Docker Container Exits with Code 137: A Comprehensive Guide to Diagnosing and Troubleshooting

Introduction

Docker containers have revolutionized the way we develop, deploy, and manage applications. However, like any other technology, Docker containers can sometimes behave unexpectedly, and one common issue is when a container exits with code 137. This error code can be frustrating to diagnose, especially for those new to Docker. In this article, we'll delve into the world of Docker containers, explore the reasons behind exit code 137, and provide a comprehensive guide on how to diagnose and troubleshoot this issue.

Understanding Exit Code 137

Exit code 137 is a special code in Docker that indicates the container was killed by the Docker daemon, usually due to a resource limitation or constraints imposed by the system. This code is often seen when the container exceeds its allocated resources, such as memory or CPU, causing the Docker daemon to terminate it.

To understand this better, let's take a look at how Docker manages resources. By default, Docker containers share the same kernel as the host system and run as a process on the host. This means that containers are subject to the same resource constraints as any other process on the system.

1# Check the current memory limit for a container
2docker inspect -f '{{ .HostConfig.Memory }}' <container_name>

In the above command, replace <container_name> with the name of your container. This command uses the docker inspect command to fetch the memory limit configured for the container.

Identifying the Cause

To diagnose the issue, we need to identify the cause of the exit code 137. Here are a few common reasons:

• Out-of-Memory (OOM) Errors: When a container consumes more memory than allocated, the Docker daemon terminates it to prevent the system from running out of memory.
• CPU Constraints: If a container exceeds its allocated CPU resources, the Docker daemon may terminate it to prevent overloading the system.
• System Resource Constraints: In some cases, the system itself may be running low on resources, causing the Docker daemon to terminate containers to free up resources.

Checking Container Logs

One of the first steps in diagnosing the issue is to check the container logs. Docker provides a convenient way to view container logs using the docker logs command.

1# View the logs for a container
2docker logs <container_name>

Replace <container_name> with the name of your container. This command will display the latest logs from the container, which can provide valuable information about what happened before the container exited.

Checking System Logs

In addition to container logs, it's also essential to check system logs for any errors or warnings related to the Docker daemon or the container.

1# Check system logs for Docker-related errors
2sudo journalctl -u docker

On systems using systemd, the above command will display the latest logs from the Docker daemon, which can provide information about any issues encountered while running containers.

Diagnosing OOM Errors

Out-of-Memory (OOM) errors are a common cause of exit code 137. To diagnose OOM errors, you can use the docker stats command to monitor container memory usage.

1# Monitor container memory usage
2docker stats <container_name>

This command will display real-time statistics about the container's memory usage, which can help you identify if the container is consuming excessive memory.

Configuring Memory Limits

To prevent OOM errors, you can configure memory limits for your containers using the --memory flag when running the container.

1# Run a container with a memory limit
2docker run -it --memory 512m <image_name>

In this example, the container is limited to 512 MB of memory. If the container exceeds this limit, the Docker daemon will terminate it to prevent the system from running out of memory.

Diagnosing CPU Constraints

CPU constraints can also cause exit code 137. To diagnose CPU constraints, you can use the docker stats command to monitor container CPU usage.

1# Monitor container CPU usage
2docker stats <container_name>

This command will display real-time statistics about the container's CPU usage, which can help you identify if the container is consuming excessive CPU resources.

Configuring CPU Limits

To prevent CPU constraints, you can configure CPU limits for your containers using the --cpus flag when running the container.

1# Run a container with a CPU limit
2docker run -it --cpus 2 <image_name>

In this example, the container is limited to 2 CPU cores. If the container exceeds this limit, the Docker daemon will terminate it to prevent overloading the system.

Best Practices and Optimization Tips

To prevent exit code 137 and ensure smooth operation of your Docker containers, follow these best practices and optimization tips:

• Monitor Container Resources: Regularly monitor container resources using the docker stats command to identify potential issues before they cause problems.
• Configure Resource Limits: Configure memory and CPU limits for your containers to prevent them from consuming excessive resources.
• Optimize Container Images: Optimize your container images to reduce their size and improve performance.
• Use Docker Compose: Use Docker Compose to manage and orchestrate your containers, which can help you scale and manage resources more efficiently.

Conclusion

Exit code 137 can be a frustrating issue to diagnose and troubleshoot, but by following the steps outlined in this article, you can identify and fix the underlying issues. Remember to monitor container resources, configure resource limits, optimize container images, and use Docker Compose to manage and orchestrate your containers. By following these best practices and optimization tips, you can ensure smooth operation of your Docker containers and prevent exit code 137.