Editorial Roadmap¶

This roadmap guides content development; it is not a reason to publish shallow material. Accuracy and review take priority over a fixed quota. Backend engineering and system design remain the center of the handbook; DSA and GenAI are complementary interview and engineering tracks.

Backend and language foundations¶

[x] Repository overview and contribution standards
[x] Python concurrency: threads, asyncio, and processes
[x] Python data model, memory, and garbage collection
[x] Go concurrency: goroutines, channels, cancellation, and worker pools
[x] Java concurrency for backend services — Java Memory Model, safe publication, bounded executors, virtual threads, synchronization, interruption, and lifecycle
[x] HTTP fundamentals, REST semantics, idempotency, and pagination
[x] SQL indexes, query plans, transactions, and isolation
[x] Zero-downtime database schema migrations — expand/contract, rolling-deploy compatibility, batched backfills, and staged constraints

Backend systems¶

[x] API validation, authentication, authorization, and versioning
[x] Application caching, consistency, invalidation, and stampede protection
[ ] General message delivery, retries, ordering, and dead-letter queues
[ ] Microservice communication and resilience
[x] Distributed rate limiting and quota enforcement for multi-tenant APIs
[x] Database connection pooling and capacity budgeting — per-process limits, deployment-wide budgets, queueing, transaction pooling, and saturation diagnosis
[x] Distributed coordination with leases, fencing tokens, and leader election — owner identity, monotonic generations, resource-side stale-writer rejection, database locks, Redis leases, and cluster leadership
[ ] Backpressure, admission control, and load shedding
[ ] Logs, metrics, traces, and SLOs

System design¶

[x] Capacity estimation and bottleneck analysis — workload modeling, peak traffic, concurrency, storage, bandwidth, replica sizing and failure headroom
[x] Notification service design — multichannel fan-out, preferences, delivery state, provider behavior, bounded retries and recovery
[x] URL shortener design — random code allocation, redirect semantics, caching, lifecycle consistency, and abuse controls
[x] Database sharding for multi-tenant backends — partitioning versus distributed sharding, shard-key selection, tenant locality, virtual buckets, hotspots, scatter-gather costs, and resharding
[ ] Replication, consistency, and recovery
[ ] Job queue and durable background-work design
[ ] Low-level design exercises

Data Structures and Algorithms¶

[x] DSA learning path and topic map
[x] Complexity analysis and Big-O
[x] Arrays, strings, hash maps, and sets — dynamic arrays, Unicode semantics, hash contracts, membership patterns, and tested Python, Go, and Java examples
[ ] Two pointers, sliding windows, and prefix sums
[ ] Linked lists, stacks, queues, and binary search
[ ] Trees, heaps, graphs, and traversal algorithms
[ ] Backtracking, greedy algorithms, and dynamic programming
[ ] Mixed interview problems with tested Python, Go, and Java solutions

GenAI engineering¶

[x] Production-focused GenAI learning path and topic map
[ ] LLM fundamentals, tokens, context windows, and structured outputs
[ ] Backend model integration: streaming, timeouts, retries, and fallbacks
[ ] Embeddings, chunking, vector search, hybrid retrieval, and reranking
[ ] RAG architecture, evaluation, grounding, and citations
[ ] Tool calling, bounded agents, and LangGraph workflows
[ ] Evaluation datasets, regression testing, and observability
[ ] Prompt injection, authorization boundaries, and data isolation
[ ] Production cost, latency, caching, and reliability

Cloud and DevOps¶

[x] AWS VPC networking — subnet tiers, route tables, security groups, NAT, endpoints, DNS, and multi-AZ reachability
[x] AWS IAM for backend workloads — role trust, temporary credentials, ECS/EC2/EKS workload identity, scoped permissions, PassRole, and policy evaluation
[ ] AWS compute, storage, managed databases, and queues
[ ] Docker images and container security
[ ] Kubernetes workloads and troubleshooting
[ ] CI/CD, deployment strategies, and rollback
[ ] Terraform state and modules
[ ] Linux process, memory, networking, and filesystem troubleshooting

Each entry should have a distinct learning objective, practical depth, references, and a duplication review. Update existing pages when behavior or best practices change.