Does this help prevent Klaviyo rate limiting issues?

Yes, it includes a dedicated Gauge metric for 'klaviyo_rate_limit_remaining' and specific alert rules to warn you when your headroom is low, allowing you to throttle traffic before hitting 429 errors.

Which monitoring tools does this skill support?

The skill is specifically designed to integrate with Prometheus for metrics, OpenTelemetry for tracing, and Pino for structured logging, though the patterns can be adapted for other observability stacks.

Can I use this to build Grafana dashboards?

Absolutely. The skill provides the specific Prometheus queries and metric definitions needed to create comprehensive Grafana panels for request rates, error trends, and P95 latency.

How does it handle sensitive customer data in logs?

The skill includes a custom pino logger configuration with serializers that automatically redact sensitive information like email addresses from log outputs to maintain compliance.

Klaviyo Observability Integration

Name: Klaviyo Observability Integration
Author: jeremylongshore

byjeremylongshore

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2,107

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分析与监控

Implements comprehensive monitoring, tracing, and alerting for Klaviyo API integrations to maintain high reliability and performance.

The Klaviyo Observability skill provides a standardized framework for monitoring Klaviyo API interactions using industry-standard tools like Prometheus and OpenTelemetry. It enables developers to track API volume, latency, error rates, and rate limit headroom through instrumented wrappers, structured logging, and pre-configured alerting rules. This skill is essential for production environments where maintaining healthy SaaS integrations, proactively detecting sync issues, and staying within Klaviyo's API limits are critical for marketing success.

主要功能

012,107 GitHub stars

02OpenTelemetry integration for distributed request tracing across services

03Prometheus-ready metrics for API request volume, latency, and error tracking

04Pre-configured Prometheus alert rules for high error rates and latency spikes

05Structured logging with built-in PII redaction for secure data handling

06Real-time rate limit monitoring to proactively prevent 429 throttling errors

使用场景

01Setting up automated alerts to notify DevOps teams of Klaviyo service degradations

02Debugging complex API failures using distributed tracing and structured logs

03Monitoring the health and throughput of high-volume Klaviyo profile syncs

主要功能

012,107 GitHub stars

02OpenTelemetry integration for distributed request tracing across services

03Prometheus-ready metrics for API request volume, latency, and error tracking

04Pre-configured Prometheus alert rules for high error rates and latency spikes

05Structured logging with built-in PII redaction for secure data handling

06Real-time rate limit monitoring to proactively prevent 429 throttling errors

使用场景

01Setting up automated alerts to notify DevOps teams of Klaviyo service degradations

02Debugging complex API failures using distributed tracing and structured logs

03Monitoring the health and throughput of high-volume Klaviyo profile syncs