Do I need to be a DevOps expert to use this?

No, the skill automates the configuration and startup process. You only need Docker and Docker Compose installed on your local machine to run the setup.

Does this stack support cost tracking?

Yes, it includes specialized dashboards for token usage analysis and cost projections based on your Claude Code interactions.

How do I access the monitoring dashboards?

Once the stack is successfully deployed, you can access the pre-configured Grafana dashboards by visiting http://localhost:3000 in your browser.

Is my Claude Code data sent to the cloud?

No, this setup is entirely local. All logs, metrics, and traces are stored on your local machine within the .observability directory, ensuring data privacy.

What does this skill actually install on my machine?

It deploys a localized Docker-based stack including Grafana for visualization, Loki for logs, Tempo for traces, Prometheus for metrics, and Grafana Alloy as an OTLP collector.

Observability Stack Setup

Name: Observability Stack Setup
Author: adaptationio

byadaptationio

Analíticas y Monitorización

Deploys a complete LGTM and Grafana Alloy observability stack for monitoring Claude Code performance, costs, and traces.

Acerca de

This skill automates the local deployment of a comprehensive observability infrastructure specifically tailored for Claude Code. By leveraging Docker Compose, it sets up Grafana, Loki, Tempo, Prometheus, and Grafana Alloy to provide deep insights into token usage, tool execution latency, and error rates. It includes pre-configured dashboards that allow developers to visualize session data, track real-time costs, and debug complex tool call traces, making it an essential tool for anyone building or optimizing workflows within the Claude Code ecosystem.

Características Principales

Pre-built dashboards for cost analysis, tool performance, and error tracking
Built-in health checks and automated service verification
Automated Grafana Alloy OTLP collector configuration for telemetry ingestion
Persistent data storage for historical analysis and session review
0 GitHub stars
Full LGTM stack deployment including Loki, Grafana, Tempo, and Prometheus

Casos de Uso

Monitoring Claude Code token usage and API costs in real-time to manage budgets
Debugging tool call failures and performance bottlenecks via distributed tracing
Setting up local development environments with comprehensive logging and metrics

Acerca de

Características Principales

Pre-built dashboards for cost analysis, tool performance, and error tracking
Built-in health checks and automated service verification
Automated Grafana Alloy OTLP collector configuration for telemetry ingestion
Persistent data storage for historical analysis and session review
0 GitHub stars
Full LGTM stack deployment including Loki, Grafana, Tempo, and Prometheus

Casos de Uso

Monitoring Claude Code token usage and API costs in real-time to manage budgets
Debugging tool call failures and performance bottlenecks via distributed tracing
Setting up local development environments with comprehensive logging and metrics