Skill UI

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.

Automates setting up synthetic monitoring by defining critical endpoints, crafting uptime, transaction, and API scenarios, and configuring alerts/dashboards to keep application performance and availability under proactive watch.

Automates SLA monitor setup within enterprise workflows, delivering step-by-step guidance, best practices, code/config snippets, and validation to align monitoring, compliance, and integration standards.

A comprehensive guide for optimizing costs when integrating the Speak API. This skill covers usage monitoring, selecting optimal API tiers, and implementing efficient audio processing pipelines. It is essential for developers managing language learning platform operations to ensure cost efficiency while maintaining high performance.

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.

A comprehensive checklist designed for developers to ensure a language learning integration (Speak) is robust and ready for production deployment. It covers critical technical areas including API authentication, audio processing pipelines, rate limiting strategies, monitoring and alerting setup, and adherence to global data compliance standards (e.g., GDPR, FERPA). Use this when implementing or troubleshooting production-grade features.

Automates spike test setup workflows by offering guided steps, best practices, code snippets, and validations across load/stress benchmarking and monitoring scenarios.

Provides SRE guidance for defining SLIs/SLOs, managing error budgets, automating toil, and configuring monitoring/alerting so teams can scale reliable services and respond to incidents effectively.

Orchestrates Statuscake monitoring tasks through Rube MCP and Composio toolkits, guiding workflow discovery, connection checks, and schema-compliant executions for reliable automation.

Automates guidance for streaming inference setup, covering best practices in ML deployment, serving, monitoring, and production-ready configurations whenever you ask about streaming inference patterns or implementation.

Automates Supabase operations through the Rube MCP toolkit, letting you query tables, inspect schemas, execute SQL, manage projects/orgs, and monitor storage or edge functions with workflow-aware guidance.

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.