Instant Open Source Observability: the magic of eBPF
Alex chats a little with Josh Lee, a Developer Advocate at Altinity with over 15 years experience in software development and management, about why he loves using Coroot.
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Chaos Testing a PostgreSQL Cluster: How Kubernetes Can Restore Replica Failures (in 30 Seconds)
🐧🐝 Use open source, automatic eBPF observability to quickly fix Patroni failures in your kubernetes cluster: https://t.ly/qBH9f
#devops #opensource #observability #kubernetes #postgresql
How to achieve Root Cause Analysis in 30 seconds: Chaos testing a PostgreSQL cluster
🐧🐝 Use open source, automatic eBPF observability to quickly fix Patroni failures in your kubernetes cluster: https://t.ly/qBH9f
How to achieve better observability and faster MTTR with the App Health Summary page
🐧🐝 Try Coroot fully open source or Enterprise and check out the latest open source observability tips on our blog: https://t.ly/qBH9f
OpenTelemetry for Go: measuring the overhead
Everything comes at a cost — and observability is no exception. When we add metrics, logging, or distributed tracing to our applications, it helps us understand what’s going on with performance and key UX metrics like success rate and latency. But what’s the cost? I’m not talking about the price of observability tools here, I mean the instrumentation overhead.
How to reduce Cloud Costs (with Open Source!)
We strongly believe that simple observability should be an innovation everyone can afford to benefit from: which is why Coroot is open source, and includes cost monitoring for Azure, GCP, AWS, or your own custom settings. eBPF automatically tracks how each deployment impacts your cloud costs, so you can easily roll back changes and avoid lovecraftian monthly bill when necessary.
Working with GPUs on Kubernetes and making them observable
GPUs are everywhere powering LLM inference, model training, video processing, and more. Kubernetes is often where these workloads run. But using GPUs in Kubernetes isn’t as simple as using CPUs. You need the right setup. You need efficient scheduling. And most importantly you need visibility. This post walks through how to run GPU workloads on Kubernetes, how to virtualize them efficiently, and how Coroot helps you monitor everything with zero instrumentation or config.
Real-Time Observability with ClickHouse, Coroot, and GlassFlow
Coroot is excited to feature an editorial from GlassFlow for our first Open Source Spotlight. We hope to improve the workflow of our global community of SREs and DevOps professionals by sharing exciting projects like Glassflow, which make innovation accessible for everyone through the freedom of open source. If you have an open source or open core project you’d like to see on our blog next, send us a message!
How to Improve Uptime and Achieve Root Cause Analysis (with Open Source!)
Observability doesn’t begin and end at telemetry or your ELK stack: most open source or vendor tools require configuration, dashboard customization, and may not actually pinpoint the data you need to mitigate system risks. Coroot was designed to solve the problem of time-consuming root cause analysis: it handles the full observability journey — from collecting telemetry to turning it into actionable insights. We also strongly believe that simple observability should be an innovation everyone can afford to benefit from: which is why our software is open source.
Peacetime Observability: Spotting Risks Before They Become Incidents
Most of the time, nothing’s broken. Traffic’s flowing, alerts are quiet, and everything seems fine. That’s peacetime, when no one’s getting paged. Coroot helps in both peacetime and wartime. When things go wrong, it guides you to the root cause fast. But during peacetime, it helps you spot risks early, clean up inefficiencies, and prevent those incidents from happening in the first place.