Overview

The following are the known issues when deploying or using the integrated registry.

Image Push Errors with Scaled Registry Using Shared NFS Volume

When using a scaled registry with a shared NFS volume, you may see one of the following errors during the push of an image:

  • digest invalid: provided digest did not match uploaded content

  • blob upload unknown

  • blob upload invalid

These errors are returned by an internal registry service when Docker attempts to push the image. Its cause originates in the synchronization of file attributes across nodes. Factors such as NFS client side caching, network latency, and layer size can all contribute to potential errors that might occur when pushing an image using the default round-robin load balancing configuration.

You can perform the following steps to minimize the probability of such a failure:

  1. Ensure that the sessionAffinity of your docker-registry service is set to ClientIP:

    $ oc get svc/docker-registry --template='{{.spec.sessionAffinity}}'

    This should return ClientIP, which is the default in recent OpenShift Origin versions. If not, change it:

    $ oc patch svc/docker-registry -p '{"spec":{"sessionAffinity": "ClientIP"}}'
  2. Ensure that the NFS export line of your registry volume on your NFS server has the no_wdelay options listed. See Export Settings in the Persistent Storage Using NFS topic for details.

The guidelines for NFS are recommended to help you get started. You may switch off from NFS when moving to production.

Pull of Internally Managed Image Fails with "not found" Error

This error occurs when the pulled image is pushed to an image stream different from the one it is being pulled from. This is caused by re-tagging a built image into an arbitrary image stream:

$ oc tag srcimagestream:latest anyproject/pullimagestream:latest

And subsequently pulling from it, using an image reference such as:

internal.registry.url:5000/anyproject/pullimagestream:latest

During a manual Docker pull, this will produce a similar error:

Error: image anyproject/pullimagestream:latest not found

To prevent this, avoid the tagging of internally managed images completely, or re-push the built image to the desired namespace manually.

Image Push Fails with "500 Internal Server Error" on S3 Storage

There are problems reported happening when the registry runs on S3 storage back-end. Pushing to a Docker registry occasionally fails with the following error:

Received unexpected HTTP status: 500 Internal Server Error

To debug this, you need to view the registry logs. In there, look for similar error messages occurring at the time of the failed push:

time="2016-03-30T15:01:21.22287816-04:00" level=error msg="unknown error completing upload: driver.Error{DriverName:\"s3\", Enclosed:(*url.Error)(0xc20901cea0)}" http.request.method=PUT
...
time="2016-03-30T15:01:21.493067808-04:00" level=error msg="response completed with error" err.code=UNKNOWN err.detail="s3: Put https://s3.amazonaws.com/oso-tsi-docker/registry/docker/registry/v2/blobs/sha256/ab/abe5af443833d60cf672e2ac57589410dddec060ed725d3e676f1865af63d2e2/data: EOF" err.message="unknown error" http.request.method=PUT
...
time="2016-04-02T07:01:46.056520049-04:00" level=error msg="error putting into main store: s3: The request signature we calculated does not match the signature you provided. Check your key and signing method." http.request.method=PUT
atest

If you see such errors, contact your Amazon S3 support. There may be a problem in your region or with your particular bucket.

Image Pruning Fails

If you encounter the following error when pruning images:

BLOB sha256:49638d540b2b62f3b01c388e9d8134c55493b1fa659ed84e97cb59b87a6b8e6c error deleting blob

And your registry log contains the following information:

error deleting blob \"sha256:49638d540b2b62f3b01c388e9d8134c55493b1fa659ed84e97cb59b87a6b8e6c\": operation unsupported

It means that your custom configuration file lacks mandatory entries in the storage section, namely storage:delete:enabled set to true. Add them, re-deploy the registry, and repeat your image pruning operation.