5 Kubernetes Best Practices You Need To Know in 2026

Kubernetes gives you incredible power but without the right practices, that power can turn into complexity very fast. If you’re just getting started or already running workloads in production, the difference between a smooth experience and constant fighting often comes down to a few decisions.

Our latest blog walks you through some of the best Kubernetes practices that help you build systems that scale naturally, stay reliable under pressure and avoid unnecessary costs. If you want Kubernetes to work for you rather than against you, these are the fundamentals you need to understand and apply early.

5 Kubernetes Best Practices You Need To Know 

Check out the best practices for Kubernetes below:

1. Define Health Checks with Liveness, Readiness and Startup Probes

One of the most overlooked but important Kubernetes practices is properly defining liveness and readiness probes. Kubernetes is excellent at keeping applications running but it can only react to problems it can detect. Health checks are how you teach Kubernetes what “healthy” actually means for your workloads.

Readiness probes tell Kubernetes when a pod is ready to receive traffic. If your application is starting up, waiting for a dependency or temporarily unable to serve requests, the readiness probe ensures traffic is stopped without killing the pod. This prevents users from hitting half-initialised or unhealthy services and improves overall reliability.

Liveness probes serve a different purpose. They help Kubernetes detect when an application is stuck or no longer making progress and needs to be restarted. This allows Kubernetes to automatically recover from issues like deadlocks or unrecoverable error states, without relying on manual intervention.

Some applications require additional time during their first startup or initialisation. In these cases, configuring a liveness probe can be tricky: aggressive settings may cause Kubernetes to restart the pod before it has finished starting, while relaxed settings slow down recovery from real failures. This is where startup probes are useful.

A startup probe uses the same HTTP, TCP, or command check as a liveness probe, but is allowed to fail for a longer period. By setting it failureThreshold × periodSeconds to cover the worst-case startup time, you give the application time to initialise properly. Once the startup probe succeeds, Kubernetes begins evaluating the liveness and readiness probes as usual.

2. Set Up Resource Requests and Limits

One of the most common mistakes when running applications on Kubernetes is not being explicit about CPU and memory requirements. Without defined resource requests, Kubernetes schedules workloads without any guaranteed capacity which can easily lead to performance issues once nodes become busy.

Resource requests specify the minimum CPU and memory a container needs to run reliably. The scheduler uses these values to place pods on nodes with enough available capacity, reducing the risk of contention and unpredictable behaviour. Resource limits, on the other hand, define how much a container is allowed to consume at most.

It’s important to understand how limits behave at runtime. When a container exceeds its CPU limit, it is throttled. When it exceeds its memory limit, it is terminated with an OOM kill and restarted. Setting these values correctly is essential to avoid unexpected slowdowns or crash loops.

3. Use Role-Based Access Control (RBAC)

The way your Kubernetes environment grows, the number of people and systems interacting with it grows too. Without clear access boundaries, it’s easy for mistakes to happen and sometimes with serious consequences. Role-Based Access Control (RBAC) helps you define who can do what and just as importantly, who shouldn’t.

RBAC allows you to grant permissions based on roles rather than individuals. Instead of giving broad access to the cluster, you assign only the permissions someone needs to perform their job. This reduces the risk of accidental changes, misconfigurations or deletions that can impact running workloads.

4. Use Labels and Annotations Consistently

As your Kubernetes environment grows, understanding what’s running in your cluster becomes just as important as running it. Labels and annotations help you organise, identify and add context to your resources, making your cluster easier to manage and reason about over time.

Labels are used for grouping and selecting resources. They allow you to answer questions like: Which pods belong to this application? Which resources are part of the same environment or team? When labels are applied consistently, everyday tasks such as monitoring, scaling and troubleshooting become far simpler and more reliable.

Annotations serve a different but equally important purpose. They store additional, non-identifying information such as ownership details, deployment context or links to documentation, that tools and humans can reference without affecting how resources are selected or grouped. This extra context becomes even more important when systems and teams interact with the cluster.

For beginners, consistency is the best practice. Inconsistent or ad-hoc labelling quickly leads to confusion and manual work. For production workloads, consistent labels and annotations improve automation and cost visibility by enabling tooling to understand your resources correctly.

5. Use Namespaces

As soon as you run more than one application in a Kubernetes cluster, things can start to feel crowded. Namespaces by default are grouping mechanism, so you don’t need separate clusters for every workload.

Namespaces let you organise resources by application, team, environment or purpose. This makes it much easier to understand what belongs where and reduces the risk of accidental changes to the wrong resources by working within a clearly defined scope.

On their own, namespaces don’t provide isolation or enforce resource limits. However, when combined with ResourceQuotas, LimitRanges, access controls like RBAC and NetworkPolicies, namespaces help prevent one team or workload from consuming more than its fair share of cluster resources or communicating with resources they shouldn’t.

Related Read: Setting Up Kubernetes Clusters on Hyperstack

Conclusion

Kubernetes best practices are what turn a cluster from something that merely runs into something that runs reliably. These practices not only reduce the operational friction and stability but also help you control costs as your workloads grow.

However, these best practices work best when paired with the right infrastructure. Hyperstack On-Demand Kubernetes provides a seamless way to run Kubernetes on AI-optimised, GPU-enabled infrastructure without the operational burden. With fast cluster provisioning, built-in GPU support and scalable node groups, you can focus on building and running workloads instead of managing infrastructure.

Launch Hyperstack On-Demand Kubernetes today and put these practices into action.

Try Hyperstack On-Demand Kubernetes 

FAQs

What are Kubernetes' best practices?

For beginners, key Kubernetes best practices include setting resource requests and limits, implementing Role-Based Access Control (RBAC), applying consistent labels and annotations and using namespaces. These practices help you manage workloads efficiently, reduce errors and improve reliability as your cluster grows.

Why are resource requests and limits important in Kubernetes?

Resource requests define the minimum CPU and memory your workloads need, while limits cap their maximum usage. Setting these ensures fair resource distribution, prevents application crashes, improves reliability and helps control operational costs.

What is Role-Based Access Control (RBAC) in Kubernetes?

RBAC allows you to assign permissions based on roles rather than individuals. It ensures that team members and systems only have access to what they need, reducing the risk of accidental changes, misconfigurations and security issues in your cluster.

How do labels and annotations help manage Kubernetes resources?

Labels help group and select resources, making monitoring, scaling, and troubleshooting simpler. Annotations provide additional context, like ownership or deployment information, without affecting resource selection. Consistent use improves automation, observability and operational efficiency.

What are namespaces in Kubernetes and why should I use them?

Namespaces separate workloads within the same cluster, allowing you to logically group applications, teams, or environments. They prevent accidental interference between workloads, improve access control and make large clusters easier to manage.