How to use this page
This is a map, not a lesson. Each row names a roadmap topic and jumps to the post and section that teaches it. The topics are numbered 1 to 107 and grouped into the same tracks as the roadmap. The twenty-eight Interview Roadmap Deep Dives (Parts 1 to 28) fill the gaps the original series left; the earlier guides, case studies, and AI posts cover the rest.
Every post ends with numbered interview questions and a quick revision list, so together they work as revision material: read a section, answer its questions aloud, and tick the checklist at the bottom.
Coverage note. Every topic below has a home, but depth varies. Topics marked (overview) are covered in a section or paragraph rather than a full post: for example the transformer architecture and GPU hardware inside the serving posts, and Kubernetes objects inside the production engineering post. If an interviewer targets one of those in depth, supplement with the linked sources at the end of the post.
Track 1: High-level system design
| # |
Roadmap topic |
Where to read |
| 1 |
System design fundamentals, requirements, estimation |
Foundations and data, capacity estimation |
| 2 |
Databases and distributed storage |
Foundations: storage, SQL vs NoSQL |
| 3 |
Storage engines and database internals |
B-trees vs LSM trees, indexes, ACID and isolation |
| 4 |
Database scaling |
Replication, sharding, hot partitions |
| 5 |
Distributed consistency (CAP, PACELC, quorums) |
Consistency models and quorums, CAP stated carefully |
| 6 |
Caching |
Caching deep dive, failure modes |
| 7 |
Networking and transport |
Networking and APIs, HTTP versions and TLS path, gRPC deep dive |
| 8 |
Load balancing |
Load balancing and global traffic |
| 9 |
API design |
Pagination, idempotency, rate limiting |
| 10 |
Event-driven and asynchronous systems |
Architecture and messaging |
| 11 |
Apache Kafka deep dive |
Kafka core concepts, consumer groups |
| 12 |
Messaging reliability |
Delivery semantics, retries and DLQs |
| 13 |
Distributed systems fundamentals |
Why agreement is hard |
| 14 |
Raft consensus |
Raft in plain language |
| 15 |
Logical clocks |
Clocks lie, logical clocks |
| 16 |
Distributed locking |
Locks and why they are dangerous |
| 17 |
Reliability patterns |
Timeouts, retries, breakers, bulkheads, rate limiting and overload |
| 18 |
High availability and disaster recovery |
Redundancy and failover, ultra-resilient patterns, recovery and RTO/RPO |
| 19 |
Big data architecture |
Batch, stream, CDC, lakehouse, CDC |
| 20 |
Microservice architecture patterns |
Monolith or microservices, outbox, saga, CQRS and event sourcing, service mesh |
| 21 |
HLD case studies |
Interview workbook and the case-study list below |
| 22 |
Video streaming system |
YouTube, Netflix, Hotstar live, CDN |
| 23 |
Location-based services |
Geohash, quadtree, S2, H3, ride-hailing dispatch |
| 24 |
Advanced database and search systems |
Search, autocomplete, time series, ad click aggregation |
| 25 |
Collaborative editing |
OT and CRDTs |
| 26 |
Stock exchange architecture |
Order book and matching engine, broker concerns |
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