observability

Metrics and traces correlation in Kiali

Metrics and traces correlation in Kiali

Metrics, traces, and logs might be the Three Pillars of Observability, as you’ve certainly already heard. This mantra helps us focus our mindset around observability, but it is not a religion. “There is so much more data that can help us have insight into our running systems,” said Frederic Branczyk at KubeCon last year.

These three kind of signals do have their specificities, but they also have common denominators that we can generalize. They could all appear on a virtual timeline and they all originate from a workload, so they are timed and sourced, which is a good start for enabling correlation. If there’s anything as important as knowing the signals that a system can emit, it’s knowing the relationships between those signals and being able to correlate one with another, even when they’re not strictly of the same nature. Ultimately, we can postulate that any sort of signal that is timed and sourced is a good candidate for correlation as well, even if we don’t have hard links between them.

Continue reading “Metrics and traces correlation in Kiali”

Share
Deploying debuginfod servers for your developers

Deploying debuginfod servers for your developers

In an earlier article, Aaron Merey introduced the new elfutils debuginfo-server daemon. With this software now integrated and released into elfutils 0.178 and coming to distros near you, it’s time to consider why and how to set up such a service for yourself and your team.

Recall that debuginfod exists to distribute ELF or DWARF debugging information, plus associated source code, for a collection of binaries. If you need to run a debugger like gdb, a trace or probe tool like perf or systemtap, binary analysis tools like binutils or pahole, or binary rewriting libraries like dyninst, you will eventually need debuginfo that matches your binaries. The debuginfod client support in these tools enables a fast, transparent way of fetching this data on the fly, without ever having to stop, change to root, run all of the right yum debuginfo-install commands, and try again. Debuginfo lets you debug anywhere, anytime.

We hope this opening addresses the “why.” Now, onto the “how.”

Continue reading “Deploying debuginfod servers for your developers”

Share
Introduction to microservices observability with Eclipse MicroProfile

Introduction to microservices observability with Eclipse MicroProfile

Microservices provide a modern approach to development, which is compliant with the cloud environment and gives us the ability to create cloud-native applications. With microservices, we promote resilience, fault tolerance, and scale; however, a microservice approach also presents different challenges than monolithic applications because of its distributed nature.

One of these challenges involves monitoring and logging, which naturally brings us to the concept of observability. In this article, we’ll look at how Eclipse MicroProfile can help you implement observability in microservices.

Continue reading “Introduction to microservices observability with Eclipse MicroProfile”

Share
Building an observability stack for automated performance tests on Kubernetes and OpenShift (part 2)

Building an observability stack for automated performance tests on Kubernetes and OpenShift (part 2)

This is the second of a series of three articles based on a session I held at Red Hat Tech Exchange in EMEA. In the first article, I presented the rationale and approach for leveraging Red Hat OpenShift or Kubernetes for automated performance testing, and I gave an overview of the setup.

In this article, we will look at building an observability stack. In production, the observability stack can help verify that the system is working correctly and performing well. It can also be leveraged during performance tests to provide insight into how the application performs under load.

An example of what is described in this article is available in my GitHub repository.

Continue reading “Building an observability stack for automated performance tests on Kubernetes and OpenShift (part 2)”

Share