Operations | Monitoring | ITSM | DevOps | Cloud

The latest News and Information on Continuous Integration and Development, and related technologies.

Keep your Agents Under Control with agent-belt

You’re shipping a product with an AI-facing interface, or embedding AI-facing interfaces across your existing product line – skills your customers trigger, MCP servers their agent reaches for. Indie author or enterprise, your code runs in someone else’s agent runtime, against a model that updates every other day and a CLI that updates every other week. Cursor 2026.05.05-84a231c rolls out. Claude Code 2.1.132 lands the same week. OpenAI bumps gpt-5.5.

The Hidden Cost of Kubernetes: Why Your Cloud Bill Is 40% Higher Than It Should Be

The average enterprise running Kubernetes wastes between $2 million and $10 million annually — not from overspending, but from under-optimizing. This is the story of costs you can't see on your dashboard but that your CFO feels every quarter.

There's an npm-shaped hole in the AI tooling stack

I've had this same conversation with 60+ engineering teams in the last six months. A team adopts AI tooling. One developer figures out how to use it well, builds up a vault of skills, MCP configs, and slash commands that 10x their output. The rest of the team has whatever they can scavenge from a shared Notion doc.

How Engineering and Ops Teams Use OKRs to Connect Technical Work to Business Outcomes

Engineering and operations teams have a measurement problem that most other functions don't. The technical metrics are excellent. Deployment frequency is up. MTTR is down. Uptime is at 99.97%. The CI/CD pipeline is running cleanly and the on-call burden has been reduced by 30% since the team adopted a proper incident management process. By every internal measure, the team is performing well. And yet, in the quarterly business review, the conversation keeps returning to the same uncomfortable question: what did engineering actually deliver for the business this quarter?

AI DevOps in 2026: How AI Coding Tools Are Breaking Your CI/CD Pipeline (and How to Fix It)

AI coding tools turned every engineer into a 10x developer. Now your CI/CD pipeline is the bottleneck. Learn how to handle 10x more deploys per engineer with Qovery's dual deployment model. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

Getting started with Codex and CircleCI

Codex is OpenAI’s coding agent, powered by the GPT-5 family of models. It reads your files, proposes edits, and runs commands directly in your local environment. It ships as both a desktop app and an open source CLI, and it extends through plugins that connect it to external tools and services. Like any AI coding tool, Codex is strongest when the code it generates gets validated automatically.
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The SDLC: phases, popular models, benefits & more

The Software Development Life Cycle (SDLC) describes the process we follow to deliver software to customers. It captures each step of creating software, from ideation to delivery and eventually to maintenance. In this post, we've broken down everything you need to understand the SDLC.

Three Architectural Principles for Mythos & GPT-Cyber Readiness

Since Anthropic announced Project Glasswing and the capabilities of Claude Mythos Preview, and OpenAI announced GPT-Cyber – my calendar has looked the same every day: Back-to-back calls with CISOs, AppSec leads, and security architects. And every call starts with the same question.

How to Improve Your Documentation with AI (CircleCI Chunk Tutorial)

AI coding assistants help you ship features fast, but documentation almost never keeps up. In this Ship Smarter session, we'll show you how CircleCI's Chunk autonomous CI/CD agent automatically analyzes your codebase, identifies documentation gaps, and opens a pull request with improvements. No manual writing required. In this video.