Fixing GPUStack Startup: Custom Cache-Dir Issues

by Alex Johnson 49 views

It can be quite frustrating when you're trying to get your powerful GPUStack environment up and running, only to be met with errors. One common point of confusion, especially when you're trying to customize its behavior, is when GPUStack fails to start with a custom cache-dir. This article dives deep into this specific problem, exploring why it might happen and how you can effectively troubleshoot and resolve it. We'll walk through the typical scenarios, interpret the logs, and provide actionable steps to get your GPUStack instance running smoothly with your desired cache directory. So, if you've encountered the dreaded RuntimeError: Port 80 is not healthy or not listening or similar, stick around, because we're about to unravel this mystery together!

Understanding the GPUStack Docker Command

Before we dive into troubleshooting, let's take a moment to understand the command you're using to start GPUStack with a custom cache directory. This is crucial because a small typo or a misunderstanding of a flag can lead to unexpected issues. Here's a breakdown of the command provided:

sudo docker run -d --name gpustack \
    --restart unless-stopped \
    --network=host \
    -v /data/gpustack_cache:/data/gpustack_cache \
    gpustack/gpustack:main \
    -d \
    --bootstrap-password 123456 \
    --cache-dir /data/gpustack_cache
  • -d: This flag runs the container in detached mode, meaning it will run in the background. This is standard for most server applications.
  • --name gpustack: Assigns a name to your container, making it easier to manage.
  • --restart unless-stopped: Ensures that Docker will automatically restart the container if it crashes or if the Docker daemon restarts, unless you explicitly stop it.
  • --network=host: This is an important one. It tells Docker to use the host's network stack directly. This means the container will share the same IP address and ports as your host machine. While convenient, it can also lead to port conflicts if other applications on your host are already using the ports GPUStack needs (like port 80 in this case).
  • -v /data/gpustack_cache:/data/gpustack_cache: This is a volume mount. It maps a directory on your host machine (/data/gpustack_cache) to a directory inside the container (/data/gpustack_cache). This is where GPUStack is intended to store its cache files. Ensuring this directory exists on your host and has the correct permissions is vital.
  • gpustack/gpustack:main: Specifies the Docker image and tag to use.
  • -d: This flag within the command arguments for GPUStack itself likely refers to running it in daemon mode inside the container, which is typical for server processes.
  • --bootstrap-password 123456: Sets the initial password for bootstrapping GPUStack. Keep this secure in a real-world scenario!
  • --cache-dir /data/gpustack_cache: This explicitly tells GPUStack inside the container where to store its cache files. It's essential that this path matches the target of your volume mount.

By understanding each part of this command, we can better pinpoint where things might be going wrong when GPUStack fails to start. The interaction between Docker's volume mounting and the application's internal configuration is often where these issues hide.

Decoding the Error Logs: "Port 80 is not healthy or not listening"

When GPUStack fails to start with a custom cache-dir, the traceback often includes a critical message: RuntimeError: Port 80 is not healthy or not listening. This error, along with the preceding ConnectionRefusedError: [Errno 111] Connect call failed ('127.0.0.1', 80), tells us a story. Let's break it down:

  1. ConnectionRefusedError: [Errno 111] Connect call failed ('127.0.0.1', 80): This is the fundamental issue. The GPUStack application, when starting up, tries to establish a connection to a service on 127.0.0.1 (localhost) on port 80. The ConnectionRefusedError means that there was no process listening on that specific IP address and port to accept the connection. It's like trying to call a phone number that isn't being answered.

  2. RuntimeError: Port 80 is not healthy or not listening: This is GPUStack's way of reporting the failure after multiple attempts. The tenacity library, used for retries, has tried to connect to port 80 several times (you can see the attempt 1 through attempt 29 logs) and each time failed because nothing was listening. Eventually, after exhausting its retries, it raises this RuntimeError.

  3. asyncio.exceptions.CancelledError: This often appears later in the log. It indicates that the asynchronous tasks within GPUStack were cancelled, likely because the main process failed to start correctly due to the port issue. It's a cascading effect rather than the root cause.

Why is Port 80 so important? In your docker run command, you've specified --network=host. This means the container uses your host's network. Port 80 is the standard HTTP port, and GPUStack, by default, tries to expose its main API and services on this port. The error suggests that either:

  • Another service is already using port 80 on your host machine. This is a very common cause. If you have a web server (like Apache or Nginx), another container, or any other application running and bound to port 80, GPUStack won't be able to use it, and its startup checks will fail.
  • GPUStack's internal server (like Uvicorn or a similar ASGI server) failed to bind to port 80. This could be due to permission issues, conflicts, or a bug within the container.
  • The --network=host configuration itself is problematic in this specific environment or with this version of GPUStack. While powerful, it bypasses Docker's network isolation and can be more prone to conflicts.

Understanding this error is the first step. It tells us the problem isn't necessarily with the cache directory itself, but with the network accessibility of the core GPUStack service.

Common Causes and Solutions

When GPUStack fails to start with a custom cache-dir, and you're seeing the