Master EF Core query optimization, N+1 prevention, compiled queries, distributed caching, and strategic indexing for high-throughput ASP.NET Core APIs.
GraphQL APIs with Apollo Server: Schema Design & Optimization
Learn to build production-ready GraphQL APIs with Apollo Server and Node.js. Schema design, query optimization, subscriptions, and scaling patterns.
gRPC and Protocol Buffers for Microservices: High-Performance Communication at Scale
Learn gRPC basics, Protocol Buffer design, streaming patterns, and load balancing for production microservices. Practical guide with .NET and Node.js examples.
Azure Bicep Multi-Tier Deployments with GitHub Actions
Learn to automate multi-tier Azure deployments using Bicep templates and GitHub Actions. Practical patterns for Container Apps, environments, and scaling.
AI Powered Blazor WebAssembly: Client Side LLM Integration
Build offline capable AI UIs with Blazor WebAssembly. Learn LLM streaming, client side prompt engineering, and production patterns for type safe AI web apps.
Production Django APIs for AI SaaS: Async, Celery, PostgreSQL
Build production-grade Django APIs for AI SaaS with async views, Celery task queues, PostgreSQL RLS multi-tenancy, and WebSocket streaming patterns.
FastAPI WebSocket Production: Real-Time AI Agent Communication
Build production WebSocket servers in FastAPI for agent-to-agent communication, connection pooling, backpressure handling, and scaling to thousands of concurrent connections.
Django Microservices for AI: Async, JSONB, Production Scaling
Build scalable AI microservices with Django 5.x async views, PostgreSQL JSONB for embeddings, and production deployment patterns for AI data pipelines.
Production FastAPI Backends for LLM APIs: Async & Observability
Build scalable Python AI backends with FastAPI: async patterns, Pydantic validation, structured outputs, and observability for production LLM services.
FastAPI Elasticsearch: Scalable AI Search Infrastructure
Build production-grade search with FastAPI and Elasticsearch. Real-time indexing, relevance tuning, vector search, and deployment patterns for AI applications.