skill-based roadmap · Computer Science
System Design Roadmap
A structured path from foundational computer networking and OS concepts through distributed systems, scalability patterns, and real-world architecture design — taking you from zero to job-ready for senior engineering roles.
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1. Stage 1: Foundations
Networking Basics
Understanding HTTP, TCP/IP, DNS underpins every distributed system.
Operating System Concepts
Processes, threads, and memory management explain backend performance limits.
Databases 101
SQL vs NoSQL tradeoffs are central to every system design decision.
APIs & Communication Protocols
REST, GraphQL, and gRPC are the primary ways services communicate.
2. Stage 2: Core Building Blocks
Load Balancers
Distributing traffic evenly is critical to handling scale.
Caching
Caching reduces latency and database load at scale.
Message Queues & Event Streaming
Async communication decouples services and improves resilience.
Content Delivery Networks (CDN)
CDNs dramatically reduce latency for globally distributed users.
3. Stage 3: Scalability & Reliability Patterns
Horizontal vs Vertical Scaling
Knowing when to scale out vs up is a foundational architecture decision.
Database Sharding & Replication
Partitioning data enables massive read/write throughput at scale.
CAP Theorem & Consistency Models
CAP tradeoffs guide every distributed data store selection.
Fault Tolerance & Circuit Breakers
Graceful degradation keeps systems alive when components fail.
4. Stage 4: Distributed Systems Deep Dive
Microservices Architecture
Microservices are the dominant pattern for large-scale production systems.
Distributed Consensus (Raft & Paxos)
Consensus algorithms power leader election and distributed coordination.
Event-Driven Architecture
Event sourcing and CQRS enable audit trails and decoupled services.
Service Discovery & API Gateways
Dynamic service registration enables zero-downtime deployments.
5. Stage 5: Storage & Data at Scale
Relational Database Internals
Indexes, query planning, and ACID depth unlock real optimization skills.
NoSQL Databases
Document, column, graph, and key-value stores each solve specific problems.
Object & Blob Storage
S3-compatible storage is the backbone for media and large data workloads.
Search Engines
Full-text and faceted search require dedicated index engines like Elasticsearch.
6. Stage 6: Real-World Architecture & Observability
Designing for Observability
Logging, metrics, and tracing are essential for production reliability.
Cloud Infrastructure & IaC
Modern systems live in the cloud; provisioning knowledge is expected.
Security in System Design
Auth, secrets management, and zero-trust belong in every design.
System Design Case Studies
Studying real architectures (YouTube, Twitter, Uber) cements all patterns.
7. Stage 7: Interview Readiness
System Design Interview Framework
A repeatable approach (requirements → estimate → design → tradeoffs) wins interviews.
Back-of-Envelope Estimation
Capacity estimation shows interviewers you can reason about scale.
Mock System Design Practice
Repeated practice under time pressure is the only way to get interview-ready.
Architecture Decision Records (ADR)
Writing ADRs demonstrates senior engineering communication skills.