Skill UI

Automates creation of A/B test configurations for ML deployment, guiding users through best practices, code samples, and validation steps so production models are served with monitoring and rollout control.

Guides teams through planning, designing, and running statistically sound A/B tests with hypothesis framing, sample sizing, metric selection, implementation strategies, and analysis checkpoints for systematic growth experimentation.

Automates the creation of Airflow DAGs for ETL and streaming data workflows, offering best-practice guidance, production-ready code samples, and validation against common pipeline standards.

Automates API health checking guidance by activating when you mention api health checker, offering best practices, integration patterns, code samples, and validation for third-party APIs, webhooks, and SDK workflows.

Automates guidance for API throttling setup, including best practices, code samples, and configuration validation across REST, GraphQL, OpenAPI, and authentication scenarios to ensure scalable API development.

Auto-activating skill that guides teams through creating validated Artillery load-testing configurations, offering best-practice patterns, sample scripts, and configuration validation for performance, load, and benchmarking use cases.

Auto-activating skill that guides teams through creating validated Artillery load-testing configurations, offering best-practice patterns, sample scripts, and configuration validation for performance, load, and benchmarking use cases.

This comprehensive guide covers the best practices for building production-ready, scalable serverless applications on Amazon Web Services (AWS). Learn to leverage core services like Lambda, API Gateway, and DynamoDB, and implement advanced patterns such as event-driven architectures (SQS/SNS). The content emphasizes performance optimization, robust error handling, structured logging, and deploying infrastructure using SAM/CDK.

This comprehensive guide covers the best practices for building production-ready, scalable serverless applications on Amazon Web Services (AWS). Learn to leverage core services like Lambda, API Gateway, and DynamoDB, and implement advanced patterns such as event-driven architectures (SQS/SNS). The content emphasizes performance optimization, robust error handling, structured logging, and deploying infrastructure using SAM/CDK.

This library serves as a low-level exporter for Python applications, enabling the reliable transfer of comprehensive OpenTelemetry telemetry data—including traces, metrics, and logs—to Azure Application Insights. It provides robust configuration options, including connection string setup, Azure AD authentication, custom sampling, and offline storage management, ensuring complete and reliable observability.

This comprehensive guide demonstrates how to implement enterprise-grade Role-Based Access Control (RBAC) and organization management using Clerk. It covers setting up multi-tenant architectures, defining granular custom roles and permissions (e.g., data:write, org:admin), integrating SSO (SAML/OIDC), and securely protecting both Next.js routes (via middleware) and client components based on user roles and specific permissions. Ideal for building secure, scalable SaaS applications.

Automates CloudWatch alarm setup by providing best-practice guidance, sample configurations, and validation for AWS compute, storage, networking, and serverless workloads.