Troubleshooting

Most build failures are plain Docker build or startup failures. You can reproduce the build on your machine with the same context and Dockerfile:

docker build -t my-worker .   # run from build_directory if the worker is in a subdirectory
docker run --rm \
  -e MISTRAL_API_KEY \
  -e DEPLOYMENT_NAME=my-worker-local \
  my-worker

docker build -t my-worker .   # run from build_directory if the worker is in a subdirectory
docker run --rm \
  -e MISTRAL_API_KEY \
  -e DEPLOYMENT_NAME=my-worker-local \
  my-worker

MISTRAL_API_KEY is passed through from your shell. With it set, the worker connects to https://api.mistral.ai and registers its workflows for real. Use a DEPLOYMENT_NAME different from your live deployment: a local worker with the same name would steal its executions.

• The worker runs but no workflows appear — check the image's ENTRYPOINT/CMD. It must start the worker, for example python worker.py calling run_worker([...]). The platform runs the image as-is.
• The build fails — open the deployment details to read the error, then reproduce it with Test the image locally.
• Executions land on the wrong worker — two deployments with the same name steal each other's executions. Give every deployment a unique name.