SigNoz

We got 30% more log processing performance without adding hardware. Problem: Sequential processing = idle CPU cores Solution: Concurrent worker pools = full utilization 35.7k → 66k logs/second peaks 67% → 108% CPU usage Technical breakdown: signoz.io/blog/optimizin…

MCP servers for observability: sophisticated co-pilots, not automated SREs. Problem: Root cause analysis is an NP problem. Verifying AI hypotheses often takes as much effort as manual investigation. Research shows the limitations: signoz.io/blog/unhyped-t…

OpenTelemetry K8s observability: 2 collectors for full coverage: - DaemonSet (per-node telemetry) - Deployment (cluster-wide metrics) Helm presets handle configuration automatically. Complete setup guide: signoz.io/blog/kubernete…

We made log queries 99.5% faster by fixing how we store data. Before: 41,498/41,676 blocks scanned (99.5%) After: 222/26,135 blocks scanned (0.85%) The fix: Resource fingerprinting + ClickHouse primary key optimization. signoz.io/blog/query-per…

5-part Next.js observability tutorial series: signoz.io/opentelemetry/… 1/ Server-side tracing & API monitoring 2/ Error tracking & external API monitoring 3/ Web Vitals & component performance 4/ Structured logging 5/ Production deployment & scaling

From observability chaos to clarity in days. Before: CloudWatch + Honeycomb = constant context switching After: One platform for logs, metrics, traces "Every single time we have an issue, SigNoz is always the first place to check." - Karl, @shapedai signoz.io/case-study/sha…

We shipped v0.89.0 completing the final step in our Dot Metrics Migration. Also includes UI improvements: 1/ Text selection in log JSON fields 2/ Smooth auto-refresh updates signoz.io/changelog/

MCP servers are black boxes in your agentic AI stack. When things break, how do you debug? Our guide shows how OpenTelemetry brings transparency to MCP architectures: signoz.io/blog/mcp-obser…