What tools does this skill use for load testing?

This skill primarily utilizes k6 for load testing and performance benchmarking of Replit integrations, supporting ramp-up, steady-state, and stress test stages.

Does it support connection management?

Yes, it provides implementation patterns for TypeScript connection pooling to manage Replit API clients efficiently and prevent resource exhaustion.

How do I measure headroom for my Replit application?

The skill includes capacity calculation logic that estimates maximum Requests Per Second (RPS) and headroom percentage based on current resource metrics.

Can this skill help with Kubernetes configuration?

Yes, it provides standardized patterns for Horizontal Pod Autoscalers (HPA) using CPU utilization and custom metrics like queue depth.

How do I trigger these scaling features in Claude?

You can activate this skill by using natural language phrases like 'replit load test', 'replit scale', or 'replit capacity' during your Claude Code session.

Replit Load & Scale Optimizer

Name: Replit Load & Scale Optimizer
Author: jeremylongshore

byjeremylongshore

•

983

Despliegue y DevOps

Implements robust load testing, auto-scaling configurations, and capacity planning strategies for Replit-based applications and integrations.

Acerca de

The Replit Load & Scale skill provides a comprehensive framework for ensuring Replit integrations can handle production-level traffic. It enables developers to automate performance testing using k6, configure Kubernetes Horizontal Pod Autoscalers (HPA) for dynamic scaling, and perform data-driven capacity planning. By providing standardized templates for benchmarks and implementation patterns for connection pooling, this skill helps teams maintain high performance and reliability across their Replit infrastructure.

Características Principales

Standardized capacity planning and headroom calculation logic
Connection pooling patterns for efficient resource management
Automated k6 load testing scripts for Replit API endpoints
983 GitHub stars
Kubernetes HPA configuration for horizontal scaling based on custom metrics
Structured performance benchmark templates for reporting

Casos de Uso

Configuring auto-scaling rules for Kubernetes-deployed Replit services
Stress testing Replit integrations before a major production launch
Benchmarking P95/P99 latency across different traffic loads to identify bottlenecks

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills replit-load-scale

For use in Claude.ai and ChatGPT

Download Skill

GitHub