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

0•

분석 및 모니터링

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

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.

주요 기능

01Expert TraceQL query construction for Grafana Tempo

020 GitHub stars

03Request-level root cause analysis for distributed systems

04Cross-correlation between traces, Loki logs, and Mimir metrics

05Latency and error bottleneck identification strategies

06Guidance on optimizing queries by avoiding high-cardinality attributes

사용 사례

01Investigating latency spikes in microservices using specific duration filters

02Refining observability workflows with structured TraceQL query patterns

03Debugging production errors by linking failed trace IDs to specific log entries

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add timbuchinger/loadout tempo-troubleshoot

For use in Claude.ai and ChatGPT

주요 기능

01Expert TraceQL query construction for Grafana Tempo

020 GitHub stars

03Request-level root cause analysis for distributed systems

04Cross-correlation between traces, Loki logs, and Mimir metrics

05Latency and error bottleneck identification strategies

06Guidance on optimizing queries by avoiding high-cardinality attributes

사용 사례

01Investigating latency spikes in microservices using specific duration filters

02Refining observability workflows with structured TraceQL query patterns

03Debugging production errors by linking failed trace IDs to specific log entries

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add timbuchinger/loadout tempo-troubleshoot

For use in Claude.ai and ChatGPT