What is the benefit of using the Cloudflare Analytics Engine?

The Analytics Engine allows you to collect high-cardinality telemetry and custom metrics from Workers, which you can then query using SQL to analyze performance trends and business data.

Why should I use structured logging instead of plain console.log?

Structured JSON logging allows for programmatic parsing, easier searching in log aggregators, and the ability to include rich metadata like request IDs and performance metrics that plain text lacks.

Can I use this for high-traffic production environments?

Yes, the skill includes configurations for log sampling and head-sampling rates to help you manage log volume, reduce noise, and control costs in high-traffic workers.

How does this skill handle sensitive data in logs?

The skill implements automated redaction middleware that identifies and masks sensitive keys such as passwords, tokens, and authorization headers before logs are emitted.

Cloudflare Workers Observability

Name: Cloudflare Workers Observability
Author: secondsky

bysecondsky

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Analytics & Monitoring

Implements production-grade monitoring, structured logging, and real-time analytics for Cloudflare Workers applications.

About

This skill equips Claude with the patterns and best practices needed to implement comprehensive observability within the Cloudflare Workers ecosystem. It automates the setup of structured JSON logging, configures the Cloudflare Analytics Engine for custom metrics, and establishes Tail Worker pipelines for log aggregation. By enforcing critical rules like request context inclusion and automatic PII redaction, it helps developers prevent common errors such as log truncation and missing alert coverage, ensuring serverless applications remain reliable and debuggable at scale.

Key Features

21 GitHub stars
Cloudflare Analytics Engine integration for custom performance and business metrics
Standardized structured JSON logging with automatic PII redaction
Request correlation patterns using unique request IDs and context tracking
Automated wrangler.jsonc configuration for observability and sampling
Tail Worker implementation for real-time log streaming and external aggregation

Use Cases

Establishing automated alerting pipelines for error rate thresholds and latency
Debugging production incidents using correlated logs and distributed tracing
Monitoring serverless application performance and business KPIs via Analytics Engine

About

Key Features

21 GitHub stars
Cloudflare Analytics Engine integration for custom performance and business metrics
Standardized structured JSON logging with automatic PII redaction
Request correlation patterns using unique request IDs and context tracking
Automated wrangler.jsonc configuration for observability and sampling
Tail Worker implementation for real-time log streaming and external aggregation

Use Cases

Establishing automated alerting pipelines for error rate thresholds and latency
Debugging production incidents using correlated logs and distributed tracing
Monitoring serverless application performance and business KPIs via Analytics Engine