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?

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