In this post we'll explore how Stack Overflow - one of the most popular websites in the world - runs its services, all with monoliths.

• Problem: Building good software systems is hard
• Solution: Analyze and learn from real world systems

Stack Overflow

Stack Overflow is one of the top 250 most popular websites in the world. It's most known as a popular Q&A site for developers but also runs Stack Exchange - Q&A software for public and private usecases at scale.

Some stats:

• 2B+ page views per month
• Pages load in less than 20ms

Stack Overflow System Architecture

Stack Overflow's System Architecture

Application

Let's start with the main Stack Overflow / Stack Exchange application. It's a monolithic, multi-tenant .NET app running on 9 servers.

• Servers: 9 (450 (via Stack Exchange) - 600 (via Arcoverde) rps)
• Stack: C# + ASP.NET MVC (highly-optimized for low memory usage to avoid the garbage collector)

Data

Stack Overflow runs on 4 large SQL Servers - 2 for Stack Overflow, 2 for Stack Exchange. They use Dapper ORM - a lightweight, performant .NET ORM (the same ORM I use in F# projects).

• Stack Overflow: 2 SQL Servers (1.5 TB RAM, 2.8 TB total size, 11k qps)
• Stack Exchange, Careers, Meta: 2 SQL Servers (786GB RAM, 3.9 TB total size, 13k qps)
• App <> DB: Dapper ORM

Note: The size of the DB cache means ~1/3 can be stored in memory at one time.

Cache

Most of the caching is actually done within the databases. Arcoverde mentioned that Stack Overflow attempted more advanced caching but uniform access patterns across all Q&A questions led to poor cache hit rates, rendering the complexity / cost not worth it (see Arcoverde - Hanselminutes Podcast).

• 2 Redis Servers (256GB, 60k ops)

Other highlights

• The whole stack runs at 5-10% capacity. This means it's theoretically possible for the whole setup to run off 1 server.
• The majority of the stack runs almost entirely on-prem. A few small services are broken out and hosted elsewhere for ergonomics.
• Stack Overflow has ~50 engineers as of July 2022

Next Steps

Another data point that monoliths scale! For more on scaling monoliths, check out Software Monoliths for Scale

References

• Stack Exchange - Performance Page
• Roberta Arcoverde, Director of Engineering at Stack Overflow on The Hanselminutes Podcast