clickhouse-observability
Set up comprehensive observability for ClickHouse integrations with metrics, traces, and alerts. Use when implementing monitoring for ClickHouse operations, setting up dashboards, or configuring alerting for ClickHouse integration health. Trigger with phrases like "clickhouse monitoring", "clickhouse metrics", "clickhouse observability", "monitor clickhouse", "clickhouse alerts", "clickhouse tracing".
Allowed Tools
Provided by Plugin
clickhouse-pack
Claude Code skill pack for ClickHouse (24 skills)
Installation
This skill is included in the clickhouse-pack plugin:
/plugin install clickhouse-pack@claude-code-plugins-plus
Click to copy
Instructions
ClickHouse Observability
Overview
Set up comprehensive observability for ClickHouse integrations.
Prerequisites
- Prometheus or compatible metrics backend
- OpenTelemetry SDK installed
- Grafana or similar dashboarding tool
- AlertManager configured
Metrics Collection
Key Metrics
| Metric | Type | Description |
|---|---|---|
clickhouserequeststotal |
Counter | Total API requests |
clickhouserequestduration_seconds |
Histogram | Request latency |
clickhouseerrorstotal |
Counter | Error count by type |
clickhouseratelimit_remaining |
Gauge | Rate limit headroom |
Prometheus Metrics
import { Registry, Counter, Histogram, Gauge } from 'prom-client';
const registry = new Registry();
const requestCounter = new Counter({
name: 'clickhouse_requests_total',
help: 'Total ClickHouse API requests',
labelNames: ['method', 'status'],
registers: [registry],
});
const requestDuration = new Histogram({
name: 'clickhouse_request_duration_seconds',
help: 'ClickHouse request duration',
labelNames: ['method'],
buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
registers: [registry],
});
const errorCounter = new Counter({
name: 'clickhouse_errors_total',
help: 'ClickHouse errors by type',
labelNames: ['error_type'],
registers: [registry],
});
Instrumented Client
async function instrumentedRequest<T>(
method: string,
operation: () => Promise<T>
): Promise<T> {
const timer = requestDuration.startTimer({ method });
try {
const result = await operation();
requestCounter.inc({ method, status: 'success' });
return result;
} catch (error: any) {
requestCounter.inc({ method, status: 'error' });
errorCounter.inc({ error_type: error.code || 'unknown' });
throw error;
} finally {
timer();
}
}
Distributed Tracing
OpenTelemetry Setup
import { trace, SpanStatusCode } from '@opentelemetry/api';
const tracer = trace.getTracer('clickhouse-client');
async function tracedClickHouseCall<T>(
operationName: string,
operation: () => Promise<T>
): Promise<T> {
return tracer.startActiveSpan(`clickhouse.${operationName}`, async (span) => {
try {
const result = await operation();
span.setStatus({ code: SpanStatusCode.OK });
return result;
} catch (error: any) {
span.setStatus({ code: SpanStatusCode.ERROR, message: error.message });
span.recordException(error);
throw error;
} finally {
span.end();
}
});
}
Logging Strategy
Structured Logging
import pino from 'pino';
const logger = pino({
name: 'clickhouse',
level: process.env.LOG_LEVEL || 'info',
});
function logClickHouseOperation(
operation: string,
data: Record<string, any>,
duration: number
) {
logger.info({
service: 'clickhouse',
operation,
duration_ms: duration,
...data,
});
}
Alert Configuration
Prometheus AlertManager Rules
# clickhouse_alerts.yaml
groups:
- name: clickhouse_alerts
rules:
- alert: ClickHouseHighErrorRate
expr: |
rate(clickhouse_errors_total[5m]) /
rate(clickhouse_requests_total[5m]) > 0.05
for: 5m
labels:
severity: warning
annotations:
summary: "ClickHouse error rate > 5%"
- alert: ClickHouseHighLatency
expr: |
histogram_quantile(0.95,
rate(clickhouse_request_duration_seconds_bucket[5m])
) > 2
for: 5m
labels:
severity: warning
annotations:
summary: "ClickHouse P95 latency > 2s"
- alert: ClickHouseDown
expr: up{job="clickhouse"} == 0
for: 1m
labels:
severity: critical
annotations:
summary: "ClickHouse integration is down"
Dashboard
Grafana Panel Queries
{
"panels": [
{
"title": "ClickHouse Request Rate",
"targets": [{
"expr": "rate(clickhouse_requests_total[5m])"
}]
},
{
"title": "ClickHouse Latency P50/P95/P99",
"targets": [{
"expr": "histogram_quantile(0.5, rate(clickhouse_request_duration_seconds_bucket[5m]))"
}]
}
]
}
Instructions
Step 1: Set Up Metrics Collection
Implement Prometheus counters, histograms, and gauges for key operations.
Step 2: Add Distributed Tracing
Integrate OpenTelemetry for end-to-end request tracing.
Step 3: Configure Structured Logging
Set up JSON logging with consistent field names.
Step 4: Create Alert Rules
Define Prometheus alerting rules for error rates and latency.
Output
- Metrics collection enabled
- Distributed tracing configured
- Structured logging implemented
- Alert rules deployed
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Missing metrics | No instrumentation | Wrap client calls |
| Trace gaps | Missing propagation | Check context headers |
| Alert storms | Wrong thresholds | Tune alert rules |
| High cardinality | Too many labels | Reduce label values |
Examples
Quick Metrics Endpoint
app.get('/metrics', async (req, res) => {
res.set('Content-Type', registry.contentType);
res.send(await registry.metrics());
});
Resources
Next Steps
For incident response, see clickhouse-incident-runbook.