System design has many terms that sound similar… …but they solve very different problems. Here’s the simplest breakdown worth saving: LATENCY How long does one request take? THROUGHPUT How many requests can the system process over time? BANDWIDTH How much data can move through the network at once? — REPLICATION Copies the same data across multiple machines. SHARDING Splits different parts of the data across multiple machines. — POLLING Keeps asking: “Has anything changed?” WEBHOOK Automatically sends a notification when something happens. — PROCESS An independent program with its own memory. THREAD A smaller execution unit that shares memory within a process. — LOAD BALANCER Distributes traffic across multiple servers. API GATEWAY Controls how clients access APIs. — CONCURRENCY Handles multiple tasks during the same period. PARALLELISM Executes multiple tasks at exactly the same time. — MONOLITH Built and deployed as one complete application. MICROSERVICES Split into smaller services that can be developed and deployed independently. Small differences. Big impact when designing production systems. Save this for your system design and AI engineering interviews. . . . [AI Engineering, AI Engineer, System Design, Backend Engineering, Software Engineering, Machine Learning Engineering, MLOps, LLMOps, Production AI, Latency, Throughput, Bandwidth, Replication, Sharding, Polling, Webhook, Process, Thread, Load Balancer, API Gateway, Concurrency, Parallelism, Monolith, Microservices, Distributed Systems, Scalability, High Availability, API Design, Cloud Engineering, DevOps, Technical Interviews] #softwaredeveloper #llm #ai #machinelearning #datascience - @jam.with.ai