In this article we are going to consider the two most common methods for Autoscaling in EKS cluster: The Horizontal Pod Autoscaler or HPA is a Kubernetes component that automatically scales your service based on metrics such as CPU utilization or others, as defined through the Kubernetes metric server. The HPA scales the pods in either a deployment or replica set, and is implemented as a Kubernetes API resource and a controller.

This article will focus on using fluentd and ElasticSearch (ES) to log for Kubernetes (k8s). This article contains useful information about microservices architecture, containers, and logging. Additionally, we have shared code and concise explanations on how to implement it, so that you can use it when you start logging in your own apps. ‍Useful Terminology.

Lately we’ve been working on improving different parts of the Mattermost server, including our monitoring and observability capabilities. We’ve been using Prometheus and Grafana to monitor our cluster for a while now, and you can read this great post where my colleague Stylianos explains how we have them working for our multi-cluster environment.