Mastering System Design: 10 Key Pillars Every Engineer Should Know

Every Engineer Should Know Designing scalable, reliable, and efficient systems starts with understanding these 10 core pillars that form the foundation of modern system architecture. Elaborated details provided here

1. APIs & Security Covers REST, gRPC, GraphQL, rate limiting, authentication methods (JWT, OAuth), TLS/SSL, and protection against DDoS and MITM attacks.

• REST
• gRPC
• GraphQL
• Rate limiting
• JWT
• OAuth
• TLS/SSL
• DDoS protection
• MITM prevention

2. Caching Improves performance and reduces load with strategies like LRU, session persistence, and multi-level caching.

• LRU
• Session persistence
• Multi-level caching
• L1: In-memory cache (e.g., Ehcache).
• L2: Distributed cache (e.g., Redis).
• CDN: Cloudflare caching static assets (e.g., React.js files).

3. Proxies Includes reverse and forward proxies, load balancing methods, and advanced routing (e.g., path-based, least outstanding requests).

• Reverse proxy
• Forward proxy
• Load balancing
• Round-robin: AWS ELB distributing requests evenly.
• Least outstanding requests: Kubernetes sending traffic to the least busy pod.
• Path-based routing

4. Messaging Ensures smooth inter-service communication with queues, pub/sub models, polling, streaming, and idempotent processing.

• Queues
• Pub/sub
• Polling
• Streaming
• Idempotency

5. Features Clarifies system goals and constraints, aligning stakeholder needs while balancing consistency, availability, and tradeoffs.

• CAP tradeoff
• Consistency (CP)
• Availability (AP)
• Example

6. Users Considers user types, access patterns, usage spikes, accessibility, and scalability based on demographics and behavior.

• User types
• Access patterns
• Read-heavy: Wikipedia (90% reads).
• Write-heavy: IoT sensor data (e.g., Tesla cars sending telemetry).
• Usage spikes
• Scalability

7. Data Model Explores relational vs NoSQL databases, indexing, horizontal scaling, sharding, ETL pipelines, and distributed query models like MapReduce.

• Relational DB
• NoSQL
• Indexing
• Sharding
• ETL
• MapReduce

8. Geography & Latency Tackles region-aware system performance using CDNs, DNS, network latency optimization, and response-time tuning.

• CDN
• GeoDNS
• Latency optimization
• AWS Global Accelerator reducing ping times for multiplayer games (e.g., Fortnite).
• Edge computing: Tesla processing autopilot data locally in cars.

9. Server Capacity Focuses on compute and storage provisioning (CPU, RAM, SSD), scaling strategies, parallel processing, and partitioning.

• Compute
• Storage
• Scaling
• Vertical: Upgrading a MySQL server from 8GB to 32GB RAM.
• Horizontal: Adding more Elasticsearch nodes for log analysis.
• Partitioning

10. Availability & Microservices Addresses fault tolerance, microservices orchestration, leader election, redundancy, observability, and service mesh principles.

• Fault tolerance
• Retries: AWS Lambda retrying failed S3 uploads.
• Circuit breaker: Netflix Hystrix stopping cascading failures.
• Microservices
• Uber’s split services (rides, payments, notifications).
• Service mesh: Istio managing traffic between Kubernetes pods.
• Leader election
• Redundancy
• Observability

Use this blueprint to build high-performance architectures that are scalable, secure, and production-ready. Whether you’re preparing for system design interviews or building the next big product - these pillars are your foundation.