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