problem With AI Agents in Production Pipelines

Vol 337 · Issue 5 · 2026-05-01

Let me describe a scenario that is already playing out in production environments. A team deploys an AI agent to handle routine infrastructure scaling. The agent performs flawlessly for weeks. It optimizes costs, responds to traffic patterns faster than any human could, and the team starts trusting it implicitly.

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The Trust Problem With AI Agents in Production Pipelines

DevOps.com, Wednesday, April 29th, 2026

AIOps Isn't Optional Anymore: What Modern DevOps Teams Must Adapt To

Vol 337 · Issue 5 · 2026-04-29

Modern infrastructure has become much more complicated than in the past. There is a constant flow of information, consisting of metrics, logs, and alerts. This is due to the introduction of microservices architecture, hybrid clouds, containerization, and IoT. Reliability is critical in the current business environment because the failure of infrastructure could mean losses for both reputation and productivity.

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AIOps Isn't Optional Anymore: What Modern DevOps Teams Must Adapt To

DevOps.com, Tuesday, April 28th, 2026

GitHub Faces Scaling Issues as AI Development Surges

Vol 337 · Issue 5 · 2026-04-28

It appears that GitHub has its hands full adjusting to the demands of scaling AI workloads. First, the company paused sign-ups for its Copilot subscription tiers in response to a wave of demand from agentic AI projects. Then it shifted to usage-based pricing to, again, better align revenue with the heavy compute demands of AI projects.

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GitHub Faces Scaling Issues as AI Development Surges

DevOps.com, Monday, April 27th, 2026

Microsoft Foundry Tackles the AI Agent Tool Problem Nobody Talks About

Vol 337 · Issue 5 · 2026-04-27

Building AI agents sounds straightforward until you actually do it. You need an agent to onboard a new employee. It has to create an Entra ID account, provision GitHub access, spin up cloud resources, create tasks in Azure DevOps, and send a welcome message in Teams. Five tools. Five different authentication models. Five different teams are managing those tools.

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Microsoft Foundry Tackles the AI Agent Tool Problem Nobody Talks About

DevOps.com, Monday, April 27th, 2026

Embracing the MCP Suck: Taming the Wild West of AI Protocols

Vol 337 · Issue 5 · 2026-04-27

The Model Context Protocol (MCP) is moving faster than the developer community can keep up with, racing past its original design parameters and leaving teams scrambling to build clients that can match its pace. The result is an ecosystem where the protocol itself keeps shifting under everyone's feet, and where the tooling, conventions and security thinking that should accompany a foundational standard are still being figured out on the fly.

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Embracing the MCP Suck: Taming the Wild West of AI Protocols

devops.com, Wednesday, April 22nd, 2026

AI Agents In Devops: Hype Vs. Reality In Production Pipelines

Vol 337 · Issue 4 · 2026-04-22

The demos look super cool! An AI agent detects a failing deployment, rolls it back, opens a GitHub issue, and notifies Slack - all before the on-call engineer has finished reading the alert. If you've been following the DevOps tooling space over the last 18 months, you've probably seen some version of this pitch.

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AI Agents In Devops: Hype Vs. Reality In Production Pipelines

devops.com, Friday, April 17th, 2026

The Open Source Trap: Why Trust Isn't a Security Strategy

Vol 337 · Issue 3 · 2026-04-17

The XZ Utils backdoor was a wake-up call, but the underlying problem it exposed has not gone away. Sophisticated adversaries are playing the long game, spending months or years earning trust within open source projects before introducing malicious code into libraries that sit at the foundation of modern software infrastructure.

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The Open Source Trap: Why Trust Isn't a Security Strategy

devops.com, Thursday, April 16th, 2026

Waydev Adds Ability to Track How Much AI Code Winds Up in Production

Vol 337 · Issue 3 · 2026-04-16

Waydev today revealed it has revamped its engineering intelligence platform to provide insights into how the adoption of artificial intelligence (AI) coding tools is impacting DevOps workflows. Company CEO Alex Circei said the overall goal is to make it easier for the leaders of software engineering teams to determine the return on investment (ROI) their AI coding tools are actually providing.

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Waydev Adds Ability to Track How Much AI Code Winds Up in Production

devops.com, Thursday, April 16th, 2026

From Code To Cloud: How Full-Stack Developers Are Taking Over DevOps

Vol 337 · Issue 3 · 2026-04-16

There was once a trend toward becoming a full-stack software engineer. Today, full-stack engineers are not limited to UI (User Interface) and DB (Backend Databases), they are adapting to cloud-native applications, managing Infrastructure as Code (IaC), automating CI/CD pipelines and using tools like GitHub Actions, Docker, and Terraform.

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From Code To Cloud: How Full-Stack Developers Are Taking Over DevOps

devops.com, Tuesday, April 7th, 2026

VibeCode Meets DevOps: Accelerating Low-Code Innovation

Vol 337 · Issue 2 · 2026-04-07

AI-assisted low-code platforms like VibeCode are generating a lot of excitement. They let users describe applications in natural language and produce working code quickly. This speed is impressive, but it raises questions for DevOps teams responsible for stability, security, and reliability.

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VibeCode Meets DevOps: Accelerating Low-Code Innovation

devops.com, Tuesday, April 7th, 2026

If It Isn't Code, It's Just Advice

Vol 337 · Issue 2 · 2026-04-07

When you ask an AI coding agent how to solve a problem, it reaches for code. That's not just a preference - code is how software teams actually ship and we have an ecosystem of essential tools and management systems: Version control, reviews, tests in CI, deploys and rollbacks.

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If It Isn't Code, It's Just Advice

devops.com, Monday, April 6th, 2026

Is Your AI Agent Secure? The DevOps Case For Adversarial Qa Testing

Vol 337 · Issue 2 · 2026-04-06

The most dangerous assumption in quality engineering right now is that you can validate an autonomous testing agent the same way you validated a deterministic application. For the last decade, we wrote tests that expected input A to always produce output B, and we built entire CI/CD pipelines around that binary logic.

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Is Your AI Agent Secure? The DevOps Case For Adversarial Qa Testing