Monitor ClickHouse with Prometheus metrics, Grafana dashboards, system table queries,
and alerting for query performance, merge health, and resource usage.
Use when setting up ClickHouse monitoring, building Grafana dashboards,
or configuring alerts for production ClickHouse deployments.
Trigger: "clickhouse monitoring", "clickhouse metrics", "clickhouse Grafana",
"clickhouse observability", "monitor clickhouse", "clickhouse Prometheus".
Instrucciones de origen · Vista previa de solo lectura
name
clickhouse-observability
description
Monitor ClickHouse with Prometheus metrics, Grafana dashboards, system table queries,
and alerting for query performance, merge health, and resource usage.
Use when setting up ClickHouse monitoring, building Grafana dashboards,
or configuring alerts for production ClickHouse deployments.
Trigger: "clickhouse monitoring", "clickhouse metrics", "clickhouse Grafana",
"clickhouse observability", "monitor clickhouse", "clickhouse Prometheus".
Set up comprehensive monitoring for ClickHouse using built-in system tables,
Prometheus integration, Grafana dashboards, and alerting rules.
Prerequisites
ClickHouse instance with system.* table access
Prometheus (or compatible: Grafana Alloy, Victoria Metrics)
Grafana for dashboards
AlertManager or PagerDuty for alerts
Instructions
Step 1: Key Metrics from System Tables
-- Real-time server health snapshotSELECT
(SELECTcount() FROM system.processes) AS running_queries,
(SELECTvalueFROM system.metrics WHERE metric ='MemoryTracking') AS memory_bytes,
(SELECTvalueFROM system.metrics WHERE metric ='Query') AS concurrent_queries,
(SELECTcount() FROM system.merges) AS active_merges,
(SELECTvalueFROM system.asynchronous_metrics WHERE metric ='Uptime') AS uptime_sec;
-- Query throughput (last hour, per minute)SELECT
toStartOfMinute(event_time) ASminute,
count() AS queries,
countIf(exception_code !=0) AS errors,
round((query_duration_ms)) avg_ms,
round(quantile()(query_duration_ms)) p95_ms,
formatReadableSize((read_bytes)) total_read
system.query_log
type (, )
event_time now()
;
toStartOfMinute(event_time) ,
() inserts,
(written_rows) rows_written,
formatReadableSize((written_bytes)) bytes_written
system.query_log
type query_kind
event_time now()
;
database, , () parts, () ,
formatReadableSize((bytes_on_disk)) size
system.parts active
database,
parts
parts ;
avg
AS
0.95
AS
sum
AS
FROM
WHERE
IN
'QueryFinish'
'ExceptionWhileProcessing'
AND
>=
-
INTERVAL
1
HOUR
GROUP
BY
minute
ORDER
BY
minute
-- Insert throughput (last hour)
SELECT
AS
minute
count
AS
sum
AS
sum
AS
FROM
WHERE
=
'QueryFinish'
AND
=
'Insert'
AND
>=
-
INTERVAL
1
HOUR
GROUP
BY
minute
ORDER
BY
minute
-- Part count per table (merge health indicator)
SELECT
table
count
AS
sum
rows
AS
rows
sum
AS
FROM
WHERE
GROUP
BY
table
HAVING
>
50
ORDER
BY
DESC
Step 2: Prometheus Integration
ClickHouse Cloud exposes a managed Prometheus endpoint:
# prometheus.ymlscrape_configs:-job_name:clickhouse-cloudmetrics_path:/v1/organizations/<ORG_ID>/prometheusbasic_auth:username:<API_KEY_ID>password:<API_KEY_SECRET>static_configs:-targets: ['api.clickhouse.cloud']
params:filtered_metrics: ['true'] # 125 critical metrics only
Self-hosted — use clickhouse-exporter or built-in metrics endpoint:
