Which tracing backends are supported by this skill?

The skill supports popular backends including Jaeger, Zipkin, and Datadog, as well as any OpenTelemetry-compatible collector.

How does it help with performance debugging?

It helps identify latency bottlenecks by visualizing the path and timing of requests across all service dependencies, allowing you to pinpoint exactly where delays occur.

Can I use this with existing microservices?

Yes, the skill provides code snippets and configuration guidance to integrate tracing into existing services regardless of their current deployment state.

Does it handle context propagation between services?

Yes, it generates the necessary configuration to ensure trace IDs and spans are passed correctly between services via HTTP headers or message brokers.

Distributed Tracing Setup

Name: Distributed Tracing Setup
Author: intent-solutions-io

byintent-solutions-io

Analytics & Monitoring

Automates the implementation of distributed tracing and observability for microservices to provide end-to-end request visibility.

About

This skill streamlines the process of establishing distributed tracing within microservices architectures, enabling developers to monitor and debug complex request flows across multiple services. It guides users through selecting backend providers like Jaeger or Zipkin, generates necessary instrumentation code using OpenTelemetry, and configures context propagation to ensure seamless observability. By identifying performance bottlenecks and latency issues, this skill helps maintain high-performing, reliable distributed systems through standardized monitoring practices.

Key Features

Automated OpenTelemetry instrumentation for microservices
Support for major backends like Jaeger, Zipkin, and Datadog
Performance bottleneck identification and troubleshooting guidance
Trace context propagation configuration across service boundaries
0 GitHub stars
Custom sampling strategy generation for high-traffic environments

Use Cases

Setting up end-to-end observability in a new microservices project
Debugging high latency and performance issues in existing request flows
Standardizing tracing instrumentation across multiple backend services

About

Key Features

Automated OpenTelemetry instrumentation for microservices
Support for major backends like Jaeger, Zipkin, and Datadog
Performance bottleneck identification and troubleshooting guidance
Trace context propagation configuration across service boundaries
0 GitHub stars
Custom sampling strategy generation for high-traffic environments

Use Cases

Setting up end-to-end observability in a new microservices project
Debugging high latency and performance issues in existing request flows
Standardizing tracing instrumentation across multiple backend services