Monitoring etcd

Monitoring etcd for system health & cluster debugging

Each etcd server provides local monitoring information on its client port through http endpoints. The monitoring data is useful for both system health checking and cluster debugging.

Debug endpoint

If --log-level=debug is set, the etcd server exports debugging information on its client port under the /debug path. Take care when setting --log-level=debug, since there will be degraded performance and verbose logging.

The /debug/pprof endpoint is the standard go runtime profiling endpoint. This can be used to profile CPU, heap, mutex, and goroutine utilization. For example, here go tool pprof gets the top 10 functions where etcd spends its time:

$ go tool pprof http://localhost:2379/debug/pprof/profile
Fetching profile from http://localhost:2379/debug/pprof/profile
Please wait... (30s)
Saved profile in /home/etcd/pprof/pprof.etcd.localhost:2379.samples.cpu.001.pb.gz
Entering interactive mode (type "help" for commands)
(pprof) top10
310ms of 480ms total (64.58%)
Showing top 10 nodes out of 157 (cum >= 10ms)
    flat  flat%   sum%        cum   cum%
   130ms 27.08% 27.08%      130ms 27.08%  runtime.futex
    70ms 14.58% 41.67%       70ms 14.58%  syscall.Syscall
    20ms  4.17% 45.83%       20ms  4.17%
    20ms  4.17% 50.00%       30ms  6.25%  runtime.pcvalue
    20ms  4.17% 54.17%       50ms 10.42%  runtime.schedule
    10ms  2.08% 56.25%       10ms  2.08%*EtcdServer).AuthInfoFromCtx
    10ms  2.08% 58.33%       10ms  2.08%*EtcdServer).Lead
    10ms  2.08% 60.42%       10ms  2.08%*timeList).Trigger
    10ms  2.08% 62.50%       10ms  2.08%*MetricVec).hashLabelValues
    10ms  2.08% 64.58%       10ms  2.08%*Framer).WriteHeaders

The /debug/requests endpoint gives gRPC traces and performance statistics through a web browser. For example, here is a Range request for the key abc:

When	Elapsed (s)
2017/08/18 17:34:51.999317 	0.000244 	/etcdserverpb.KV/Range
17:34:51.999382 	 .    65 	... RPC: from deadline:4.999377747s
17:34:51.999395 	 .    13 	... recv: key:"abc"
17:34:51.999499 	 .   104 	... OK
17:34:51.999535 	 .    36 	... sent: header:<cluster_id:14841639068965178418 member_id:10276657743932975437 revision:15 raft_term:17 > kvs:<key:"abc" create_revision:6 mod_revision:14 version:9 value:"asda" > count:1

Metrics endpoint

Each etcd server exports metrics under the /metrics path on its client port and optionally on locations given by --listen-metrics-urls.

The metrics can be fetched with curl:

$ curl -L http://localhost:2379/metrics | grep -v debugging # ignore unstable debugging metrics

# HELP etcd_disk_backend_commit_duration_seconds The latency distributions of commit called by backend.
# TYPE etcd_disk_backend_commit_duration_seconds histogram
etcd_disk_backend_commit_duration_seconds_bucket{le="0.002"} 72756
etcd_disk_backend_commit_duration_seconds_bucket{le="0.004"} 401587
etcd_disk_backend_commit_duration_seconds_bucket{le="0.008"} 405979
etcd_disk_backend_commit_duration_seconds_bucket{le="0.016"} 406464

Health Check

Since v3.3.0, in addition to responding to the /metrics endpoint, any locations specified by --listen-metrics-urls will also respond to the /health endpoint. This can be useful if the standard endpoint is configured with mutual (client) TLS authentication, but a load balancer or monitoring service still needs access to the health check.

Since v3.5.12, two new endpoints /livez and /readyz are added.

  • the /livez endpoint reflects whether the process is alive or if it needs a restart.
  • the /readyz endpoint reflects whether the process is ready to serve traffic.

Design details of the endpoints are documented in the KEP.

Each endpoint includes several individual health checks, and you can use the verbose parameter to print out the details of the checks and their status, for example

curl -k http://localhost:2379/readyz?verbose

and you would see the response similar to

[+]data_corruption ok
[+]serializable_read ok
[+]linearizable_read ok

The http API also supports to exclude specific checks, for example

curl -k http://localhost:2379/readyz?exclude=data_corruption


Running a Prometheus monitoring service is the easiest way to ingest and record etcd’s metrics.

First, install Prometheus:

wget$PROMETHEUS_VERSION/prometheus-$PROMETHEUS_VERSION.linux-amd64.tar.gz -O /tmp/prometheus-$PROMETHEUS_VERSION.linux-amd64.tar.gz
tar -xvzf /tmp/prometheus-$PROMETHEUS_VERSION.linux-amd64.tar.gz --directory /tmp/ --strip-components=1
/tmp/prometheus -version

Set Prometheus’s scraper to target the etcd cluster endpoints:

cat > /tmp/test-etcd.yaml <<EOF
  scrape_interval: 10s
  - job_name: test-etcd
    - targets: ['','','']
cat /tmp/test-etcd.yaml

Set up the Prometheus handler:

nohup /tmp/prometheus \
    -config.file /tmp/test-etcd.yaml \
    -web.listen-address ":9090" \
    -storage.local.path "" >> /tmp/test-etcd.log  2>&1 &

Now Prometheus will scrape etcd metrics every 10 seconds.


There is a set of default alerts for etcd v3 clusters for Prometheus.


Grafana has built-in Prometheus support; just add a Prometheus data source:

Name:   test-etcd
Type:   Prometheus
Url:    http://localhost:9090
Access: proxy

Then import the default etcd dashboard template and customize. For instance, if Prometheus data source name is my-etcd, the datasource field values in JSON also need to be my-etcd.

Sample dashboard:

Distributed tracing

In v3.5 etcd has added support for distributed tracing using OpenTelemetry.

To enable this experimental feature, pass the --experimental-enable-distributed-tracing=true to the etcd server, along with the --experimental-distributed-tracing-sampling-rate=<number> flag to choose how many samples to collect per million spans, the default sampling rate is 0.

Configure the distributed tracing by starting etcd server with the following optional flags:

  • --experimental-distributed-tracing-address - (Optional) - “localhost:4317” - Address of the tracing collector.

  • --experimental-distributed-tracing-service-name - (Optional) - “etcd” - Distributed tracing service name, must be same across all etcd instances.

  • --experimental-distributed-tracing-instance-id - (Optional) - Instance ID, while optional it’s strongly recommended to set, must be unique per etcd instance.

Before enabling the distributed tracing, make sure to have the OpenTelemetry endpoint, if that address differs to the default one, override with the --experimental-distributed-tracing-address flag. Due to OpenTelemetry having different ways of running, refer to the collector documentation to learn more.