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#!/bin/bash -e
# Kubernetes api server is supposed to run compaction on etcd
# when that does not happen we need to do an emergency compaction to make etcd not lock up
# this should only be done once, so we pick the leader to do it, which we assume is healthy
# (compacting manually outside of api server can lead to watches failing / requests for specific revisions failing etc)
#
# 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.
# The process of defragmentation releases this storage space back to the file system.
# It also decreases the db_size which we monitor.
# Defragmentation is issued on a per-member so that cluster-wide latency spikes may be avoided.
set -o pipefail
source /etc/profile # get env vars
while true; do
compact_limit="1610612736" # 1.5 GB of the 2 GB default db size
defrag_limit="1073741824" # 1 GB of the 2 GB default db size
status=$(etcdctl endpoint status --write-out json)
member_id=$(echo $status | jq .[0].Status.header.member_id)
leader_id=$(echo $status | jq .[0].Status.leader)
revision=$(echo $status | jq .[0].Status.header.revision)
db_size=$(echo $status | jq .[0].Status.dbSize)
pause=60
echo "member $member_id / leader $leader_id / db_size $db_size"
if [ "$member_id" = "$leader_id" ] && [ $db_size -gt $compact_limit ]; then
echo "Started compact"
timeout 10 etcdctl compact $revision
else
echo "decided not to compact"
fi
if [ $db_size -gt $defrag_limit ]; then
if [ "$member_id" != "$leader_id" ]; then
sleep $[$RANDOM % 60]s # Stagger for each member so we don't lock db
fi
echo "Started defrag"
timeout 10 etcdctl defrag
else
echo "decided not to defrag"
fi
sleep $pause
done
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