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Five Common Mistakes Made by Kubernetes Beginners


Kubernetes has become the de-facto standard for container orchestration as it comes with a powerful and robust feature set to accommodate any orchestration need. However, this extensive usage has also made Kubernetes a relatively complex solution to configure and manage.  

If you are starting your K8s journey, getting into Kubernetes orchestration may seem like a daunting task. However, you can grasp K8s in no time with a little bit of dedication and effort. This article will focus on some common mistakes users make when interacting with Kubernetes to help you in this matter.

5 Common Kubernetes Mistakes

Incorrect Labels and Selectors

Labels provide a way to add identifiable metadata to Kubernetes objects, while selectors (label selectors) are used to identify a set of objects using these predefined labels. From services to replication, controllers use labels and selectors to identify which resource they should be associated with, such as Pods.

Thus it is crucial to configure correct labels and selectors throughout all the Kubernetes objects. Otherwise, it can lead to different types of errors like traffic routing issues by targeting inaccessible or incorrect Pods and scaling issues due to incorrect policy targets.

Using the Default Namespace for all Objects

Namespaces provide users with a mechanism to group different kinds of non-global resources such as deployments and services. It is ideal for resource separation if multiple products or teams interact with a single Kubernetes cluster. Namespaces also allow the easy application of different policies at a namespace level.

While using the default namespace is acceptable in a test environment, the best practice is to use a different namespace. It provides users with a proper isolated environment without affecting unrelated services or objects within the cluster. Proper namespace usage also eliminates the risk of running Kubernetes commands on the default namespace, impacting other resources.

Inadequate Testing on a Kubernetes Environment

Testing is a core part of any software development. It should not be applied only to the application but also to the environment as a whole to mitigate application, configuration, or infrastructure issues in the production environments.

Testing within an identical environment to production allows users to capture most configuration or infrastructure errors beforehand. Additionally, it helps to easily capture hard-to-identify errors such as Linux segmentation faults in containers, resulting in Kubernetes exit code 139.

However, testing should not be rushed and should be appropriately conducted as a part of the overall software delivery process to deliver an error-free container to the production cluster.

Inefficient Resource Management

Users often ignore or forget to set the request and limits in the K8s configuration files for CPU and memory. This mistake can lead to resource starvation and directly impact the performance of the application. 

Besides, incorrectly configured limits can lead to resource wastage by unnecessarily allocating resources to a container while neglecting to provide the necessary resources to another. In both cases, it can impact the application performance and lead to errors such as OOMKilled due to incorrect memory allocation.

Therefore, the ideal way to manage the underlying resources will be to configure resource quotas and limit ranges at a namespace level and utilize horizontal and vertical auto-scaling tools to manage the overall resource usage within a cluster. All these things can lead to a better-optimized cluster environment, ultimately leading to better application performance.

Improper Use of Liveness and Readiness Probes

Health checks are crucial for ensuring the health of an application. Not implementing health checks within the containers is detrimental to the overall management of the Kubernetes cluster.

One common mistake made by users is pointing both the liveness and readiness probes to a single HTTP endpoint, which defeats the purpose of these two different probe types. The Liveness probe is used to determine the application’s health, and if it fails, the pod will be restarted. On the other hand, the Readiness probe is used to indicate to Kubernetes that the container is ready to serve traffic. Kubernetes will block any traffic if the readiness probe indicates a failure. Unlike the liveness probe, failures in the readiness probe do not affect the pod itself.

One key consideration when implementing these probes is to ensure that they are pointed at endpoints that are not dependent on other services. The reason is that an issue in a dependency can cause a false indication in the probe, leading to unexpected behavior.


Kubernetes will have a longer learning curve, and there are many different implementations of Kubernetes itself due to its constantly evolving nature and widespread adoption. However, most of the core features of Kubernetes are ubiquitous regardless of the implementation. Thus gaining proper knowledge of the Kubernetes fundamentals are crucial to succeed in any K8s environment. With a proper understanding, beginners can easily avoid common mistakes mentioned above and start managing Kubernetes environments while adhering to the industry-accepted best practices.

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