New video: Change Data Capture in System Design Interviews.

Learn how CDC streams database writes to caches, search indexes, and downstream services without dual writes. Premium: hellointerview.com/twitter/to/lea…

When a user uploads a 4K video, don't make them wait for encoding to finish. Return "upload successful" the moment the file lands, then queue the encoding and CDN distribution to background workers. The user stays engaged while the heavy work happens out of band.

Maximal Square looks like a search problem and is a DP problem with one of the cleanest recurrences you will meet.

Almost all system design prep is written for one level, and probably not yours. Candidates at every level prepare the same way: memorise components, explain every tradeoff, cover all the bases.

Instagram has 500 million daily users. Beyonce has 300 million followers. When she posts, something has to stop that becoming 300 million writes in a few seconds.

Fanning out a post to every follower's feed cache makes opening Instagram a fast read. Then a celebrity with 200M followers posts once and triggers 200M writes. So you don't fan those out at all.

A government contractor with 8 years of experience and zero big tech background just landed Netflix, Google, and Meta offers.

Connect Four is most people's first low-level design interview. Seven columns, six rows, drop a disc, first to line up four wins. The rules take a sentence and the design takes forty minutes.

Everyone reaches for sharding first when writes get heavy. But a single modern box with 200 cores, 10Gb NICs, and SSDs pushes write throughput way further than people assume. Tune the hardware and DB before you distribute anything.

You can know every database on the planet and still run out of time in a system design interview with half a system drawn. Build a complete first version before going deep.

CAP says you get two of consistency, availability and partition tolerance. Networks fail whether you planned for it or not, so partition tolerance is never the one you drop.

Partition Kafka by advertiserId and Nike launches a campaign: all their clicks hash to one partition. That partition gets slammed while the rest sit idle. Adding more partitions doesn't help, Nike is still one key hashing to one place.

Atomicity, consistency, isolation, durability. Four words most candidates can expand and far fewer can say what breaks without each one.

Your database can't keep up with writes. A bigger server, sharding, batching and a queue can all help, but they help in different ways.

The best system design material is written by the people running the systems. Five worth reading, starting with Netflix on chaos engineering and streaming to 230 million people. netflixtechblog.com

Redis is single-threaded on purpose. One core loop processing commands means no locks, no context-switch thrash, no coordinating threads over shared data. Want more CPU? Run more instances in a cluster.

DynamoDB scales without you thinking about it, which is exactly why candidates reach for it and then cannot answer what a partition key costs them.