API Design for AI Inference Systems | Scalability, Security & Performance Guide

Description

🚀 Want to understand how AI systems like ChatGPT, recommendation engines, and fraud detection systems actually work behind the scenes? In this video, we break down API Design and Microservices Architecture for AI Inference Systems in a simple and practical way. 🔍 What You’ll Learn: - What is API Design in AI systems - How Microservices improve scalability - Importance of Stateless APIs - API Versioning explained - Rate Limiting & Security best practices - Load Balancing & Caching for performance - Real-world AI use cases (chatbots, recommendation engines, fraud detection) 💡 Why This Matters: Modern AI applications rely heavily on well-designed APIs and scalable architectures. Without proper design, systems can fail under load, become insecure, or difficult to maintain. 📌 Key Concepts Covered: API Design, Microservices, AI Inference, Scalability, Load Balancing, Rate Limiting, Caching, Authentication, Monitoring, System Architecture 🎯 Who is this for? - Beginners learning AI systems - Developers & Engineers - Tech Enthusiasts - Students preparing for interviews 🔥 Don’t forget to LIKE 👍, SHARE 🔁 and SUBSCRIBE 🔔 for more content on AI, Technology & System Design! 📢 Stay tuned for upcoming videos where we explain each concept in depth with real-world examples! #API #Microservices #AI #SystemDesign #TechExplained #Scalability #Ai #MachineLearning #ArtificialIntelligence #Microservices #API