When something goes wrong with a piece of code, engineers want to know all the relevant details of the error immediately so they can get right to work remedying the malfunction.
However, as technology has advanced, measuring system metrics and …
When something goes wrong with a piece of code, engineers want to know all the relevant details of the error immediately so they can get right to work remedying the malfunction.
However, as technology has advanced, measuring system metrics and …
In Uber’s New York engineering office, our Observability team maintains a robust, scalable metrics and alerting pipeline responsible for detecting, mitigating, and notifying engineers of issues with their services as soon as they occur. Monitoring the health of our thousands …
When Celina Ward joined Uber in March 2018 to work on M3, an open source metrics platform created by Uber’s Observability team, she had no idea that she’d be co-headlining KubeCon just eight months later to talk about her …
To facilitate the growth of Uber’s global operations, we need to be able to quickly store and access billions of metrics on our back-end systems at any given time. As part of our robust and scalable metrics infrastructure, we built …
As Uber’s architecture has grown to encompass thousands of interdependent microservices, we need to test our mission-critical components at max load in order to preserve reliability. Accurate load testing allows us to validate if a set of services are working …
Capacity is a key component of reliability. Uber’s services require enough resources in order to handle daily peak traffic and to support our different kinds of business units. These services are deployed across different cloud platforms and data centers …
The Fulfillment Platform is a foundational Uber domain that enables the rapid scaling of new verticals. The platform handles billions of database transactions each day, ranging from user actions (e.g., a driver starting a trip) and system actions …
Uber’s mission is to help our consumers effortlessly go anywhere and get anything in thousands of cities worldwide. At its core, we capture a consumer’s intent and fulfill it by matching it with the right …
By its nature, Uber’s business is highly real-time and contingent upon geospatial data. PBs of data are continuously being collected from our drivers, riders, restaurants, and eaters. Real-time analytics over this geospatial data could provide powerful insights.
In this …
Uber relies on a containerized microservice architecture. Our need for computational resources has grown significantly over the years, as a consequence of business’ growth. It is an important goal now to increase the efficiency of our computing resources. Broadly …
Orbit is a general interface for Bayesian time series modeling. The goal of Orbit development team is to create a tool that is easy to use, flexible, interitible, and high performing (fast computation). Under the hood, Orbit uses the probabilistic …
At Uber, we provide a centralized, reliable, and interactive logging platform that empowers engineers to work quickly and confidently at scale. The logs are tagged with a rich set of contextual key value pairs, with which engineers can slice and …
With tech offices around the world, Uber engineers are responsible for building new features and systems that improve rideshare, new mobility, food delivery, and other services enabled by our platform. Our Uber Engineering Blog highlights some of these efforts, giving …
Uber held its first open source summit on November 15, 2018 in San Francisco. Following the success of this event, we held a second edition of the summit in Sofia, Bulgaria in April 2019. Sofia, home to one of …
Open source software plays a big part at Uber and other San Francisco Bay Area tech companies, but its impact can be felt globally. Engineers all over the world launch new open source projects that find widespread adoption among leading …
Reliability engineering teams at Uber build the tools, libraries, and infrastructure that enable engineers to operate our thousands of microservices reliably at scale. At its essence, reliability engineering boils down to actively preventing outages that affect the mean time between …
A Docker registry’s primary purpose is to store and distribute Docker images. This may seem like a relatively trivial task, but with a large-scale compute cluster like Uber’s, it can easily turn into a scaling bottleneck. In computing environments with …
At Uber’s scale, thousands of microservices serve millions of rides and deliveries a day, generating more than a hundred petabytes of raw data. Internally, engineering and data teams across the company leverage this data to improve the Uber experience. …
From engineers and data scientists to product managers and designers, Uber’s tech team in NYC hosts our Observability, Uber Eats, Uber for Business, and Payments Engineering teams.
Our Observability team manages the reliability and stability of our microservice …
The diversity of Uber’s open source offerings speaks to the complexity of our technology stack and the business problems we use these projects to solve. Open source also gives our engineers, data scientists, and researchers the opportunity to further build …