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Скачать или смотреть How to Successfully Deploy Multi-Container Pods in Kubernetes

  • vlogize
  • 2025-04-06
  • 12
How to Successfully Deploy Multi-Container Pods in Kubernetes
Deploying multi-container pod in Kuberneteskuberneteskubernetes pod
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Описание к видео How to Successfully Deploy Multi-Container Pods in Kubernetes

Master the art of deploying multi-container pods in Kubernetes with this comprehensive guide, troubleshooting common errors and following step-by-step solutions.
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This video is based on the question https://stackoverflow.com/q/73647344/ asked by the user 'pysquirrel' ( https://stackoverflow.com/u/19948542/ ) and on the answer https://stackoverflow.com/a/73647711/ provided by the user 'Taimoor Mirza' ( https://stackoverflow.com/u/4978880/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Deploying multi-container pod in Kubernetes

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The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

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How to Successfully Deploy Multi-Container Pods in Kubernetes

Deploying applications in Kubernetes can sometimes be complex, especially when it comes to running multiple containers in a single pod. If you’re new to Kubernetes and find yourself facing the CrashLoopBackOff error while trying to run two containers in a pod, you’re not alone. In this post, we’ll break down the issue you might encounter, provide a clear solution, and guide you through the configuration process step-by-step.

The Problem: CrashLoopBackOff Error

As a beginner, you might have attempted to launch two containers in a Kubernetes pod using the following YAML configuration:

[[See Video to Reveal this Text or Code Snippet]]

Unfortunately, running this configuration likely results in the CrashLoopBackOff error. This error typically indicates that the container is crashing and failing to start properly, prompting Kubernetes to retry.

Analyzing the CrashLoopBackOff

When you check the pod’s status using kubectl describe pod, you may see something similar to this:

[[See Video to Reveal this Text or Code Snippet]]

This signifies that Kubernetes is attempting to restart the busybox container multiple times because it’s not running as expected.

The Solution: Adding a Running Process

The root cause of your issue lies in the configuration of the busybox container. The BusyBox image does not include a default process that runs indefinitely, which is needed to keep the container alive.

Configuring the BusyBox Container

To resolve the issue, you should add a command that keeps the BusyBox container running. Here’s how you can modify your YAML configuration:

[[See Video to Reveal this Text or Code Snippet]]

Explanation of Changes

Command Addition: The key addition here is the command attribute in your BusyBox container definition. By using ["sh", "-c", "sleep 3600"], you instruct the BusyBox container to execute a shell command that sleeps for 3600 seconds (or 1 hour). This keeps the container alive for an extended period, avoiding the CrashLoopBackOff error.

Final Thoughts

Running multiple containers in a single pod is not only feasible but often one of the best practices for deploying microservices in Kubernetes. By ensuring that each container runs a process that doesn’t terminate, you can maintain the health of your pods and streamline your deployments.

In summary, if you find yourself getting the CrashLoopBackOff error with a multi-container setup, remember to check the container configurations and ensure that each container is set up to keep running. With the adjusted YAML configuration provided, you should observe your pod running smoothly.

Don’t hesitate to reach out if you have any further questions or run into additional issues. Happy Kubernetes deploying!

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