Skill UI

A comprehensive guide to implementing Perplexity's API integration at various scales. It provides three validated architectural blueprints—Direct Widget, Cached Research Layer, and Multi-Query Pipeline—allowing developers to choose the optimal structure based on required query volume, latency goals, and complexity. Learn how to scale from simple search widgets to automated, high-volume research pipelines.

Fully managed, auto-scaling vector database tailored for production AI workloads such as RAG, recommendations, and semantic search, offering hybrid dense+sparse search, namespaces, metadata filters, and <100ms latency on serverless infrastructure.

A comprehensive guide to selecting the optimal architecture for Replit applications. It compares three scaling models—single-file scripts (prototypes), modular apps (MVPs), and multi-service systems (large scale)—to help developers choose the correct database, storage, and deployment strategy as their project grows.

This comprehensive skill manages the full lifecycle deployment of applications on the Replit platform. It supports three key deployment types: Static (for frontends), Autoscale (for variable APIs), and Reserved VM (for always-on services). Use this for configuring production environments, setting up custom domains, implementing health checks, managing environment secrets, and optimizing scaling strategies.

This comprehensive guide provides detailed steps for load testing and capacity planning of Replit deployments. Learn how to benchmark performance using industry tools like k6 and autocannon, optimize Autoscale behavior, right-size Reserved VMs, and manage database connection pools. It covers optimizing cold start times and ensuring high availability under variable and peak traffic loads.

A comprehensive, step-by-step guide for deploying applications on Replit to production environments. It covers crucial best practices, including configuring deployment settings, managing environment secrets, implementing robust health checks, handling global errors, setting up custom domains, and defining rollback strategies. Essential for developers preparing an app for a live launch or scaling up.

This advanced guide provides strategies for scaling Sentry in high-traffic, enterprise-level applications handling millions of events daily. It details implementing adaptive sampling based on endpoint criticality, using adaptive error deduplication to manage quotas, and optimizing the SDK for minimal runtime overhead, ensuring robust visibility even under extreme load.

A comprehensive guide covering the principles of production-grade server management. Topics include process control (PM2, systemd), advanced monitoring strategies (Grafana, metrics), structured logging, scaling decisions (horizontal/vertical), and security best practices. It teaches systematic thinking for ensuring high availability, reliability, and scalability in complex systems.

This pattern provides established best practices for implementing efficient similarity search in production systems. It is crucial for building semantic search engines, implementing Retrieval-Augmented Generation (RAG), creating advanced recommendation systems, and optimizing retrieval performance when scaling to millions of vectors.

Guides post-training of GLM-class LLMs with Megatron-LM and SGLang, focusing on GRPO rollout generation, custom data buffers, and tight RL scaling workflows for research and production use.

Master advanced techniques for scaling Supabase projects to handle high production load. This skill covers six critical layers: implementing read replicas for analytics, optimizing connectivity using connection pooling (Supavisor), upgrading compute resources, utilizing CDN caching for Storage, deploying Edge Functions regionally, and performing database table partitioning. Ideal for engineers preparing for traffic spikes or optimizing large-scale database architectures.

This skill guides the setup of a robust, multi-environment architecture for Supabase, ensuring complete data isolation between development, staging, and production projects. It covers best practices for managing separate environment-specific secrets, safe database migration promotion (db push), environment-aware client initialization, and implementing safeguards to prevent accidental cross-environment operations in production. Essential for scaling SaaS applications.