glean-observability
Set up comprehensive observability for Glean integrations with metrics, traces, and alerts. Use when implementing monitoring for Glean operations, setting up dashboards, or configuring alerting for Glean integration health. Trigger with phrases like "glean monitoring", "glean metrics", "glean observability", "monitor glean", "glean alerts", "glean tracing".
Allowed Tools
Provided by Plugin
glean-pack
Claude Code skill pack for Glean (24 skills)
Installation
This skill is included in the glean-pack plugin:
/plugin install glean-pack@claude-code-plugins-plus
Click to copy
Instructions
Glean Observability
Overview
Set up comprehensive observability for Glean integrations.
Prerequisites
- Prometheus or compatible metrics backend
- OpenTelemetry SDK installed
- Grafana or similar dashboarding tool
- AlertManager configured
Metrics Collection
Key Metrics
| Metric | Type | Description |
|---|---|---|
gleanrequeststotal |
Counter | Total API requests |
gleanrequestduration_seconds |
Histogram | Request latency |
gleanerrorstotal |
Counter | Error count by type |
gleanratelimit_remaining |
Gauge | Rate limit headroom |
Prometheus Metrics
import { Registry, Counter, Histogram, Gauge } from 'prom-client';
const registry = new Registry();
const requestCounter = new Counter({
name: 'glean_requests_total',
help: 'Total Glean API requests',
labelNames: ['method', 'status'],
registers: [registry],
});
const requestDuration = new Histogram({
name: 'glean_request_duration_seconds',
help: 'Glean request duration',
labelNames: ['method'],
buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
registers: [registry],
});
const errorCounter = new Counter({
name: 'glean_errors_total',
help: 'Glean 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('glean-client');
async function tracedGleanCall<T>(
operationName: string,
operation: () => Promise<T>
): Promise<T> {
return tracer.startActiveSpan(`glean.${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: 'glean',
level: process.env.LOG_LEVEL || 'info',
});
function logGleanOperation(
operation: string,
data: Record<string, any>,
duration: number
) {
logger.info({
service: 'glean',
operation,
duration_ms: duration,
...data,
});
}
Alert Configuration
Prometheus AlertManager Rules
# glean_alerts.yaml
groups:
- name: glean_alerts
rules:
- alert: GleanHighErrorRate
expr: |
rate(glean_errors_total[5m]) /
rate(glean_requests_total[5m]) > 0.05
for: 5m
labels:
severity: warning
annotations:
summary: "Glean error rate > 5%"
- alert: GleanHighLatency
expr: |
histogram_quantile(0.95,
rate(glean_request_duration_seconds_bucket[5m])
) > 2
for: 5m
labels:
severity: warning
annotations:
summary: "Glean P95 latency > 2s"
- alert: GleanDown
expr: up{job="glean"} == 0
for: 1m
labels:
severity: critical
annotations:
summary: "Glean integration is down"
Dashboard
Grafana Panel Queries
{
"panels": [
{
"title": "Glean Request Rate",
"targets": [{
"expr": "rate(glean_requests_total[5m])"
}]
},
{
"title": "Glean Latency P50/P95/P99",
"targets": [{
"expr": "histogram_quantile(0.5, rate(glean_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 glean-incident-runbook.