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As a DevOps or SRE, you likely monitor dozens of applications and services with the goal of keeping them up and running all the time. To do so effectively, you probably rely on alerts from Prometheus and similar systems to get notifications about important issues. But all too often those alerts can be noisy and instead of trusting those alerts to tell you something important, you find yourself ignoring them. When this happens, you and your team can miss out on critical alerts.

This month we released composable dashboards in the UI and other highly-requested features. Join us, on October 01st - We're doing a webinar with the author of the most influential engineering-leadership book in the past decade. Don't miss it!

Prometheus is one of the most used monitoring tools. On Kubernetes, Prometheus is installed with many other components. Most people use all these components without understanding each one. A Helm chart called Kube Prometheus stack is used widely to install Prometheus on Kubernetes. 

Millions of developers write PromQL queries and build custom Grafana dashboards for Kubernetes. And everyone uses the same underlying metrics from node-exporter, kubelet, and kube-state-metrics. Unfortunately, there are some little-known pitfalls that many people don’t know how to avoid. In this post, I’ll troubleshoot a simple-looking Prometheus query for Kubernetes that is supposed to return a pod’s memory usage.

We will deploy an ArgoCD Application Declaratively, using the pure GitOps approach. When doing declarative ArgoCD Deployments, your Argo CD projects and applications will be defined as Kubernetes manifest files. Nothing will be defined in the ArgoCD UI.

What can we learn about Kubernetes from the history of Linux?

It's time for the term "container orchestrator" to die.

What is the Kubernetes way of thinking?

Top 5 tools to use alongside Helm

Updates to our benchmark on Kubernetes Node Efficiency

How much overhead do Kubernetes providers take from each node?

What are PodSecurityStandards and how do they differ from the now-deprecated PodSecurityPolicies?

Prometheus configurations are made using the prometheus.yml and individual rule files. But that's not the case when using a Helm chart. So where do you configure your alerts and rules?

How is KubeWatch used and what's new in version 2.0.0?

Most people are familiar with CrashLoopBackOffs, but there are actually many ways a pod can unexpectedly stop running. Here are the top four..

How do containers actually work? Most people think chroot is involved, but that's not quite right!

Everyone wants high utilization and high reliability. The hard truth about Kubernetes is that you need to pick one or the other.

On Kubernetes, the best practice is to set memory limit=request. This surprises many people, especially because we recommend not setting Kubernetes CPU limits altogether! Here's everything to know when setting a Kubernetes memory limit.

Working with multiple clusters is always a challenge. It’s too easy to run a command on the wrong cluster.

How can you show a product's value, when there is nothing to see?

Many people think you need CPU limits on Kubernetes but this isn't true. In most cases, Kubernetes CPU limits do more harm than help. In fact, they're the number one cause of Kubernetes CPU throttling.

In this article, we will show how to expose applications running in Kubernetes Pods to other applications inside the cluster and the external world

In this post, I'll walk through the arguments and answer. I'll also explain you when you do and don't need Kubernetes.

Its human-friendly syntax has fueled the widespread use of YAML in configuration files. In particular, a thorough understanding of handling these files is helpful if you work with Kubernetes.

Here is a common Python mistake we see in PRs for robusta.dev on GitHub

Kubernetes is a powerful container orchestrator. However, the real power of Kubernetes is the ability to expand it's core functionality.

Don’t get me wrong: Prometheus is awesome, but having too many alerts is not awesome...

The story behind WhyProfiler

It's the first thing everyone notices. Our home page says it takes 97.68 seconds to install our open source. Why? How did we reach that oddly specific number?

Why and how to audit Kubernetes changes (updated)