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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Your AI agents don't need better models. They need the same context.

Everyone on the team has good coding agents. That is not what made the team fast. The shared repo, the shared docs, and a glossary nobody is allowed to drift from did more than any model choice. In this Product Highlights conversation, Patrick Dawkins, a principal engineer at Upsun who is building Upsun Dispatch under a hard deadline, explains what his team changed to sustain that pace. His take: "As well as the team all having access to the same things and the same vocabulary, all the agents also have access to those docs.".

Introducing MCP Connections: Netdata AI Now Reads From the Tools You Already Run

Netdata AI can now connect outward to the tools your team already runs, like GitHub, PagerDuty, Atlassian, or any custom MCP server, and read from them during an investigation. We call this MCP Connections. It’s the missing piece in the middle of every root-cause investigation: the alert tells you what changed, but the why is usually somewhere else entirely.

Netdata Network Topology: Live SNMP Discovery & Container Connection Maps

Netdata now builds live network topology maps directly in the agent: no scheduled scans, no stale picture the next morning. In this walkthrough, we cover both sides of the new Topology view: Network device discovery (SNMP): Container & process network connections.

Shipped: Put every AI task on the cheapest model that can actually do it

If your team builds with AI, someone is defaulting to the biggest model available (say, Fable) because it feels like the safe pick, and the safe pick is almost always the most expensive one. One over-powered choice looks harmless on its own, but multiplied across every prompt, agent, and workflow, and you get a big number on the P&L. All that, yet nobody chose which model on purpose. As we like to say, using a default is not a decision.