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2 posts

Everything about Scaling

Scaling - it’s the reason we’re all using this cloud thing anyway, right? Surely all of your applications have been tested to effortlessly scale from 0 to 1,000 in milliseconds, and your databases can rebalance after scaling within minutes with zero impact to anything important, correct?

Don’t worry, I don’t think anyone has fully cracked this nut. But why is this? What makes it so difficult to actually get ALL the benefits of the infinitely flexible cloud?

Distributed System Design — Scaling from 0–1K, 1K -10K, 10K-100K, 100K-1M, and 1M to 1B users.

One of the most challenging aspects of building a distributed system is scaling it to handle different levels of user traffic. In this blog post, I will discuss some of the common techniques and trade-offs involved in scaling a distributed system from 1 to 1 billion users. I will also provide some step-by-step explanations for each scale.

  1. Scaling from 0–1K,
  2. Scaling from 1K -10K,
  3. Scaling from 10K-100K,
  4. Scaling from 100K-1M,
  5. Scaling from 1M to 1B users