Global Clusters

Global Clusters


Swift’s default configuration is currently designed to work in a single region, where a region is defined as a group of machines with high-bandwidth, low-latency links between them. However, configuration options exist that make running a performant multi-region Swift cluster possible.

For the rest of this section, we will assume a two-region Swift cluster: region 1 in San Francisco (SF), and region 2 in New York (NY). Each region shall contain within it 3 zones, numbered 1, 2, and 3, for a total of 6 zones.

Configuring Global Clusters


The proxy-server configuration options described below can be given generic settings in the [app:proxy-server] configuration section and/or given specific settings for individual policies using Per policy configuration.


This setting, combined with sorting_method setting, makes the proxy server prefer local backend servers for GET and HEAD requests over non-local ones. For example, it is preferable for an SF proxy server to service object GET requests by talking to SF object servers, as the client will receive lower latency and higher throughput.

By default, Swift randomly chooses one of the three replicas to give to the client, thereby spreading the load evenly. In the case of a geographically-distributed cluster, the administrator is likely to prioritize keeping traffic local over even distribution of results. This is where the read_affinity setting comes in.


sorting_method = affinity
read_affinity = r1=100

This will make the proxy attempt to service GET and HEAD requests from backends in region 1 before contacting any backends in region 2. However, if no region 1 backends are available (due to replica placement, failed hardware, or other reasons), then the proxy will fall back to backend servers in other regions.


sorting_method = affinity
read_affinity = r1z1=100, r1=200

This will make the proxy attempt to service GET and HEAD requests from backends in region 1 zone 1, then backends in region 1, then any other backends. If a proxy is physically close to a particular zone or zones, this can provide bandwidth savings. For example, if a zone corresponds to servers in a particular rack, and the proxy server is in that same rack, then setting read_affinity to prefer reads from within the rack will result in less traffic between the top-of-rack switches.

The read_affinity setting may contain any number of region/zone specifiers; the priority number (after the equals sign) determines the ordering in which backend servers will be contacted. A lower number means higher priority.

Note that read_affinity only affects the ordering of primary nodes (see ring docs for definition of primary node), not the ordering of handoff nodes.


This setting makes the proxy server prefer local backend servers for object PUT requests over non-local ones. For example, it may be preferable for an SF proxy server to service object PUT requests by talking to SF object servers, as the client will receive lower latency and higher throughput. However, if this setting is used, note that a NY proxy server handling a GET request for an object that was PUT using write affinity may have to fetch it across the WAN link, as the object won’t immediately have any replicas in NY. However, replication will move the object’s replicas to their proper homes in both SF and NY.

One potential issue with write_affinity is, end user may get 404 error when deleting objects before replication. The write_affinity_handoff_delete_count setting is used together with write_affinity in order to solve that issue. With its default configuration, Swift will calculate the proper number of handoff nodes to send requests to.

Note that only object PUT/DELETE requests are affected by the write_affinity setting; POST, GET, HEAD, OPTIONS, and account/container PUT requests are not affected.

This setting lets you trade data distribution for throughput. If write_affinity is enabled, then object replicas will initially be stored all within a particular region or zone, thereby decreasing the quality of the data distribution, but the replicas will be distributed over fast WAN links, giving higher throughput to clients. Note that the replicators will eventually move objects to their proper, well-distributed homes.

The write_affinity setting is useful only when you don’t typically read objects immediately after writing them. For example, consider a workload of mainly backups: if you have a bunch of machines in NY that periodically write backups to Swift, then odds are that you don’t then immediately read those backups in SF. If your workload doesn’t look like that, then you probably shouldn’t use write_affinity.

The write_affinity_node_count setting is only useful in conjunction with write_affinity; it governs how many local object servers will be tried before falling back to non-local ones.


write_affinity = r1
write_affinity_node_count = 2 * replicas

Assuming 3 replicas, this configuration will make object PUTs try storing the object’s replicas on up to 6 disks (“2 * replicas”) in region 1 (“r1”). Proxy server tries to find 3 devices for storing the object. While a device is unavailable, it queries the ring for the 4th device and so on until 6th device. If the 6th disk is still unavailable, the last replica will be sent to other region. It doesn’t mean there’ll have 6 replicas in region 1.

You should be aware that, if you have data coming into SF faster than your replicators are transferring it to NY, then your cluster’s data distribution will get worse and worse over time as objects pile up in SF. If this happens, it is recommended to disable write_affinity and simply let object PUTs traverse the WAN link, as that will naturally limit the object growth rate to what your WAN link can handle.

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