Maintenance

Overview

An etcd cluster needs periodic maintenance to remain reliable. Depending on an etcd application’s needs, this maintenance can usually be automated and performed without downtime or significantly degraded performance.

All etcd maintenance manages storage resources consumed by the etcd keyspace. Failure to adequately control the keyspace size is guarded by storage space quotas; if an etcd member runs low on space, a quota will trigger cluster-wide alarms which will put the system into a limited-operation maintenance mode. To avoid running out of space for writes to the keyspace, the etcd keyspace history must be compacted. Storage space itself may be reclaimed by defragmenting etcd members. Finally, periodic snapshot backups of etcd member state makes it possible to recover any unintended logical data loss or corruption caused by operational error.

Raft log retention

etcd --snapshot-count configures the number of applied Raft entries to hold in-memory before compaction. When --snapshot-count reaches, server first persists snapshot data onto disk, and then truncates old entries. When a slow follower requests logs before a compacted index, leader sends the snapshot forcing the follower to overwrite its state.

Higher --snapshot-count holds more Raft entries in memory until snapshot, thus causing recurrent higher memory usage. Since leader retains latest Raft entries for longer, a slow follower has more time to catch up before leader snapshot. --snapshot-count is a tradeoff between higher memory usage and better availabilities of slow followers.

Since v3.2, the default value of --snapshot-count has changed from from 10,000 to 100,000.

In performance-wise, --snapshot-count greater than 100,000 may impact the write throughput. Higher number of in-memory objects can slow down Go GC mark phase runtime.scanobject, and infrequent memory reclamation makes allocation slow. Performance varies depending on the workloads and system environments. However, in general, too frequent compaction affects cluster availabilities and write throughputs. Too infrequent compaction is also harmful placing too much pressure on Go garbage collector. See https://www.slideshare.net/mitakeh/understanding-performance-aspects-of-etcd-and-raft for more research results.

History compaction: v3 API Key-Value Database

Since etcd keeps an exact history of its keyspace, this history should be periodically compacted to avoid performance degradation and eventual storage space exhaustion. Compacting the keyspace history drops all information about keys superseded prior to a given keyspace revision. The space used by these keys then becomes available for additional writes to the keyspace.

The keyspace can be compacted automatically with etcd’s time windowed history retention policy, or manually with etcdctl. The etcdctl method provides fine-grained control over the compacting process whereas automatic compacting fits applications that only need key history for some length of time.

An etcdctl initiated compaction works as follows:

# compact up to revision 3
$ etcdctl compact 3

Revisions prior to the compaction revision become inaccessible:

$ etcdctl get --rev=2 somekey
Error:  rpc error: code = 11 desc = etcdserver: mvcc: required revision has been compacted

Auto Compaction

etcd can be set to automatically compact the keyspace with the --auto-compaction-* option with a period of hours:

# keep one hour of history
$ etcd --auto-compaction-retention=1

v3.0.0 and v3.1.0 with --auto-compaction-retention=10 run periodic compaction on v3 key-value store for every 10-hour. Compactor only supports periodic compaction. Compactor records latest revisions every 5-minute, until it reaches the first compaction period (e.g. 10-hour). In order to retain key-value history of last compaction period, it uses the last revision that was fetched before compaction period, from the revision records that were collected every 5-minute. When --auto-compaction-retention=10, compactor uses revision 100 for compact revision where revision 100 is the latest revision fetched from 10 hours ago. If compaction succeeds or requested revision has already been compacted, it resets period timer and starts over with new historical revision records (e.g. restart revision collect and compact for the next 10-hour period). If compaction fails, it retries in 5 minutes.

v3.2.0 compactor runs every hour. Compactor only supports periodic compaction. Compactor continues to record latest revisions every 5-minute. For every hour, it uses the last revision that was fetched before compaction period, from the revision records that were collected every 5-minute. That is, for every hour, compactor discards historical data created before compaction period. The retention window of compaction period moves to next hour. For instance, when hourly writes are 100 and --auto-compaction-retention=10, v3.1 compacts revision 1000, 2000, and 3000 for every 10-hour, while v3.2.x, v3.3.0, v3.3.1, and v3.3.2 compact revision 1000, 1100, and 1200 for every 1-hour. If compaction succeeds or requested revision has already been compacted, it resets period timer and removes used compacted revision from historical revision records (e.g. start next revision collect and compaction from previously collected revisions). If compaction fails, it retries in 5 minutes.

In v3.3.0, v3.3.1, and v3.3.2, --auto-compaction-mode=revision --auto-compaction-retention=1000 automatically Compact on "latest revision" - 1000 every 5-minute (when latest revision is 30000, compact on revision 29000). For instance, --auto-compaction-mode=periodic --auto-compaction-retention=72h automatically Compact with 72-hour retention window, for every 7.2-hour. For instance, --auto-compaction-mode=periodic --auto-compaction-retention=30m automatically Compact with 30-minute retention window, for every 3-minute. Periodic compactor continues to record latest revisions for every 1/10 of given compaction period (e.g. 1-hour when --auto-compaction-mode=periodic --auto-compaction-retention=10h). For every 1/10 of given compaction period, compactor uses the last revision that was fetched before compaction period, to discard historical data. The retention window of compaction period moves for every 1/10 of given compaction period. For instance, when hourly writes are 100 and --auto-compaction-retention=10, v3.1 compacts revision 1000, 2000, and 3000 for every 10-hour, while v3.2.x, v3.3.0, v3.3.1, and v3.3.2 compact revision 1000, 1100, and 1200 for every 1-hour. Furthermore, when writes per minute are 1000, v3.3.0, v3.3.1, and v3.3.2 with --auto-compaction-mode=periodic --auto-compaction-retention=30m compact revision 30000, 33000, and 36000, for every 3-minute with more finer granularity.

When --auto-compaction-retention=10h, etcd first waits 10-hour for the first compaction, and then does compaction every hour (1/10 of 10-hour) afterwards like this:

0Hr  (rev = 1)
1hr  (rev = 10)
...
8hr  (rev = 80)
9hr  (rev = 90)
10hr (rev = 100, Compact(1))
11hr (rev = 110, Compact(10))
...

Whether compaction succeeds or not, this process repeats for every 1/10 of given compaction period. If compaction succeeds, it just removes compacted revision from historical revision records.

In v3.3.3, --auto-compaction-mode=revision --auto-compaction-retention=1000 automatically Compact on "latest revision" - 1000 every 5-minute (when latest revision is 30000, compact on revision 29000). Previously, --auto-compaction-mode=periodic --auto-compaction-retention=72h automatically Compact with 72-hour retention window for every 7.2-hour. Now, Compact happens, for every 1-hour but still with 72-hour retention window. Previously, --auto-compaction-mode=periodic --auto-compaction-retention=30m automatically Compact with 30-minute retention window for every 3-minute. Now, Compact happens, for every 30-minute but still with 30-minute retention window. Periodic compactor keeps recording latest revisions for every compaction period when given period is less than 1-hour, or for every 1-hour when given compaction period is greater than 1-hour (e.g. 1-hour when --auto-compaction-mode=periodic --auto-compaction-retention=24h). For every compaction period or 1-hour, compactor uses the last revision that was fetched before compaction period, to discard historical data. The retention window of compaction period moves for every given compaction period or hour. For instance, when hourly writes are 100 and --auto-compaction-mode=periodic --auto-compaction-retention=24h, v3.2.x, v3.3.0, v3.3.1, and v3.3.2 compact revision 2400, 2640, and 2880 for every 2.4-hour, while v3.3.3 or later compacts revision 2400, 2500, 2600 for every 1-hour. Furthermore, when --auto-compaction-mode=periodic --auto-compaction-retention=30m and writes per minute are about 1000, v3.3.0, v3.3.1, and v3.3.2 compact revision 30000, 33000, and 36000, for every 3-minute, while v3.3.3 or later compacts revision 30000, 60000, and 90000, for every 30-minute.

Defragmentation

After compacting the keyspace, the backend database may exhibit internal fragmentation. Any internal fragmentation is space that is free to use by the backend but still consumes storage space. Compacting old revisions internally fragments etcd by leaving gaps in backend database. Fragmented space is available for use by etcd but unavailable to the host filesystem. In other words, deleting application data does not reclaim the space on disk.

The process of defragmentation releases this storage space back to the file system. Defragmentation is issued on a per-member basis so that cluster-wide latency spikes may be avoided.

To defragment an etcd member, use the etcdctl defrag command:

$ etcdctl defrag
Finished defragmenting etcd member[127.0.0.1:2379]

Note that defragmentation to a live member blocks the system from reading and writing data while rebuilding its states.

Note that defragmentation request does not get replicated over cluster. That is, the request is only applied to the local node. Specify all members in --endpoints flag or --cluster flag to automatically find all cluster members.

Run defragment operations for all endpoints in the cluster associated with the default endpoint:

$ etcdctl defrag --cluster
Finished defragmenting etcd member[http://127.0.0.1:2379]
Finished defragmenting etcd member[http://127.0.0.1:22379]
Finished defragmenting etcd member[http://127.0.0.1:32379]

To defragment an etcd data directory directly, while etcd is not running, use the command:

$ etcdctl defrag --data-dir <path-to-etcd-data-dir>

Space quota

The space quota in etcd ensures the cluster operates in a reliable fashion. Without a space quota, etcd may suffer from poor performance if the keyspace grows excessively large, or it may simply run out of storage space, leading to unpredictable cluster behavior. If the keyspace’s backend database for any member exceeds the space quota, etcd raises a cluster-wide alarm that puts the cluster into a maintenance mode which only accepts key reads and deletes. Only after freeing enough space in the keyspace and defragmenting the backend database, along with clearing the space quota alarm can the cluster resume normal operation.

By default, etcd sets a conservative space quota suitable for most applications, but it may be configured on the command line, in bytes:

# set a very small 16 MiB quota
$ etcd --quota-backend-bytes=$((16*1024*1024))

The space quota can be triggered with a loop:

# fill keyspace
$ while [ 1 ]; do dd if=/dev/urandom bs=1024 count=1024  | ETCDCTL_API=3 etcdctl put key  || break; done
...
Error:  rpc error: code = 8 desc = etcdserver: mvcc: database space exceeded
# confirm quota space is exceeded
$ ETCDCTL_API=3 etcdctl --write-out=table endpoint status
+----------------+------------------+-----------+---------+-----------+-----------+------------+
|    ENDPOINT    |        ID        |  VERSION  | DB SIZE | IS LEADER | RAFT TERM | RAFT INDEX |
+----------------+------------------+-----------+---------+-----------+-----------+------------+
| 127.0.0.1:2379 | bf9071f4639c75cc | 2.3.0+git | 18 MB   | true      |         2 |       3332 |
+----------------+------------------+-----------+---------+-----------+-----------+------------+
# confirm alarm is raised
$ ETCDCTL_API=3 etcdctl alarm list
memberID:13803658152347727308 alarm:NOSPACE

Removing excessive keyspace data and defragmenting the backend database will put the cluster back within the quota limits:

# get current revision
$ rev=$(ETCDCTL_API=3 etcdctl --endpoints=:2379 endpoint status --write-out="json" | egrep -o '"revision":[0-9]*' | egrep -o '[0-9].*')
# compact away all old revisions
$ ETCDCTL_API=3 etcdctl compact $rev
compacted revision 1516
# defragment away excessive space
$ ETCDCTL_API=3 etcdctl defrag
Finished defragmenting etcd member[127.0.0.1:2379]
# disarm alarm
$ ETCDCTL_API=3 etcdctl alarm disarm
memberID:13803658152347727308 alarm:NOSPACE
# test puts are allowed again
$ ETCDCTL_API=3 etcdctl put newkey 123
OK

The metric etcd_mvcc_db_total_size_in_use_in_bytes indicates the actual database usage after a history compaction, while etcd_debugging_mvcc_db_total_size_in_bytes shows the database size including free space waiting for defragmentation. The latter increases only when the former is close to it, meaning when both of these metrics are close to the quota, a history compaction is required to avoid triggering the space quota.

etcd_debugging_mvcc_db_total_size_in_bytes is renamed to etcd_mvcc_db_total_size_in_bytes from v3.4.

Snapshot backup

Snapshotting the etcd cluster on a regular basis serves as a durable backup for an etcd keyspace. By taking periodic snapshots of an etcd member’s backend database, an etcd cluster can be recovered to a point in time with a known good state.

A snapshot is taken with etcdctl:

$ etcdctl snapshot save backup.db
$ etcdctl --write-out=table snapshot status backup.db
+----------+----------+------------+------------+
|   HASH   | REVISION | TOTAL KEYS | TOTAL SIZE |
+----------+----------+------------+------------+
| fe01cf57 |       10 |          7 | 2.1 MB     |
+----------+----------+------------+------------+