DVC Status — Is DVC Down?

API Error (500 / 502 / 503)

DVC is returning API errors (HTTP 500, 502, or 503), indicating the platform's backend is experiencing issues. MLOps platforms handle complex workloads — model training, experiment tracking, pipeline orchestration — making server errors particularly disruptive to active workflows.

Pipeline / Training Run Failed

Your ML pipeline or training run on DVC has failed unexpectedly. This can be caused by platform-side issues (compute unavailability, orchestration bugs) or configuration problems on your end. Distinguishing between the two is key to a fast resolution.

Model Registry / Artifact Store Error

You cannot push, pull, or access model artifacts in DVC's model registry. This blocks model deployment and versioning workflows. Registry errors are often caused by storage backend issues or permission problems.