Explanations built around an animation you can step through.
An ordered route through the algorithms, with practice by pattern.
Design practice, capacity sizing, and a regex safety check.
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All 202 →How to release new versions with minimal risk: rolling updates, blue-green switches, canaries that expose a change to a small share of real traffic first, automated rollback on bad metrics, feature flags that separate deploy from release, and the database migrations that make rollback possible.
How an app like Uber or Ola matches riders with drivers: a high-write location service indexed by geo cell, matching ranked by ETA rather than distance, a trip state machine, live tracking over WebSockets, surge pricing, and the consistency questions behind 'two riders, one driver'.
Designing a crawler that fetches billions of pages politely: the URL frontier with per-host queues, robots.txt and rate limits, DNS caching, de-duplicating URLs with Bloom filters and content with fingerprints, avoiding crawler traps, freshness scheduling, and scaling it all across machines.
A grid is a graph: each cell is a node, and its neighbours are its edges. How flood fill (the paint-bucket tool) and 'number of islands' are BFS or DFS over that implicit graph, how to avoid stack overflows and revisits, and the family of grid problems the same template solves.