In this article, we will look at what the Kubernetes metrics server is and what it is used for. We will also learn how to set up a metrics server and use it to monitor Kubernetes metrics. Finally, we will explore how to use hosted Graphite by MetricFire for monitoring Kubernetes metrics.

Observability has gained a lot of momentum and is now rightly a central component of the microservices landscape: It’s an important part of the cloud native world where you may have many microservices deployed on a production Kubernetes cluster, and a need to monitor these microservices keeps rising. In production, quickly finding failures and fixing them is crucial. As the name suggests, observability plays an important role in this failure discovery.

When running a cloud service, it’s never good for customers to be the first people noticing an issue. It happened to our customers over the course of a few months, and we began to accumulate a series of reports of unpredictable start-up times for Docker jobs. At first the reports were rare, but the frequency began to increase. Jobs with high parallelism were disproportionately represented in the reports.

Docker is a high-level virtualization platform that lets you package software as isolated units called containers. Containers are created from images that include everything needed to run the packaged workload, such as executable binaries and dependency libraries. Images are defined in Dockerfiles. These resemble sequential scripts that are executed to assemble an image.

It can be difficult to comprehend and successfully scale your services as modern orchestrated settings grow larger and more sophisticated. Container monitoring allows you to see the health and performance of your dynamic container infrastructure in real-time. Container monitoring is the practice of collecting and analyzing performance metrics to track the performance of containerized applications built on cloud-based microservices.