Kubernetes Best Practices to consider on 2023

Kubernetes(k8s) is one of the best container orchestration tools, you may see the adoption to it growing rapidly, why? One of the main reasons is automation. Apart from this Kubernetes provides wide range of advantages like, workload discovery, self-healing, and containerized application scaling, near future IaC.

But really how much application team using Kubernetes on production? The count may not very good, compared to adoption ratio. As still security is big concerns, it is delaying. How can we fix? Well, there are lot of best practices need to be introduced across each layer of implementation. Not only to cover security, other than that, we need to establish more best practices to have Kubernetes stability along with security.

In this article we have identifies some critical Kubernetes best practices that you can plan to Kubernetes implementation planning to improve your Kubernetes security, performance, and costs.

Best Practices

  • Always run with Stable Version

Very first best practices for any software tool are run the package with stable version, same applies to Kubernetes. What is advantage of running Kubernetes stable version? As it mostly patched for any security or performance issues. There will almost certainly be more community-based or vendor-provided support available as well. Finally, the K8s best practice allows you to avoid security, performance, and cost anomalies that could jeopardize your service delivery.

  • Yamllint

If you are developer, and you are trying to deploy a manifest, you may experience the pain.! Yes, it sometime consumes our time more than what we planned, so we may feel YAML difficult to use. Then you may pick yamllint, which helps to manage multiple documents in a single file. There are also Kubernetes-specific linters available, you can add to your IDE or pipeline or CLI. Which saves your time.

You can lint your manifests and follow best practices with kube-score. Kubeval will also lint your manifests. However, it only checks for validity. The dry-run option on kubectl in Kubernetes 1.13 allows Kubernetes to inspect but not apply your manifests. This feature allows you to validate your YAML files for K8s.

  • Versioning the config/manifests

As we are all slowly moving towards GitOps, it is best to keep all-config files, such as deployment, services, and ingress ones in your favorites’ version control system. GitHub is the most popular, open-source, and distributed version control platform for that, but others include GitLab, Bitbucket, and GoGs.

This helps to check and track what change done and who did, so it also helps on critical situation to roll back the change, re-create, or restore your cluster to ensure stability and security.

Also make sure to write declarative YAML files instead of using imperative kubectl commands like kubectl run. A declarative approach allows you to specify the desired state, and Kubernetes will figure out how to get there. This is a way will help to maintain the versioning.

  • A GitOps Workflow

GitOps is an excellent model for automating all tasks, including CI/CD pipelines, with Git serving as the single source of truth. A GitOps framework can assist you in the following ways, in addition to increasing productivity:

  1. Accelerate deployments
  2. Enhance error tracking
  3. Automate your CI/CD workflows.

Finally, using the GitOps approach simplifies cluster management and speeds up app development.

When resources are sporadic, production clusters may fail in the absence of resource limits and requests. Excess resources can be consumed by pods in a cluster, increasing your Kubernetes costs. Furthermore, if pods consume too much CPU or memory and the scheduler is unable to add new pods, nodes can crash. To avoid this case, you can implement the resources.

You are always recommended to use Namespaces, as namespaces assist teams in logically partitioning a cluster into sub-clusters. This is especially useful when you want to share a Kubernetes cluster among multiple projects or teams at the same time. Namespaces allow development, testing, and production teams to collaborate within the same cluster without overwriting or interfering with each other’s projects.

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Discuss about #Linux, #DevOps, #Docker, #kubernetes, #HowTo’s, #cloud & IT technologies like #argocd #crossplane #azure https://foxutech.com/