Canonical Concepts
Explore foundational engineering concepts. Each entity includes 30s Spark summaries, 3–5m breakdown, 15m deep dives, scenario practice, and design defense.
Concept Unlock Graph
Explore how mastering prerequisite concepts unlocks advanced engineering patterns.
Select a concept to focus its path graph
Click any concept node to focus strictly on the incoming and outgoing paths for that specific concept.
Showing 1–10 of 39 Concepts
In-Memory Caching & Event Loop Architecture
Eliminate DB latency bottlenecks using single-threaded event loops, Epoll I/O multiplexing, and LRU/LFU memory eviction.
Takeaway: Use single-threaded I/O multiplexing for ultra-fast, lock-free key-value operations; guard against blocking O(N) calls and un-bounded memory growth.
Rate Limiting & Token Buckets
Protect downstream APIs and services from Denial-of-Service spikes using Token Bucket and Sliding Window Log algorithms.
Takeaway: Use Token Bucket for bursting tolerance or Sliding Window Counter for smooth memory-efficient window tracking.
Event-Driven Architecture & Message Streaming
Decouple microservices using distributed commit logs, message queues, and event streams.
Takeaway: Use append-only distributed logs (Kafka) for durable replayable streams.
Load Balancing & Consistent Hashing
Distribute incoming network traffic across server pools using Round-Robin and Consistent Hashing rings.
Takeaway: Use Layer 4 for TCP throughput and Layer 7 for HTTP path routing.
Database Indexing: B-Trees vs LSM-Trees
Optimize query read latencies using balanced search trees or log-structured merge-tree write buffers.
Takeaway: Choose B-Trees for read-heavy workloads (PostgreSQL/MySQL) and LSM-Trees for write-heavy append workloads (Cassandra/RocksDB).
Quorum Consistency & Raft Consensus
Guarantee strong consistency across distributed database nodes using Quorum math (R + W > N) and Raft leader election.
Takeaway: Use Quorum (R=2, W=2, N=3) for strict consistency across database clusters; use Raft for leader election and state machine replication.
Database Sharding & Range Partitioning
Horizontally partition massive database tables across multiple database instances using shard keys.
Takeaway: Select high-cardinality, evenly distributed shard keys (e.g. user_id) to avoid hotspot shards.
Message Queues & DLQ Backpressure
Buffer asynchronous job workloads and buffer spikes using Dead Letter Queues and backpressure mechanisms.
Takeaway: Use Dead Letter Queues (DLQ) to capture poison-pill messages after N failed retries.
B-Trees vs LSM-Trees Storage Engines
Compare B+ Tree read-optimized node layouts against LSM-Tree append-only SSTable write buffers.
Takeaway: Mastering B-Trees vs LSM-Trees Storage Engines enables robust software design, high availability, and efficient resource utilization.
Graph Traversal & Pathfinding: BFS, DFS & Dijkstra
Traverse graphs efficiently using Breadth-First Search, Depth-First Search, and Dijkstra shortest path algorithms.
Takeaway: Mastering Graph Traversal & Pathfinding: BFS, DFS & Dijkstra enables robust software design, high availability, and efficient resource utilization.