exa-observability
Set up comprehensive observability for Exa integrations with metrics, traces, and alerts. Use when implementing monitoring for Exa operations, setting up dashboards, or configuring alerting for Exa integration health. Trigger with phrases like "exa monitoring", "exa metrics", "exa observability", "monitor exa", "exa alerts", "exa tracing". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore <jeremy@intentsolutions.io>
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Provided by Plugin
exa-pack
Claude Code skill pack for Exa (30 skills)
Installation
This skill is included in the exa-pack plugin:
/plugin install exa-pack@claude-code-plugins-plus
Click to copy
Instructions
# Exa Observability
## Overview
Set up comprehensive observability for Exa integrations.
## Prerequisites
- Prometheus or compatible metrics backend
- OpenTelemetry SDK installed
- Grafana or similar dashboarding tool
- AlertManager configured
## Metrics Collection
### Key Metrics
| Metric | Type | Description |
|--------|------|-------------|
| `exa_requests_total` | Counter | Total API requests |
| `exa_request_duration_seconds` | Histogram | Request latency |
| `exa_errors_total` | Counter | Error count by type |
| `exa_rate_limit_remaining` | Gauge | Rate limit headroom |
### Prometheus Metrics
```typescript
import { Registry, Counter, Histogram, Gauge } from 'prom-client';
const registry = new Registry();
const requestCounter = new Counter({
name: 'exa_requests_total',
help: 'Total Exa API requests',
labelNames: ['method', 'status'],
registers: [registry],
});
const requestDuration = new Histogram({
name: 'exa_request_duration_seconds',
help: 'Exa request duration',
labelNames: ['method'],
buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
registers: [registry],
});
const errorCounter = new Counter({
name: 'exa_errors_total',
help: 'Exa errors by type',
labelNames: ['error_type'],
registers: [registry],
});
```
### Instrumented Client
```typescript
async function instrumentedRequest(
method: string,
operation: () => Promise
): Promise {
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
```typescript
import { trace, SpanStatusCode } from '@opentelemetry/api';
const tracer = trace.getTracer('exa-client');
async function tracedExaCall(
operationName: string,
operation: () => Promise
): Promise {
return tracer.startActiveSpan(`exa.${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
```typescript
import pino from 'pino';
const logger = pino({
name: 'exa',
level: process.env.LOG_LEVEL || 'info',
});
function logExaOperation(
operation: string,
data: Record,
duration: number
) {
logger.info({
service: 'exa',
operation,
duration_ms: duration,
...data,
});
}
```
## Alert Configuration
### Prometheus AlertManager Rules
```yaml
# exa_alerts.yaml
groups:
- name: exa_alerts
rules:
- alert: ExaHighErrorRate
expr: |
rate(exa_errors_total[5m]) /
rate(exa_requests_total[5m]) > 0.05
for: 5m
labels:
severity: warning
annotations:
summary: "Exa error rate > 5%"
- alert: ExaHighLatency
expr: |
histogram_quantile(0.95,
rate(exa_request_duration_seconds_bucket[5m])
) > 2
for: 5m
labels:
severity: warning
annotations:
summary: "Exa P95 latency > 2s"
- alert: ExaDown
expr: up{job="exa"} == 0
for: 1m
labels:
severity: critical
annotations:
summary: "Exa integration is down"
```
## Dashboard
### Grafana Panel Queries
```json
{
"panels": [
{
"title": "Exa Request Rate",
"targets": [{
"expr": "rate(exa_requests_total[5m])"
}]
},
{
"title": "Exa Latency P50/P95/P99",
"targets": [{
"expr": "histogram_quantile(0.5, rate(exa_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
```typescript
app.get('/metrics', async (req, res) => {
res.set('Content-Type', registry.contentType);
res.send(await registry.metrics());
});
```
## Resources
- [Prometheus Best Practices](https://prometheus.io/docs/practices/naming/)
- [OpenTelemetry Documentation](https://opentelemetry.io/docs/)
- [Exa Observability Guide](https://docs.exa.com/observability)
## Next Steps
For incident response, see `exa-incident-runbook`.