Kubernetes in production: Why you must separate staging and prod

Key points:

• Total Blast Radius Isolation: Separating clusters ensures that aggressive testing, configuration changes, or a "broken" staging environment can never physically impact the stability or speed of your production workload.
• Hard Security Boundaries: By utilizing separate clusters, you can enforce the Principle of Least Privilege, locking down production access to a select few while giving developers the freedom to debug and iterate in staging without risking data leaks.
• Production Parity for Confidence: A staging cluster should be a "mirror" of production. Testing in a separate but identical environment allows you to catch failures, API deprecations, and scaling issues before they ever reach the end-user.

So you have a Kubernetes cluster, and you are tempted to isolate your production from staging?

If you  don’t know where to start, or have doubts about the cost, this article should help you shine a light through all of your interrogations.

What is a Kubernetes cluster?

A Kubernetes cluster is a set of nodes with a certain amount of CPU and RAM that run and manage your application workload in a resilient way. Kubernetes is ideal in case of worker node disruption. There is no need to panic; Kubernetes got you back and will keep your application up and running.

What is a staging cluster?

A staging cluster is used for iterations/testing and validation before releasing in production - to the client. The main idea behind a staging cluster is to mimic the production cluster. So it must be perfectly similar. Same Kubernetes version, number of nodes, and applications than the production.

What is a production cluster?

This is the end-user application the client has access to. It should contain stable and well-tested features.

Why you should use a different cluster for production and staging

Performance: Isolation of the production environment

• So, you can take care of testing a new version of Kubernetes in staging only without impacting the production.
• Changing some of the configurations, such as the number of nodes, can make your production slow; having a cluster dedicated for staging can ensure that you can make some changes without impacting the product speed.

Security: Lock access to the prod cluster

• You can decide to give access to the production cluster to a reduced number of people, so it reduces the risk of human error.
• If you have a set of debugging tools and framework testing in your production cluster, it can give anyone in the team access to some sensible data. Your team should do all the testing before going to production; it’s better to add those debugging tools and framework testing for your staging cluster only so you can reduce the risk of a data leak.

Productivity: Iterate faster and release with confidence

• Never be scared of doing changes on your staging cluster before releasing it in production. You will never break your production application while testing.
• Prevent failure in production before they happen 🙂

How to separate staging from production clusters with Qovery

Once you created your organization, head to the “organization settings” and select “add a cluster”.

Step 1 - Set up and deploy your staging cluster

You can start by creating a cluster called “Staging”, add your credential, choose the features you need then select “create”.

After you have entered your credential and selected “create”, you can click on the three dots on the right of your cluster and select “install”.

Your cluster should take about 30 mn to be ready. You can see the status of your cluster on the left, and a green dot should appear once your cluster is set up and deployed.

Step 2 - Set up and deploy your production cluster

The process is the same here except that you want to call your second cluster “Production” so you can recognize it quickly.

Once you have entered your credential and selected “create”, you can deploy this second cluster.

Once you have created and deployed both your staging and production clusters, you can deploy your application on both clusters; here is a tutorial that can help you get started with your first application.

How much does it cost to run multiple clusters on AWS?

To run one EKS cluster, the minimum requirement will be:

• Control-plane Kube → ~75$ per month
• 3 nodes minimum: t3a.large → $55 per instance - $165 in total per month
• Network load balancer → $30 per month

This comes up to 270$ for one EKS cluster, and using two clusters for production and staging will cost a minimum of 540$ per month.

When using a staging cluster?

If a production disruption costs you more than a cluster per month, you are better considering using a staging environment before releasing it in production. A good temporary solution is to put your staging in a production cluster if it does not take too many resources. However, it’s much better to consider using a fully dedicated staging cluster.

Wrapping Up: Your Zero-Downtime Kubernetes Checklist

Your production environment is your brand's reputation. By using two different clusters, you say goodbye to the fear of "breaking production" and gain total control over your deployment lifecycle.

Final Checklist for Isolation:

• Ensure Staging and Production have the same K8s version.
• Restrict production kubeconfig access to SRE/Lead roles.
• Use Qovery to automate the provisioning of identical environments.
• Always validate Helm chart upgrades in Staging first.

Slash Cloud Costs & Prevent Downtime

Still struggling with inefficiency, security risks, and high cloud bills? This guide cuts through the complexity with actionable best practices for production Kubernetes environments.

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