Skill UI

This skill provides comprehensive observability tools for Groq API integrations. It instruments the client to track critical performance metrics such as Time to First Token (TTFT), total latency, token throughput, and estimated cost. Furthermore, it sets up Prometheus exporters and alert rules to monitor rate limit status and detect performance degradation in real-time, ensuring robust production monitoring.

This skill provides a comprehensive framework for monitoring Mistral AI API usage in production. It includes an instrumented client wrapper (TypeScript) to automatically capture critical metrics like latency, token consumption, cost, and error rates. Furthermore, it integrates with Prometheus for metric storage and Grafana for visualization, allowing users to set up sophisticated alerting rules for performance degradation, rate limiting, or cost spikes.

This skill guides the implementation of comprehensive, real-time monitoring for APIs. It covers collecting key metrics (latency, error rates, request rate), setting up health and readiness endpoints, building detailed Grafana dashboards, and implementing SLO-based alerting (following the RED method). Use this when you need to ensure API reliability, high availability, and performance in a production environment.

Designs comprehensive, production-ready observability strategies by integrating metrics, logs, and traces. This tool guides the setup of SLI/SLO frameworks, optimizes noisy alerting configurations, and generates detailed dashboards, ensuring deep visibility into service health and performance.

Provides a comprehensive monitoring solution for the Perplexity Sonar API. It tracks critical performance metrics, including latency (p95), cost per query, error rates, and citation quality. This skill is essential for implementing production monitoring dashboards, configuring proactive alerts (e.g., high latency, zero citations), and ensuring the API's stability and high-quality output in real-world applications.

A comprehensive guide for diagnosing production performance issues in Qdrant vector databases. Learn how to systematically check the optimizer status, analyze high memory usage (OOM crashes), and troubleshoot slow query latencies using key metrics and dedicated API endpoints. Essential for maintaining optimal operational health.

This comprehensive guide details how to set up end-to-end observability for ClickHouse. It covers extracting key metrics using built-in system tables (e.g., query logs, merge status), integrating the metrics with Prometheus, and finally visualizing performance, throughput, and health indicators on Grafana dashboards. Essential for monitoring production-grade ClickHouse deployments and configuring reliable alerting.