Skill UI

This guide provides a comprehensive framework for debugging and analyzing AgentCore runtime sessions using CloudWatch Logs Insights. It details advanced techniques like OpenTelemetry (OTEL) span correlation, resolving session IDs to trace IDs, and structuring complex query queries. Use this when investigating agent execution flows, diagnosing tool call failures, analyzing latency, or building detailed behavioral timelines.

This skill provides a comprehensive guide to instrumenting Algolia search services for enterprise-grade observability. It integrates core monitoring patterns, including Prometheus metrics (latency, error rates, request counts), OpenTelemetry distributed tracing, and structured logging. Use this to achieve deep insights into search performance, user experience, and system health in production environments.

Implement comprehensive observability for Canva Connect API integrations using industry best practices. This guide covers gathering critical metrics (latency, error rates, rate limits) with Prometheus, implementing distributed tracing with OpenTelemetry, and setting up robust alert rules. Essential for monitoring API health, optimizing performance, and ensuring system reliability in SaaS environments.

This skill provides comprehensive observability for ClickUp API integrations. It instruments API calls to capture key metrics like request rate, latency percentiles, error counts, and rate limit usage. It integrates with Prometheus for metrics, OpenTelemetry for distributed tracing, and structured logging for detailed event tracking. Use it to build robust dashboards and set up critical alerts for API performance issues.

A comprehensive solution for setting up production-grade observability for Cohere API v2. It integrates Prometheus metrics, OpenTelemetry tracing, and robust alerting mechanisms. This skill tracks critical operational data including per-endpoint latency, token consumption (input/output), error rates, and usage costs, ensuring reliable monitoring for AI-powered applications.

This skill provides a comprehensive observability stack for Flexport logistics integrations. It sets up Prometheus metrics for API health tracking, uses structured logging (pino) for debugging, implements OpenTelemetry tracing for latency analysis, and defines actionable Grafana dashboards and alert rules. This ensures reliable, performant, and fully monitored logistics operations.

This comprehensive skill guides developers on implementing full observability for HubSpot API integrations. It details how to instrument calls using industry-standard tools, including Prometheus metrics (Counters, Histograms, Gauges), OpenTelemetry tracing, structured logging (pino), and configuring AlertManager rules. Use this when needing to monitor CRM integration health, track latency, detect errors, or manage rate limits for mission-critical API operations.

This skill provides a comprehensive guide to setting up full observability for Intercom integrations. It covers implementing Prometheus metrics (counters, histograms, gauges) to track API request status, latency, and error rates. Furthermore, it demonstrates structured logging using Pino and OpenTelemetry tracing, offering deep, actionable insights into integration health. Ideal for DevOps, backend engineering, and robust system monitoring.

This skill integrates LangChain 1.0 and LangGraph 1.0 into standard OpenTelemetry (OTEL) backends (e.g., Jaeger, Honeycomb, Tempo). It solves critical observability gaps by ensuring correct prompt content capture, propagating spans across complex subgraphs, and providing five LLM-specific Service Level Objectives (SLOs) like latency and cost. Ideal for multi-tenant, compliance-sensitive, or existing OTEL stack environments where LangSmith is unsuitable.

Provides comprehensive observability for Miro REST API v2 integrations. It captures critical metrics using Prometheus (request rates, latency, error tracking) and OpenTelemetry traces for end-to-end request flow visibility. Includes structured logging for detailed debugging and robust rate limit management, ensuring your applications are highly reliable and maintainable.

Implement a comprehensive observability stack for Webflow Data API v2 integrations. This skill provides structured code using Prometheus metrics, OpenTelemetry distributed tracing, and structured logging (pino) to monitor API call frequency, latency, error rates, and rate limit usage. Ideal for developers building robust, production-grade Webflow-connected SaaS applications that require deep performance insights and reliable alerting.

This component is an essential extension for KubeSphere Observability Platform, designed for comprehensive collection, processing, and storage of Kubernetes and KubeSphere audit events. It supports various sinks, including OpenSearch and Doris, and provides an API for querying historical audit data, ensuring robust auditing capabilities for platform operations.