When considering the scale of an engineering project, there are not many companies that can compare to Instagram. In terms of scale alone, Instagram has a sheer scope of scale that is rarely matched.
Instagram has been using Python and the Django web framework to build out one of the largest deployments of this type since its beginning. The purpose of this blog is to provide insight into why Instagram made this choice, how the architecture has evolved, and how it continues to be a benchmark for backend development today.
1. The Power of Python for Backend Engineering
Python is an interpreted language that is high-level with a focus on productivity for developers. Since Instagram was just a startup in 2010, the “speed of getting to market” is more important than “speed of execution”.
Why is Python still a top language choice for developers?
Readability: The syntax of Python closely matches the English language, which allows developers who are part of large teams to more easily collaborate.
Large Libraries: Python has a library for every type of application; specifically, for example, PyTorch for Artificial Intelligence (AI), or Celery for task queues.
Scalability: Scaling a system is a common misconception; however, the fact of the matter is that with proper scaling methods and system management, it is more than possible to horizontally scale a Python application out to more than 1000 servers.
2. Why Django, the Framework for Perfectionists?
Instagram is built using Django, a web application framework that allows for efficient development and has an easy-to-use design, resulting in a good product.
MVT Architecture: MVT or Model View Template architecture is the separation of business logic, data, and user interface within a web application, such as Django.
Each of these components serves a specific purpose in Instagram's architecture:
Model: Used to define the database structure for user profiles, posts, and likes.
View: Handles business logic (e.g.,double-tap, like)
Template: Renders the initial web-based layouts for users.
3. Why Instagram Chose Python & Django?
The founders of Instagram, Kevin Systrom and Mike Krieger, decided to build their website using the Python programming language for the platform. With the amount of traffic they anticipated receiving, they needed a stack that could handle that amount of traffic (i.e., hockey stick growth).
Speed of development: Python’s web framework (Django) has a “batteries included” philosophy, meaning that the founders did not have to build their own user registration/ authentication system or ORM (object-relational mapping) for the website.
Talent pool: The popularity of Python makes it much easier to find and train engineers to work with the language than if they were to build the website in a lower-level language, such as C++.
Security: Django provides multiple layers of protection from security threats (i.e., SQL injection, cross-site scripting (XSS), and CSRF), which are especially important for a social network such as Instagram.
4. Understanding Instagram’s High-Level Architecture
Instagram's backend is not built from one single script, but it is a large orchestration of services.
Simplified request flow of the Instagram application:
User request → Load balancer → Nginx → Gunicorn (WSGI) → Django app → PostgreSQL/Redis → Response.
Core Backend Components:
Django ORM: allows managing many complex relationships of billions of followers and following counts.
PostgreSQL: The primary repository for user data.
Celery and RabbitMQ: Used to complete tasks asynchronously, such as sending out notifications or processing videos in the background.
Engineering Challenges: Scaling to 2 Billion Users
As Instagram grew, it faced limitations of Python's Global Interpreter Lock (GIL), and its engineering team became leaders in optimizing Python.
Moving to Python 3: One of Instagram's well-known achievements was the completion of one of the largest migrations from Python 2 to 3, yielding significant memory usage improvement.
Cinder: Instagram (Meta) developed Cinder, a performance-oriented version of CPython, to make their code run even faster.
Asyncio: Essentially, we have migrated from synchronous to asynchronous code execution to allow for more connections concurrently.
Key Takeaways for Developers
Building an app today, you can learn from Instagram's experiences and realize the following:
- The cost of a developer's time is more than the cost of CPU time.
- Django is a viable choice for apps with high traffic.
- Optimizations are done later, build fast using Python, and optimize as you grow your app or reach bottlenecks.
Conclusion
The accomplishment of Instagram demonstrates how effective Python and Django can be when given solid architectural support and emphasis on writing good code, allowing for development to happen within a framework that can have a worldwide impact.
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