How to Scale a System from 0 to 10 million+ Users

How To Scale a Development Team

As hackers, we’re familiar with the need to scale web servers, databases, and other software systems. An equally important challenge in a growing business is scaling your development team.

The Value of Getting Closer to the Work

Scaling The core problem of scaling a team is that not everyone can know everything. Scaling is the work of systematizing that – so that things are understandable, knowable. It’s turnin…

‘Give Away Your Legos’ and Other Commandments for Scaling Startups

Molly Graham helped forge a work culture at Facebook that's withstood huge amounts of growth. Today, she's something of a rapid scaling expert. Here's the key to doing it right, she says.

Your startup culture needs to act like a mosquito, not a termite colony

I'd like to talk to you about scaling. Specifically, startup scaling. At a high level, what you want is: A: more customers, more growth, more reach. You do this using: B: cost: hosting, staff, tokens, licenses, etc. Scaling is not minimising cost. Scaling is increasing external output faster than

Horizon

Deploy and manage MCP servers at scale.

Scale-Up! | Odoo

Have you ever dreamed of starting your own business ? Or wondered how you could get started? With Odoo Scale-Up! you will learn all of that through 10 different business cases.

binhnguyennus/awesome-scalability

The Patterns of Scalable, Reliable, and Performant Large-Scale Systems

Scaling PostgreSQL to power 800 million ChatGPT users

An inside look at how OpenAI scaled PostgreSQL to millions of queries per second using replicas, caching, rate limiting, and workload isolation.

How To Scale Your Model

Training LLMs often feels like alchemy, but understanding and optimizing the performance of your models doesn't have to. This book aims to demystify the science of scaling language models: how TPUs (and GPUs) work and how they communicate with each other, how LLMs run on real hardware, and how to parallelize your models during training and inference so they run efficiently at massive scale. If you've ever wondered “how expensive should this LLM be to train” or “how much memory do I need to serve this model myself” or “what's an AllGather”, we hope this will be useful to you.

Declarative Server with NixOS: A Reproducible Infrastructure | Mustafa Erbay

A technical guide exploring how to create a declarative server configuration with NixOS, covering reproducibility and rollback processes.