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Service Mesh Observability Patterns Guide

service-mesh-observability

sickn33/antigravity-awesome-skills

A comprehensive guide covering observability patterns for service meshes like Istio and Linkerd. Learn how to implement the three pillars—Metrics, Traces, and Logs—to monitor service health, visualize dependencies, track golden signals (latency, traffic, errors, saturation), and debug microservice communication issues across complex distributed systems.

Distributed Tracing Setup

setting-up-distributed-tracing

jeremylongshore/claude-code-plugins-plus-skills

Automates setting up distributed tracing across a microservices landscape by guiding backend selection, instrumentation strategy, and configuration generation to enable end-to-end observability and aid performance troubleshooting.

Centralized Log Aggregation

setting-up-log-aggregation

jeremylongshore/claude-code-plugins-plus-skills

Automates deployment and configuration of ELK, Loki, or Splunk log aggregation platforms by gathering requirements, crafting secure scalable configs, and producing deployment code for observability needs.

Speak API Health and Observability Monitoring

speak-observability

jeremylongshore/claude-code-plugins-plus-skills

This skill provides comprehensive observability for the Speak language learning platform. It monitors critical metrics such as API health status, assessment latency, session usage, and detailed pronunciation score distributions. It is essential for developers implementing robust, production-grade monitoring systems and managing large-scale language learning operations.

Comprehensive Supabase Monitoring and Observability

supabase-observability

jeremylongshore/claude-code-plugins-plus-skills

Use this resource to implement comprehensive end-to-end monitoring and observability for Supabase projects. It guides users through analyzing API metrics, diagnosing slow database queries using pg_stat_statements, managing log drains for external aggregation, and setting up custom alerts, ensuring optimal project health and performance.

TwinMind Observability and Health Monitoring

twinmind-observability

jeremylongshore/claude-code-plugins-plus-skills

Provides comprehensive observability for the TwinMind AI meeting system. This skill allows users to monitor critical performance metrics, including transcription quality (using Ear-3 model), meeting coverage, action item extraction accuracy, and memory vault health. It is essential for implementing robust, enterprise-grade AI workflows and managing the operational status of advanced meeting AI applications.

Vast.ai GPU Monitoring and Cost Tracking

vastai-observability

jeremylongshore/claude-code-plugins-plus-skills

This skill provides comprehensive monitoring capabilities for GPU instances running on Vast.ai. It collects key metrics including GPU utilization, instance uptime, temperature, and accumulated costs. Use this when setting up operational monitoring dashboards, configuring critical alerts (e.g., idle GPUs, high temperature, budget overruns), or automating resource usage tracking in a cloud computing environment.

Configure Vercel Observability and Monitoring

vercel-observability

jeremylongshore/claude-code-plugins-plus-skills

This guide provides a comprehensive setup for Vercel observability. It covers enabling built-in analytics, collecting detailed runtime logs, implementing structured logging, configuring external log drains (e.g., Datadog, Sentry), and integrating OpenTelemetry tracing. Use this when monitoring production deployments and setting up robust error tracking.

Vertex Agent Builder

vertex-agent-builder

jeremylongshore/claude-code-plugins-plus-skills

Scaffolds production-ready generative AI agents on Vertex AI with Gemini models, multi-modal tools, RAG, and Cloud Run/Endpoint deployment, including observability and evaluation for enterprise scenarios.

AI Tool Observability and Productivity Tracking

windsurf-observability

jeremylongshore/claude-code-plugins-plus-skills

Monitor the adoption, feature usage, and overall Return on Investment (ROI) of AI tools like Windsurf. This skill provides comprehensive analytics, including daily active users, completion acceptance rates, and estimated time saved. It allows teams to set up usage alerts, identify underutilized seats, and build custom extensions to measure deep usage patterns, ensuring maximum team efficiency and quantifying AI impact.

Building Production gRPC Services with Go

sickn33/antigravity-awesome-skills

A comprehensive guide for designing and implementing production-grade microservices using gRPC in Go. Covers best practices for API contract standardization with Protobuf and Buf, securing service-to-service communication via mTLS, and integrating deep observability using OpenTelemetry interceptors. Ideal for building high-performance, reliable internal APIs.

Temporal Go Pro Guide

temporal-golang-pro

sickn33/antigravity-awesome-skills

Expert guide for building durable distributed systems with the Temporal Go SDK, covering deterministic workflow rules, mTLS worker configuration, advanced patterns, and testing/observability strategies for production workloads.

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