Skip to footer

M3 - search results

Optimizing Observability with Jaeger, M3, and XYS at Uber

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

Optimizing M3: How Uber Halved Our Metrics Ingestion Latency by (Briefly) Forking the Go Compiler

0

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

Uber Open Source: Catching Up with Celina Ward, M3 Observability Engineer

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

M3: Uber’s Open Source, Large-scale Metrics Platform for Prometheus

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

Introducing Ballast: An Adaptive Load Test Framework

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 Recommendation Engine: Throughput and Utilization Based Predictive Scaling

Introduction

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

Building Uber’s Fulfillment Platform for Planet-Scale using Google Cloud Spanner

 

Introduction

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 Fulfillment Platform: Ground-up Re-architecture to Accelerate Uber’s Go/Get Strategy

Introduction to Fulfillment at Uber

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

‘Orders Near You’ and User-Facing Analytics on Real-Time Geospatial Data

Introduction

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

Efficient and Reliable Compute Cluster Management at Scale

Introduction

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

Introducing Orbit, An Open Source Package for Time Series Inference and Forecasting

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

Fast and Reliable Schema-Agnostic Log Analytics Platform

0

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

Year in Review: 2019 Highlights from the Uber Engineering Blog

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

Enabling Collaboration through Open Source: Highlights from Uber Open Summit Sofia 2019

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

Announcing the Uber Open Summit Sofia 2019

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

Using Machine Learning to Ensure the Capacity Safety of Individual Microservices

0

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

Introducing Kraken, an Open Source Peer-to-Peer Docker Registry

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

Managing Uber’s Data Workflows at Scale

0

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.

Building Locally, Scaling Globally: Meet the Tech Team at Uber New York City

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

Year in Review: 2018 Highlights from Uber Open Source

0

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