The Replit Team

At Replit, we are on a mission to empower the next billion software creators. As we reflected on our mission and heard feedback from our community, we grew confident in our pursuit to create an end-to-end experience that represents the best developer tool membership in the market to go from idea to software, fast.


Today, we’re excited to announce Replit Core, a singular plan that we aim to continue investing in for years to come.


With Replit Core, you get:


Access to advanced Replit AI features

Save time and code faster with Replit's industry-leading AI coding assistant, currently powered by GPT-4.

Debug code, get intelligent autocomplete suggestions, and convert natural language to code with one click.


Announcing Replit Core - The Essential Membership for Builders

Luis Héctor Chávez

Figuring out how to install third-party libraries can derail people from learning to code or starting a new side project. We built the Universal Package Manager (UPM for short) to save people from having to think about package installation at all. Just import the library, press run, and UPM will install it into your repl!

Every time you run a repl or a repl wakes up, UPM checks to see if it needs to download and install any dependencies. This is handy (no matter what's gone inside your repl, it will always have the dependencies it needs) but slow: UPM needs to download typically tens of megabytes worth of packages, extract them on the local filesystem, and sometimes also pre-compile them for better runtime performance.

Or at least it used to be slow until yesterday when we enabled the Python package cache, so now the most popular Python packages are pre-populated in pip's cache (/home/runner/.cache/pip), so the download step is going to be mostly gone for the vast majority of Python repls! It also uses pre-built wheels as much as possible to avoid even having to pre-compile code.

How does it work?

We had two goals in mind when we started designing this:

it should be as transparent as possible, which meant that users would still be able to add packages to the local cache while avoiding copying files around (which would have defeated the purpose of using a cache in the first place), and

Introducing the Python package cache

Connor Brewster

To make it so that anyone with a web browser can code on Replit, our backend infrastructures runs on preemptible VMs. That means the computer running your code can shutdown at any time! We've made it really fast for repls to reconnect when that happens. Despite our best efforts, though, people had been seeing repls stuck connecting for a long time. After some profiling and digging into the Docker source code, we found and fixed the problem. Our session connection error rate dropped from 3% to under 0.5% and our 99th percentile session boot time dropped from 2 minutes to 15 seconds.

There were many different causes of stuck repls, varying from: unhealthy machines, race conditions that lead to deadlock, and slow container shutdowns. This post focuses how we fixed the last cause, slow container shutdowns. Slow container shutdowns affected nearly everyone using the platform and would cause a repl to be inaccesible for up to a minute.

Replit Architecture

Before going in depth on fixing slow container shutdowns, you'll need some knowledge of Replit's architecture.

When you open a repl, the browser opens a websocket connection to a Docker container running on a preemptible VM. Each of the VMs run something we call conman, which is short for container manager.

We must ensure that there is only a single container per repl at anytime. The container is used to facilitate multiplayer features, so its important that every user in the repl connects to the same container.

Killing Containers at Scale

Amjad Masad

At Repl.it, our mission is to make programming more accessible, more creative, and more fun. A place away from the modern software development grind. It’s an ambitious mission, and it's already resonated with millions of coders who followed their creative energy to build great apps, like repl.email, a free email service built and hosted entirely on Repl.it and available to anyone with a Repl.it account.

Repl.it has grown so much in the past few years:

To give you an idea of the scale we're operating on, we now serve 120k concurrent containers. That is 120,000 computers started at once

We doubled our team every year for the past 4 years: 2^4 = 16, and are still hiring

Repl.it went from a simple online REPL to a world-leading collaborative coding environment focused on learning and prototyping

However, with growth comes problems:

Introducing the Python package cache

Killing Containers at Scale

Focusing on a solid foundation