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