Operations | Monitoring | ITSM | DevOps | Cloud

What actually makes a logging system fast? That was the question behind Tech Talk. And if you were expecting the answer to be a collection of clever Go optimizations, Jesús Espino, Principal Engineer at VictoriaMetrics, made an important point pretty early in our conversation: A huge part of VictoriaLogs’ performance comes from architecture and data structures. The micro-optimizations come later. Now that gave my Tech Talk partner in crime, Mathias Palmersheim, and me plenty to dig into.

Starting an experiment with an LLM has never been easier. Keeping a growing collection of those experiments consistent is another matter. Earlier this year, as more teams began exploring AI features here at Grafana Labs, we repeatedly encountered the same pattern: a new experiment would start, move quickly, and build its own client for whichever model provider it needed. The next experiment would do the same, with a slightly different abstraction for streaming, tools, errors, or provider configuration.

With the new NETGEAR AV Line monitoring plugin, you can easily monitor NETGEAR AV Line devices in Icinga 2. This lightweight yet powerful Go-based tool communicates directly with the devices’ API and provides clear status values – including perfdata.

Coroot's node-agent already collects CPU profiles for any process on the node using eBPF, with zero integration from the application side. For Java, we dynamically inject async-profiler into the JVM to get memory and lock profiles. But Go processes were still a blind spot for non-CPU profiling unless the app exposed a pprof endpoint and the cluster-agent scraped it. We wanted the same zero-config experience for Go heap profiles. This post is about how we got there.

Sometimes the hardest part of debugging a system isn’t fixing the problem—it’s figuring out what’s actually happening in the first place.

You probably should avoid ctx.WithTimeout or ctx.WithDeadline with code that makes network calls. Here is why.

This article explains how to use opentelemetry-go Metrics API to collect metrics, for example, go-redis/cache stats.

Golang (Go) applications are known for their high performance, concurrency model, and efficient resource use, making Go an easy choice for building modern distributed systems. But just because your Go application is built for speed doesn't mean it's running perfectly in production. When things go wrong, just checking if your service is "UP" isn't enough.

Go’s os.Root feature, introduced in Go 1.24, is designed to improve filesystem security by restricting operations to a specific directory, making it much harder for attackers to exploit path traversal vulnerabilities.

This technical deep-dive reveals how Harness engineers discovered and fixed a critical Go memory leak where reassigning context variables in worker loops created invisible chains that prevented garbage collection across thousands of goroutines, ultimately consuming gigabytes of memory in their CI/CD delegate service.