Dr Code

50 System Design Concepts Every Developer Should Understand to Build Better Software Systems ① Scalability → Handling increasing users and workloads. ② Availability → Keeping systems accessible when users need them. ③ Reliability → Ensuring systems work consistently without failures. ④ Fault Tolerance → Keeping systems running when components fail. ⑤ High Availability → Minimizing downtime through redundancy. ⑥ Performance → Making applications respond quickly and efficiently. ⑦ Latency → Measuring how long a request takes. ⑧ Throughput → Measuring how many requests a system handles. ⑨ Load Balancing → Distributing traffic across multiple servers. ⑩ Horizontal Scaling → Adding more servers to handle increased workloads. ⑪ Vertical Scaling → Increasing the resources of an existing server. ⑫ Reverse Proxy → Forwarding client requests to backend servers. ⑬ API Gateway → Managing and routing incoming API requests. ⑭ Caching → Storing frequently accessed data for faster retrieval. ⑮ CDN → Delivering content from geographically distributed servers. ⑯ Database Sharding → Splitting data across multiple database instances. ⑰ Database Replication → Maintaining copies of data across servers. ⑱ Database Indexing → Speeding up database queries. ⑲ SQL vs NoSQL → Understanding relational and non-relational databases. ⑳ Database Partitioning → Dividing large datasets into smaller sections. ㉑ ACID Properties → Ensuring reliable database transactions. ㉒ CAP Theorem → Understanding consistency, availability, and partition tolerance. ㉓ Eventual Consistency → Allowing distributed replicas to synchronize over time. ㉔ Strong Consistency → Ensuring users see the latest committed data. ㉕ Distributed Systems → Coordinating multiple computers to work together. ㉖ Microservices Architecture → Breaking applications into independent services. ㉗ Monolithic Architecture → Building an application as one deployable unit. ㉘ Event-Driven Architecture → Communicating through events and messages. ㉙ Message Queues → Handling asynchronous communication between services. ㉚ Publish-Subscribe Pattern → Distributing messages to interested subscribers. ㉛ Kafka → Streaming and processing real-time event data. ㉜ WebSockets → Enabling real-time, two-way communication. ㉝ REST APIs → Designing resource-based HTTP interfaces. ㉞ GraphQL → Allowing clients to request specific data. ㉟ gRPC → Enabling efficient service-to-service communication. ㊱ Rate Limiting → Controlling how frequently clients can make requests. ㊲ Throttling → Restricting excessive traffic to protect services. ㊳ Circuit Breaker Pattern → Preventing repeated calls to failing services. ㊴ Retry Pattern → Reattempting failed operations safely. ㊵ Idempotency → Ensuring repeated requests don't create unintended effects. ㊶ Service Discovery → Finding available services dynamically. ㊷ Leader Election → Selecting a coordinator in distributed systems. ㊸ Consensus Algorithms → Helping distributed nodes agree on shared decisions. ㊹ Data Replication → Keeping information synchronized across multiple locations. ㊺ Disaster Recovery → Restoring systems after major failures. ㊻ Observability → Understanding system behavior through logs, metrics, and traces. ㊼ Monitoring & Alerting → Detecting problems before they become major incidents. ㊽ Authentication & Authorization → Verifying identities and controlling access. ㊾ Data Encryption → Protecting sensitive information during storage and transmission. ㊿ Backpressure → Preventing overloaded services from overwhelming other components. Don't just memorize these concepts. Understand why they exist, when to use them, and how they interact. That's how you move from writing code to designing systems that scale, survive failures, and serve millions of users. Follow @e_opore for more software engineering and system design content.