Tag: Infra
Code Migration in Production: Rewriting the Sharding Layer of Uber’s Schemaless Datastore
Migrating our Schemaless sharding layer from Python to Go while in production demonstrated that it was possible for us to rewrite the frontend of a massive datastore with zero downtime.
Reliability at Scale: Engineering an Uneventful New Year’s Eve
How does Uber keep New Year's Eve and other high traffic events...well, uneventful? By keeping our networks extensible and our services reliable year-round.
Constructing a Seamless Flow: Meet Uber Engineering’s Developer Experience Team
Get to know Uber's Developer Experience team, a group of writers, educators, and technologists dedicated to setting our engineers up for success.
Pyflame: Uber Engineering’s Ptracing Profiler for Python
Seemingly small inefficiencies are greatly magnified as Uber's business scales. In this article we’ll explore design considerations and unique implementation characteristics of Pyflame, Uber Engineering's high-performance Python profiler implemented in C++.
The Uber Engineering Summer Intern Experience
As this summer comes to a close, profiles from last summer's Uber Engineering intern class and what their Uber experience was like.
uReplicator: Uber Engineering’s Robust Apache Kafka Replicator
Take a look into uReplicator, Uber’s open source solution for replicating Apache Kafka data in a robust and reliable manner.
Why Uber Engineering Switched from Postgres to MySQL
Uber Engineering explains the technical reasoning behind its switch in database technologies, from Postgres to MySQL.
The Uber Engineering Tech Stack, Part I: The Foundation
Uber’s mission is transportation as reliable as running water, everywhere, for everyone. Here's the first of a two-part series on the tech stack that Uber Engineering uses to make this happen.
Engineering Uber Systems to Combat Fraud
Fraud prevention is one of Uber's fastest growing areas of research and development. As our platform has grown, so has the international underworld that tries to undermine it. Here’s how Uber engineers systems to fight fraud in 2016 and beyond.
Uber Engineering’s Micro Deploy: Deploying Daily with Confidence
Uber Engineering's Micro Deploy (μDeploy), our in-house deployment system that builds, upgrades, and rolls back services at Uber.
Meet Uber Engineering Amsterdam
A team profile of the people and technical work of Uber Engineering Amsterdam, and what it’s like to be a part of the team.
Rewriting Uber Engineering: The Opportunities Microservices Provide
To show how a microservice is implemented in Uber Engineering's ecosystem, we look at the development of Tincup, our currency and exchange rate service.
How We Built Uber Engineering’s Highest Query per Second Service Using Go
How the Go programming language helped Uber Engineering build and scale our highest queries per second microservice, for geofence lookups.
How Uber Engineering Evaluated JSON Encoding and Compression Algorithms to Put the Squeeze on...
Imagine you have to store data whose massive influx increases by the hour. Your first priority, after making sure you can easily add storage capacity, is to try and reduce the data’s footprint to save space. But how? This is the story of Uber Engineering’s comprehensive encoding protocol and compression algorithm test and how this discipline saved space in our Schemaless datastores.
How Ringpop from Uber Engineering Helps Distribute Your Application
How to develop with Uber Engineering's Ringpop, an open source library developed to make our applications cooperative and scalable.
Using Triggers On Schemaless, Uber Engineering’s Datastore Using MySQL
The details and examples of Schemaless triggers, a key feature of the datastore that’s kept Uber Engineering scaling since October 2014. This is the third installment of a three-part series on Schemaless; the first part is a design overview and the second part is a discussion of architecture.
The Architecture of Schemaless, Uber Engineering’s Trip Datastore Using MySQL
How Uber’s infrastructure works with Schemaless, the datastore using MySQL that’s kept Uber Engineering scaling since October 2014. This is part two of a three-part series on Schemaless; part one is on designing Schemaless.
Designing Schemaless, Uber Engineering’s Scalable Datastore Using MySQL
The making of Schemaless, Uber Engineering’s custom designed datastore using MySQL, which has allowed us to scale from 2014 to beyond. This is part one of a three-part series on Schemaless.
Service-Oriented Architecture: Scaling the Uber Engineering Codebase As We Grow
Moving away from a monolithic codebase to a service-oriented architecture (SOA) has not been an easy task. Here's a brief glimpse of the scalability problems we've faced and the steps we've taken to solve them.
Learning as a New Grad on the Uber Engineering Money Team
One of our new graduate hires from 2014, Cory, recounts a lesson learned from deploying code with a bug for our payment systems on a Friday.
Project Mezzanine: The Great Migration
What happens when you have to migrate hundreds of millions of rows of data and 100 services over several weeks with dozens of engineers, while simultaneously serving millions of rides? The story of how Uber moved to Mezzanine in 2014.
