Ai

SigNoz is building observability for the AI era: agent-native observability and AI-scale telemetry. We shipped MCP, Noz, dashboards, and a new trace view.

The new SigNoz Cloud trace detail view renders 100,000 spans in one flame graph. Find the failing span in million-span, AI-scale traces, fast.

Agent-native observability dashboards in SigNoz Cloud. A validated schema on the open CNCF Perses spec lets agents create and edit dashboards reliably.

MSI's sales-order workflow runs across the UI, APIs, database, and its ERP. Engineers already used SigNoz for API traces and logs. Here's how Taylor Mattison uses SigNoz MCP with Claude to compare traces at scale, connect telemetry to code, and get to a clear answer for where slowdowns actually live.

Kathleen Xue at Shaped used a coding agent with SigNoz MCP to fix a Redis latency bug that had lived in production for almost a year. A closer look at what agent-native observability actually takes.

Meet Noz, the AI teammate inside SigNoz that answers from your telemetry and docs, creates alerts and dashboards, and helps teams work inside SigNoz faster.

A case study of how Alien Intelligence built an AI SRE workflow on SigNoz to triage alerts, reduce noise, and keep humans in the loop.

SigNoz introduces agent-native observability with the SigNoz MCP server, plus AI Assistant (beta) and Agent Skills coming soon. Agents bring the context, humans bring the care.

When AI handles 95% of your incident response, do you get worse at handling the 5% that actually matters? Exploring the ironies of automation applied to SREs and the growing deskilling risk.

This blog is a look into how our engineers use AI for coding (and where they refuse to) with practical tips that you can adopt asa well.