Operations | Monitoring | ITSM | DevOps | Cloud

The Data Race That Wasn't a Bug (and the One That Was)

Imagine this: you are testing the performance of some part of your application. Everything is going smoothly, the numbers look good, and as a last check you turn on Go’s race detector. Then, out of nowhere, it prints a warning you didn’t expect: So you look at it. You look at it again, and again, and you think: “What the…?” The race is between your code and a goroutine you never started, somewhere deep inside net/http. You have no idea how that is possible, or why.

The Year-2 Price Cliff: What Your Observability Stack Really Costs Over 3 Years

I’m not the one whose phone lights up at 3 a.m. when production breaks. But I’ve spent years working alongside the engineers who are, and I’ve noticed that observability migrations happen for two reasons. Either engineering needed one, or, far more often, a quote landed that looked too good to refuse. The engineers rarely regret the first kind. The second kind they tell me about in year two, usually with a renewal notice in hand.

Telemetry Talks ep 8 - Fireside chat with OpenTelemetry maintainers

Telemetry Talks episode 8 is here We sat down with OTel maintainers to talk about the future of the community, GenAI semantic conventions, contributing beyond code, OTel in Practice, and what they’re currently building, writing, organizing, and experimenting with across the CloudNative and OpenSource ecosystem. A conversation about where OTel is today and what comes next. Playlist Resources for Further Learning.

How Linux readahead works, and the two ways to change it

Most of the time, when we read a file, we do not think much about what happens underneath. You ask for some bytes, you get some bytes. But when getting data off the disk efficiently is at the core of what your application does, what happens underneath starts to matter a great deal, and two identical read() calls can differ enormously in what they cost. So in this post we are going to look at one of the Linux kernel’s optimizations for reading files: readahead.

VictoriaTraces in VictoriaMetrics Cloud: Complete Observability is Here

Earlier this year, we launched VictoriaLogs in VictoriaMetrics Cloud, bringing fast and cost-effective log management to everyone. Today we launch the final major step toward full observability: VictoriaTraces is now available to all cloud users. With this release, you can now manage all three signals, metrics, logs, and traces, in one place with the predictable pricing, reliability, and the operational simplicity you’ve come to expect from VictoriaMetrics.

Tech Talk #15 - How VictoriaLogs Go Fast

Go is fast because of decisions most engineers never see. Jesus walks through how VictoriaMetrics uses Go to process logs at scale, the tradeoffs behind those choices, and what breaks if you get them wrong. If you write Go or run log pipelines, this is 30 minutes worth blocking your calendar for. Resources for Further Learning.

Telemetry Talks ep 7 - Beyond OpenTelemetry with anomaly detection

In this episode, we continue to dive into the workshop we hosted at Cloud Native Days Romania in May, together with our guest, Fred Navruzov, correlating OpenTelemetry with anomaly detection. Furthermore we explore how the VictoriaMetrics MCP server and skills bring AI-powered observability to your workflows. Learn how to detect anomalies faster and interact with your metrics, logs and traces using natural language.

The most expensive half-hour of an incident.

It’s not the outage, it’s the stretch before you know what actually broke In short: VictoriaMetrics Enterprise support is expertise, not a ticket queue. It’s reactive by design (you reach engineers who know the stack when something breaks), with one proactive service, Monitoring of Monitoring, that watches the health of your VictoriaMetrics observability stack (metrics, logs, and traces).