1 min read crispytechtips

[k8s] optimize workloads with pod resource recommendations

Most Kubernetes pods could be better configured in terms of resources. Unfortunately, is not so easy out-of-the-box. Robusta KRR (Kubernetes Resource Recommender) comes to help us with it.
[k8s] optimize workloads with pod resource recommendations

Intro

According to a recent Sysdig study, on average, Kubernetes clusters have:

  • 69% unused CPU
  • 18% unused memory

By right-sizing your containers with KRR, you can save an average of 69% on cloud costs.

Resource recommendations

How to deal with that?

There's a lot of solutions out there, one of them is for sure Robusta KRR (Kubernetes Resource Recommender)

Usage

screenshot.jpeg

Installation

KRR requires Prometheus and kube-state-metrics

No setup is required if you use kube-prometheus-stack or Robusta's Embedded Prometheus.

If you have a different setup, make sure the following metrics exist:

  • container_cpu_usage_seconds_total
  • container_memory_working_set_bytes
  • kube_replicaset_owner
  • kube_pod_owner
  • kube_pod_status_phase

Then follow https://github.com/robusta-dev/krr?tab=readme-ov-file#installation-methods

Published by:

Yuri Bacciarini

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