Skills Development Klaviyo API Observability Implementation

Klaviyo API Observability Implementation

v20260423
klaviyo-observability
A comprehensive guide to implementing observability for Klaviyo API integrations. This solution uses Prometheus metrics (counters, histograms, gauges) to track API volume, latency, and errors, combined with OpenTelemetry for distributed tracing and structured logging. Ideal for setting up robust monitoring dashboards and critical alerting systems for marketing data pipelines.
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Overview

Klaviyo Observability

Overview

Comprehensive observability for Klaviyo integrations: Prometheus metrics for API call tracking, OpenTelemetry tracing, structured logging, and alerting rules tuned to Klaviyo's rate limits and error patterns.

Prerequisites

  • Prometheus or compatible metrics backend
  • OpenTelemetry SDK installed (optional)
  • Grafana or similar dashboarding tool (optional)
  • klaviyo-api SDK installed

Key Metrics to Track

Metric Type Why It Matters
klaviyo_api_requests_total Counter Track total API volume by endpoint
klaviyo_api_duration_seconds Histogram Detect latency degradation
klaviyo_api_errors_total Counter 4xx/5xx error rates
klaviyo_rate_limit_remaining Gauge Predict when you'll hit 429s
klaviyo_profiles_synced_total Counter Profile sync throughput
klaviyo_events_tracked_total Counter Event tracking volume
klaviyo_webhook_received_total Counter Inbound webhook volume

Instructions

Step 1: Instrumented API Wrapper

// src/klaviyo/instrumented-client.ts
import { Counter, Histogram, Gauge, Registry } from 'prom-client';

const registry = new Registry();

const apiRequests = new Counter({
  name: 'klaviyo_api_requests_total',
  help: 'Total Klaviyo API requests',
  labelNames: ['method', 'endpoint', 'status'],
  registers: [registry],
});

const apiDuration = new Histogram({
  name: 'klaviyo_api_duration_seconds',
  help: 'Klaviyo API request duration in seconds',
  labelNames: ['method', 'endpoint'],
  buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5, 10],
  registers: [registry],
});

const apiErrors = new Counter({
  name: 'klaviyo_api_errors_total',
  help: 'Klaviyo API errors by status code',
  labelNames: ['endpoint', 'status_code', 'error_code'],
  registers: [registry],
});

const rateLimitRemaining = new Gauge({
  name: 'klaviyo_rate_limit_remaining',
  help: 'Remaining requests in current rate limit window',
  registers: [registry],
});

export async function instrumentedCall<T>(
  endpoint: string,
  method: string,
  operation: () => Promise<T>
): Promise<T> {
  const timer = apiDuration.startTimer({ method, endpoint });

  try {
    const result = await operation();
    apiRequests.inc({ method, endpoint, status: 'success' });

    // Extract rate limit headers if available
    const headers = (result as any)?.headers;
    if (headers?.['ratelimit-remaining']) {
      rateLimitRemaining.set(parseInt(headers['ratelimit-remaining']));
    }

    return result;
  } catch (error: any) {
    const statusCode = error.status || 'unknown';
    const errorCode = error.body?.errors?.[0]?.code || 'unknown';
    apiRequests.inc({ method, endpoint, status: 'error' });
    apiErrors.inc({ endpoint, status_code: statusCode, error_code: errorCode });
    throw error;
  } finally {
    timer();
  }
}

export { registry };

Step 2: Usage in Service Layer

// Wrap all Klaviyo calls with instrumentation
import { instrumentedCall } from '../klaviyo/instrumented-client';

// Profile creation with metrics
const profile = await instrumentedCall('profiles', 'POST', () =>
  profilesApi.createOrUpdateProfile({
    data: {
      type: 'profile' as any,
      attributes: { email: user.email, firstName: user.name },
    },
  })
);

// Event tracking with metrics
await instrumentedCall('events', 'POST', () =>
  eventsApi.createEvent({
    data: {
      type: 'event',
      attributes: {
        metric: { data: { type: 'metric', attributes: { name: 'Placed Order' } } },
        profile: { data: { type: 'profile', attributes: { email: order.email } } },
        properties: { orderId: order.id },
        value: order.total,
        time: new Date().toISOString(),
      },
    },
  })
);

Step 3: OpenTelemetry Tracing

// src/klaviyo/tracing.ts
import { trace, SpanStatusCode, Span } from '@opentelemetry/api';

const tracer = trace.getTracer('klaviyo-integration', '1.0.0');

export async function tracedKlaviyoCall<T>(
  operationName: string,
  attributes: Record<string, string>,
  operation: () => Promise<T>
): Promise<T> {
  return tracer.startActiveSpan(`klaviyo.${operationName}`, async (span: Span) => {
    span.setAttributes({
      'klaviyo.operation': operationName,
      'klaviyo.revision': '2024-10-15',
      ...attributes,
    });

    try {
      const result = await operation();
      span.setStatus({ code: SpanStatusCode.OK });
      return result;
    } catch (error: any) {
      span.setStatus({ code: SpanStatusCode.ERROR, message: error.message });
      span.setAttributes({
        'klaviyo.error.status': error.status?.toString() || 'unknown',
        'klaviyo.error.code': error.body?.errors?.[0]?.code || 'unknown',
      });
      span.recordException(error);
      throw error;
    } finally {
      span.end();
    }
  });
}

Step 4: Structured Logging

// src/klaviyo/logger.ts
import pino from 'pino';

const logger = pino({
  name: 'klaviyo',
  level: process.env.KLAVIYO_LOG_LEVEL || 'info',
  serializers: {
    // Redact sensitive data from logs
    profile: (profile: any) => ({
      id: profile.id,
      email: profile.email ? `${profile.email.substring(0, 3)}***` : undefined,
    }),
    err: pino.stdSerializers.err,
  },
});

export function logApiCall(operation: string, durationMs: number, status: 'ok' | 'error', meta?: Record<string, any>) {
  logger.info({
    msg: `klaviyo.${operation}`,
    service: 'klaviyo',
    operation,
    durationMs: Math.round(durationMs),
    status,
    ...meta,
  });
}

export function logWebhook(topic: string, eventId: string, durationMs: number) {
  logger.info({
    msg: `klaviyo.webhook.${topic}`,
    service: 'klaviyo',
    topic,
    eventId,
    durationMs: Math.round(durationMs),
  });
}

export { logger };

Step 5: Alert Rules (Prometheus)

# prometheus/klaviyo-alerts.yml
groups:
  - name: klaviyo
    rules:
      - alert: KlaviyoHighErrorRate
        expr: |
          rate(klaviyo_api_errors_total[5m]) /
          rate(klaviyo_api_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Klaviyo API error rate above 5%"
          description: "Error rate: {{ $value | humanizePercentage }}"

      - alert: KlaviyoRateLimited
        expr: |
          increase(klaviyo_api_errors_total{status_code="429"}[5m]) > 10
        for: 2m
        labels:
          severity: warning
        annotations:
          summary: "Klaviyo rate limit being hit frequently"

      - alert: KlaviyoHighLatency
        expr: |
          histogram_quantile(0.95,
            rate(klaviyo_api_duration_seconds_bucket[5m])
          ) > 3
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Klaviyo API P95 latency above 3 seconds"

      - alert: KlaviyoDown
        expr: |
          increase(klaviyo_api_errors_total{status_code=~"5.."}[5m]) > 20
          and increase(klaviyo_api_requests_total{status="success"}[5m]) == 0
        for: 3m
        labels:
          severity: critical
        annotations:
          summary: "Klaviyo API appears to be down"

      - alert: KlaviyoRateLimitLow
        expr: klaviyo_rate_limit_remaining < 20
        for: 30s
        labels:
          severity: warning
        annotations:
          summary: "Klaviyo rate limit headroom below 20 requests"

Step 6: Metrics Endpoint

// src/routes/metrics.ts
import { registry } from '../klaviyo/instrumented-client';

app.get('/metrics', async (req, res) => {
  res.set('Content-Type', registry.contentType);
  res.send(await registry.metrics());
});

Grafana Dashboard Panels

Panel Query Purpose
Request Rate rate(klaviyo_api_requests_total[5m]) API call volume
Error Rate rate(klaviyo_api_errors_total[5m]) Error trend
Latency P50/P95 histogram_quantile(0.95, rate(klaviyo_api_duration_seconds_bucket[5m])) Performance
Rate Limit klaviyo_rate_limit_remaining Rate limit headroom
Error by Code topk(5, sum by (status_code) (rate(klaviyo_api_errors_total[5m]))) Error breakdown

Error Handling

Issue Cause Solution
Missing metrics No instrumentation wrapper Wrap all API calls with instrumentedCall()
High cardinality Too many label values Use endpoint groups, not full URLs
Alert storms Thresholds too low Tune alert rules to your traffic pattern
PII in logs Email in log messages Use serializer to redact emails

Resources

Next Steps

For incident response, see klaviyo-incident-runbook.

Info
Category Development
Name klaviyo-observability
Version v20260423
Size 9.36KB
Updated At 2026-04-26
Language