System design and cloud architecture interviews are critical for software engineers, backend developers, and cloud architects. This cheat sheet covers system design fundamentals, cloud concepts, scalability, database strategies, and real-world interview questions to help you ace your next interview. 💡

🏗️ System Design Fundamentals

Key Concepts

  • Scalability: Ensuring a system can handle increasing loads efficiently.
  • Availability: Ensuring uptime and reliability with failover mechanisms.
  • Latency vs Throughput: Response time vs number of processed requests.
  • Consistency vs Partition Tolerance (CAP Theorem):
    • CP (Consistency, Partition Tolerance): Strong consistency (e.g., traditional RDBMS).
    • AP (Availability, Partition Tolerance): Eventual consistency (e.g., NoSQL, DynamoDB).
    • CA (Consistency, Availability): Only works if there's no network partition.
  • Horizontal vs Vertical Scaling:
    • Horizontal Scaling: Adding more machines (e.g., load balancing).
    • Vertical Scaling: Increasing CPU, RAM on a single machine.
  • Load Balancing: Distributing traffic across multiple servers to ensure reliability.
  • Caching: Improving performance by storing frequently accessed data (Redis, Memcached).
  • Rate Limiting: Controlling API access to prevent abuse (Token Bucket, Leaky Bucket).

Common System Design Interview Questions

  1. Design Twitter (Feed System, Rate Limiting, Scaling)
  2. Design a URL Shortener like Bit.ly
  3. Design an E-commerce Checkout System
  4. Design a File Sharing System (Google Drive, Dropbox)
  5. Design a Distributed Messaging Queue (Kafka, RabbitMQ)

🌩️ Cloud Architecture & Distributed Systems

Cloud Providers & Services

  • AWS, Azure, Google Cloud: Leading cloud providers.
  • Compute Services:
    • AWS EC2, Lambda | GCP Compute Engine, Cloud Functions | Azure VMs, Functions.
  • Storage Services:
    • AWS S3, EBS | GCP Cloud Storage, Persistent Disk | Azure Blob Storage.
  • Database Services:
    • AWS RDS, DynamoDB | GCP Firestore, Cloud SQL | Azure CosmosDB, SQL Database.
  • Networking Services:
    • AWS VPC, CloudFront | GCP VPC, Load Balancer | Azure Virtual Network.

Cloud Design Patterns

  • Microservices: Breaking down applications into independent, loosely coupled services.
  • Serverless Architecture: Using cloud functions to run event-driven workloads without managing servers.
  • Event-Driven Architecture: Services communicate asynchronously via events (Kafka, SNS, Pub/Sub).
  • Multi-Region Deployment: Distributing applications across multiple regions for redundancy.
  • Service Mesh: Managing communication between microservices (Istio, Linkerd).

Database Scaling & Optimization

  • Sharding: Splitting a database into smaller chunks distributed across multiple servers.
  • Replication: Copying data across multiple nodes for high availability.
  • Indexing: Speeding up queries with efficient lookups (B-Trees, Hash Indexing).
  • SQL vs NoSQL:
    • SQL (Relational): Strong consistency (e.g., PostgreSQL, MySQL, SQL Server).
    • NoSQL (Non-Relational): Scales horizontally (e.g., MongoDB, DynamoDB, Cassandra).

Caching Strategies

  • Write-Through Cache: Writes to both database and cache simultaneously.
  • Write-Back Cache: Writes to cache first, then periodically updates the database.
  • Cache Invalidation: Removing stale cache entries (Least Recently Used - LRU, Time-To-Live - TTL).

🛡️ Security & Reliability

Common Cloud Security Concerns

  • Authentication & Authorization:
    • JWT, OAuth, OpenID, API Gateway authentication.
  • Data Encryption:
    • At rest (AWS KMS, GCP Cloud KMS), In transit (TLS, SSL).
  • DDoS Protection:
    • Cloudflare, AWS Shield, GCP Armor.
  • Secrets Management:
    • HashiCorp Vault, AWS Secrets Manager, GCP Secret Manager.
  • Monitoring & Logging:
    • AWS CloudWatch, GCP Stackdriver, Azure Monitor.

High Availability & Fault Tolerance

  • Failover Mechanisms: Redirecting traffic when a failure occurs.
  • Auto-Scaling: Adjusting resources dynamically to handle changing loads.
  • Distributed Consensus Algorithms: Ensuring consistency across distributed systems (Paxos, Raft).
  • Chaos Engineering: Introducing failures to test system resilience (Netflix Chaos Monkey).

🔥 Final Tips for System Design & Cloud Interviews

✅ Understand trade-offs between availability, consistency, and performance.
✅ Use diagrams to explain architecture decisions clearly.
✅ Think in terms of scalability and how your design handles increased load.
✅ Discuss monitoring and failure recovery – interviewers love resilience planning.
✅ Stay updated with cloud technologies – AWS, GCP, Azure keep evolving.

🚀 Good luck with your system design and cloud interviews! You've got this! 🔥

💬 What’s the toughest system design question you’ve faced? Let’s discuss in the comments!