Configure caches for high availability

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This topic applies to Docker Enterprise.

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If you’re deploying a DTR cache in a zone with few users and with no uptime SLAs, a single cache service is enough for you.

But if you want to make sure your DTR cache is always available to users and is highly performant, you should configure your cache deployment for high availability.

Highly-available cache

System requirements

  • Multiple nodes, one for each cache replica.
  • A load balancer.
  • Shared storage system that has read-after-write consistency.

The way you deploy a DTR cache is the same, whether you’re deploying a single replica or multiple ones. The difference is that you should configure the replicas to store data using a shared storage system.

When using a shared storage system, once an image layer is cached, any replica is able to serve it to users without having to fetch a new copy from DTR.

DTR caches support the following storage systems:

  • Alibaba Cloud Object Storage Service
  • Amazon S3
  • Azure Blob Storage
  • Google Cloud Storage
  • NFS
  • Openstack Swift

If you’re using NFS as a shared storage system, make sure the shared directory is configured with:

/dtr-cache *(rw,root_squash,no_wdelay)

This ensures read-after-write consistency for NFS.

You should also mount the NFS directory on each node where you’ll deploy a DTR cache replica.

Label the DTR cache nodes

Use SSH to log in to a manager node of the swarm where you want to deploy the DTR cache.

If you’re using UCP to manage that swarm you can also use a client bundle to configure your Docker CLI client to connect to that swarm.

Label each node that is going to run the cache replica, by running:

docker node update --label-add dtr.cache=true <node-hostname>

Configure and deploy the cache

Create the cache configuration files by following the instructions for deploying a single cache replica.

Make sure you adapt the storage object, using the configuration options for the shared storage of your choice.

Configure your load balancer

The last step is to deploy a load balancer of your choice to load-balance requests across the multiple replicas you deployed.

DTR, cache