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.
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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.
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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
- Design Twitter (Feed System, Rate Limiting, Scaling)
- Design a URL Shortener like Bit.ly
- Design an E-commerce Checkout System
- Design a File Sharing System (Google Drive, Dropbox)
- Design a Distributed Messaging Queue (Kafka, RabbitMQ)
🌩️ Cloud Architecture & Distributed Systems
Cloud Providers & Services
- AWS, Azure, Google Cloud: Leading cloud providers.
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Compute Services:
- AWS EC2, Lambda | GCP Compute Engine, Cloud Functions | Azure VMs, Functions.
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Storage Services:
- AWS S3, EBS | GCP Cloud Storage, Persistent Disk | Azure Blob Storage.
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Database Services:
- AWS RDS, DynamoDB | GCP Firestore, Cloud SQL | Azure CosmosDB, SQL Database.
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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).
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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
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Authentication & Authorization:
- JWT, OAuth, OpenID, API Gateway authentication.
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Data Encryption:
- At rest (AWS KMS, GCP Cloud KMS), In transit (TLS, SSL).
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DDoS Protection:
- Cloudflare, AWS Shield, GCP Armor.
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Secrets Management:
- HashiCorp Vault, AWS Secrets Manager, GCP Secret Manager.
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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!
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