How does it help with observability correlation?

It provides specific patterns to link traces with Loki logs and Prometheus/Mimir metrics, enabling a holistic view of your system's performance.

What systems benefit most from this skill?

It is ideal for microservices architectures and distributed environments utilizing the Grafana observability stack for tracing.

Does it support high-cardinality data?

The skill includes best practices to avoid high-cardinality attributes like UUIDs as primary filters, ensuring your queries remain performant.

What is the Tempo Troubleshooting skill?

It is a specialized capability for Claude Code designed to help developers query and debug distributed traces within the Grafana Tempo ecosystem.

Can this skill execute TraceQL queries directly?

No, the skill assists in crafting, optimizing, and explaining TraceQL queries, but it does not execute them directly in your infrastructure.

Tempo Troubleshooting

Name: Tempo Troubleshooting
Author: timbuchinger

bytimbuchinger

分析与监控

Optimizes distributed tracing workflows by crafting efficient TraceQL queries and correlating traces with Loki logs and Mimir metrics.

关于

The Tempo Troubleshooting skill empowers developers to master distributed tracing within the Grafana Tempo ecosystem. It provides expert guidance on constructing precise TraceQL queries, identifying performance bottlenecks, and debugging complex request-level errors. By integrating best practices for correlating traces with logs (Loki) and metrics (Mimir), this skill facilitates rapid root cause analysis and helps maintain system health through efficient observability patterns and structural query optimization.

主要功能

Expert TraceQL query construction for Grafana Tempo
0 GitHub stars
Request-level root cause analysis for distributed systems
Cross-correlation between traces, Loki logs, and Mimir metrics
Latency and error bottleneck identification strategies
Guidance on optimizing queries by avoiding high-cardinality attributes

使用场景

Investigating latency spikes in microservices using specific duration filters
Refining observability workflows with structured TraceQL query patterns
Debugging production errors by linking failed trace IDs to specific log entries

关于

主要功能

Expert TraceQL query construction for Grafana Tempo
0 GitHub stars
Request-level root cause analysis for distributed systems
Cross-correlation between traces, Loki logs, and Mimir metrics
Latency and error bottleneck identification strategies
Guidance on optimizing queries by avoiding high-cardinality attributes

使用场景

Investigating latency spikes in microservices using specific duration filters
Refining observability workflows with structured TraceQL query patterns
Debugging production errors by linking failed trace IDs to specific log entries