Docker runtimeerror: can’t start new thread

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When encountering the “docker runtimeerror: can’t start new thread” error, it means that the Docker daemon has reached its maximum limit of running threads or processes. This error typically occurs when the system running Docker has very limited resources or when certain applications or processes are consuming a large number of threads.

Possible Solutions:

1. Upgrade System Resources: If the system running Docker has limited resources, such as CPU or memory, consider upgrading them to handle more concurrent threads.
2. Limit Concurrent Containers: Docker allows running multiple containers simultaneously, which can consume a large number of threads. Consider limiting the number of containers or optimizing the application architecture to reduce the required number of threads.
3. Tune Docker Daemon Configuration: Inspect the Docker daemon configuration file (usually located at /etc/docker/daemon.json) and make changes to the “max-concurrent-downloads” and “max-concurrent-uploads” values to limit simultaneous downloads and uploads, respectively. For example:

{
  "max-concurrent-downloads": 10,
  "max-concurrent-uploads": 5
}

4. Troubleshoot Resource-Intensive Applications: Identify applications or processes running inside the Docker containers that are consuming a large number of threads. Optimize or refactor those applications to reduce the thread requirements.
5. Monitor System Resource Usage: Use monitoring tools to track resource usage, such as CPU, memory, and threads, to identify any abnormalities or excessive consumption. Adjust the system resources accordingly or optimize resource-intensive applications.

Example:

Let’s consider an example where the Docker host system has limited CPU and memory resources. By upgrading the system resources, you can effectively handle more concurrent threads without encountering the “docker runtimeerror: can’t start new thread” error. Additionally, monitoring tooling can help identify resource-intensive containers or processes that require optimization.

Remember to always monitor the system and adjust its resources accordingly to ensure smooth operation and prevent resource exhaustion.