Skill UI

This guide provides comprehensive methods for load testing and capacity planning of Vercel serverless deployments. Learn how to use professional tools like k6 and autocannon to simulate realistic traffic spikes, measure latency (P95, P99), analyze cold start impact, and tune concurrency settings (Fluid Compute) to ensure optimal application performance and scalability under heavy load.

A comprehensive guide to optimizing Vercel deployment performance. This skill covers advanced techniques such as edge caching implementation (using Cache-Control headers), leveraging Incremental Static Regeneration (ISR), minimizing serverless function cold starts, and optimizing bundle size. Use this when facing slow page load times, needing to improve Core Web Vitals, or requiring robust, scalable deployment performance.

Modal is a serverless cloud platform for running Python code on demand, including GPU-accelerated AI/ML workloads. Use for deploying models, serving web APIs, batch processing, and scaling Python applications to cloud containers with automatic scaling from zero to thousands of instances. Supports custom container images, persistent storage, and sub-second cold starts for low-latency inference.

This guide provides comprehensive strategies to significantly boost the performance and reliability of applications deployed on Fly.io. Techniques covered include eliminating cold starts (auto-stop/start), right-sizing Virtual Machines based on workload demands, implementing multi-region deployment for low latency, and optimizing connection pooling for databases. Essential for scaling modern SaaS applications.

A comprehensive set of reusable patterns for structured incident triage in AWS environments. Includes pre-built Logs Insights queries for detecting errors, latency spikes, cold starts, and OOM events. Also provides systematic correlation methods linking CloudWatch alarms to deployment events, and a decision tree to narrow the blast radius scope from account to resource.

A comprehensive guide for researchers preparing academic artifacts for voluntary, post-acceptance evaluation (e.g., HPCA). It outlines best practices for structuring submissions for cold-start evaluators, defining reproducibility tiers (full reproduction, regeneration from logs, inspection), and managing computational budgets to successfully earn IEEE reproducibility badges.

A read-only repository explorer for cold-start code orientation and cross-file localization. It locates where relevant code lives using broad parallel search and returns only compact path:line citations. Use when the exact file or symbol is not yet known; skip when direct search already works.

Build and deploy serverless functions on AWS Lambda. Configure triggers like API Gateway, S3, and SQS. Manage IAM permissions and optimize performance for cold starts. Ideal for event-driven applications, scheduled tasks, and lightweight APIs. Includes deployment via CLI and SAM templates.

This skill enables building production-ready serverless applications on AWS. It covers core components like Lambda functions, API Gateway, and DynamoDB. It also includes event-driven patterns using SQS and SNS, deployment strategies with SAM or CDK, and optimization techniques for cold starts. Ideal for backend development and cloud-native architecture implementation.

Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js programming models.

This skill enables building production-ready serverless applications on Google Cloud Platform using Cloud Run. It covers containerized services, event-driven functions, cold start optimization, and Pub/Sub integration. Includes guidance on memory management, concurrency settings, and scaling bottlenecks to ensure efficient deployment and cost control.