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At Instagram, we have one of the world’s largest deployments of the Apache Cassandra database. We began using Cassandra in 2012 to replace Redis and support product use cases like fraud detection, Feed, and the Direct inbox. At first we ran Cassandra clusters in an AWS environment, but migrated them over to Facebook’s infrastructure when the rest of Instagram moved. We’ve had a really good experie
At Instagram, we have the world’s largest deployment of the Django web framework, which is written entirely in Python. We began using Python early on because of its simplicity, but we’ve had to do many hacks over the years to keep it simple as we’ve scaled. Last year we tried dismissing the Python garbage collection (GC) mechanism (which reclaims memory by collecting and freeing unused data), and
Today we are excited to announce we’re open-sourcing MonkeyType, our tool for automatically adding type annotations to your Python 3 code via runtime tracing of types seen. MotivationAt Instagram we have hundreds of engineers working on well over a million lines of Python 3. Every day we have new engineers joining the team from other projects and other languages who need to ramp up quickly and get
The Instagram community is bigger and more diverse than ever before. 800m people now visit every month, 80% of whom are outside of the United States. As the community grows, it becomes more and more important that our app can withstand diverse network conditions, a growing variety of devices, and non-traditional usage patterns. The client performance team at Instagram New York is focused on making
React Native has come a long way since it was open-sourced in 2015. Fewer than two years later, it’s being used not only in Facebook and Facebook Ads Manager, but also in many other companies, from Fortune 500 companies to hot new startups. Developer velocity is a defining value of Instagram’s mobile engineering. In early 2016, we started exploring using React Native to allow product teams to ship
By dismissing the Python garbage collection (GC) mechanism, which reclaims memory by collecting and freeing unused data, Instagram can run 10% more efficiently. Yes, you heard it right! By disabling GC, we can reduce the memory footprint and improve the CPU LLC cache hit ratio. If you’re interested in knowing why, buckle up! How We Run Our Web ServerInstagram’s web server runs on Django in a multi
Last September, Apple announced the iPhone 7 and 7 Plus, which include cameras that capture a greater range of colors than previous models, and screens that can display that wider color range. We’ve just finished updating Instagram to support wide color, and since we’re one of the first major apps to do so, I wanted to share the process of converting the app to help any others doing the conversion
One of the questions we always get asked at meet-ups and conversations with other engineers is, “what’s your stack?” We thought it would be fun to give a sense of all the systems that power Instagram, at a high-level; you can look forward to more in-depth descriptions of some of these systems in the future. This is how our system has evolved in the just-over-1-year that we’ve been live, and while
With more than 25 photos and 90 likes every second, we store a lot of data here at Instagram. To make sure all of our important data fits into memory and is available quickly for our users, we’ve begun to shard our data — in other words, place the data in many smaller buckets, each holding a part of the data. Our application servers run Django with PostgreSQL as our back-end database. Our first qu
Today, we are excited to announce that we’re open sourcing one of Instagram’s core frameworks: IGListKit. This framework powers how we take data from the server and turn it into fast and flexible lists. To do this, we combined a familiar data-driven UICollectionView architecture with a state-of-the-art diffing algorithm. With this setup, we created a tool that lets engineers with varying levels of
Instagram currently features the world’s largest deployment of the Django web framework, which is written entirely in Python. We initially chose to use Python because of its reputation for simplicity and practicality, which aligns well with our philosophy of “do the simple thing first.” But simplicity can come with a tradeoff: efficiency. Instagram has doubled in size over the last two years and r
The Instagram Engineering Blog has a new locationIn order to streamline our internal blog operations, all future Instagram Engineering content will be posted on the Engineering at Meta blog located here.
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