Blogsby GlyphHow to measure and improve instrumentation quality for better full-stack observability
Modern engineering teams instrument everything, with metrics, logs, traces, and profiles flowing from hundreds of services at once.
6 of 800 posts
Thu Aug 271 post
Tue Aug 251 post
The Grafana AI SDK for Go: a shared foundation for building AI applications
Starting an experiment with an LLM has never been easier. Keeping a growing collection of those experiments consistent is another matter.
Fri Aug 211 post
How to scale Alloy as a central telemetry gateway: capacity planning, load testing, and production lessons
Running Alloy as a single-instance sidecar is simple. Running it as a centralized gateway that absorbs the full telemetry stream of an enterprise platform, tens of millions of active series, terabytes of logs per day, and tens of thousands...
Thu Aug 201 post
Grafana 13.2 release: easier ways to query and explore your data
Grafana 13.2 is here, bringing more improvements to help you and your team explore your data and get to insights faster. In this post, we’ll highlight the latest updates to saved queries, a feature that lets teams share, discover, and...
Wed Aug 192 posts
From failed check to real user impact: Pairing Synthetic Monitoring and Frontend Observability in Grafana Cloud
Say you get a support escalation about a page in the app that won’t load. But when you pull up your synthetic checks, they're all green: 100% uptime, probes are passing. Something's not adding up, but which one do you trust?
Knowledge Graph as context for LLMs: demonstrating decisive RCA and faster production performance
On the product team here at Grafana Labs, we consider AI agents our users, too. That’s why we set out to test how well agents can debug incidents across the full stack, and how much better they perform with Grafana Cloud’s Knowledge Graph...