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Optimizing Observability with Jaeger, M3, and XYS at Uber
Uber’s observability engineers present their work on distributed tracing (Jaeger), sampling (XYS), and metrics processing (M3).
Optimizing M3: How Uber Halved Our Metrics Ingestion Latency by (Briefly) Forking the Go...
Noticing increased latency in our metrics platform, Uber engineers track down a bug related to stack growth in a goroutine, resulting in a fix elevated to the Go open source GitHub repository.
Uber Open Source: Catching Up with Celina Ward, M3 Observability Engineer
Celina Ward discusses her journey to engineering, what it was like to present at Kubecon 2018, and what’s next for M3, Uber's open source metrics platform.
M3: Uber’s Open Source, Large-scale Metrics Platform for Prometheus
M3, Uber's open source metrics platform for Prometheus, facilitates scalable and configurable multi-tenant storage for large-scale metrics.
Year in Review: 2019 Highlights from the Uber Engineering Blog
To cap off 2019, the Uber Engineering Blog editors present a selection of our most popular articles covering a range of technical topics, from AI to mobile development.
Enabling Collaboration through Open Source: Highlights from Uber Open Summit Sofia 2019
At the Uber Open Summit Sofia 2019, we showcased how open source technologies are driving the future of artificial intelligence, site reliability, and other domains.
Bridging the Gap from Sofia to San Francisco: A Conversation with Engineering Manager Marin...
Uber Engineering Manager Marin Dimitrov shares his best practices for motivating an engineering team, keeping connected when your headquarters office is over 6,000 miles and 10 hours away, and leveraging open source software.
Announcing the Uber Open Summit Sofia 2019
The next Uber Open Summit, where we present our latest and most impactful open source projects, will be in Sofia, Bulgaria on April 20, 2019.
Using Machine Learning to Ensure the Capacity Safety of Individual Microservices
Uber leveraged machine learning to design our capacity safety forecasting tooling with a special emphasis on calculating a quality of reliability score.
Introducing Kraken, an Open Source Peer-to-Peer Docker Registry
Developed by Uber, Kraken is an open source peer-to-peer Docker registry capable of distributing terabytes of data in seconds.
Managing Uber’s Data Workflows at Scale
In this article, we discuss Uber's journey toward a unified, multi-tenant, and scalable data workflow management system.
Building Locally, Scaling Globally: Meet the Tech Team at Uber New York City
Ever wondered what it’s like to work in tech at Uber New York City? Just blocks from Times Square and Bryant Park, Uber’s new office in midtown Manhattan is home to more than a dozen teams, hundreds of employees (and growing), and a wide variety of engineering roles.
Year in Review: 2018 Highlights from Uber Open Source
Brian Hsieh, Uber's Open Source program lead, reflects on open source accomplishments, project launches, and collaborations in 2018.
The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series...
Part of Uber's open source M3 metrics system, our query engine can support real-time, large-scale computation and multiple query languages.
Observability at Scale: Building Uber’s Alerting Ecosystem
Uber’s Observability team built a robust, scalable metrics and alerting pipeline to detect, mitigate, and notify engineers of issues as they occur.
Peloton: Uber’s Unified Resource Scheduler for Diverse Cluster Workloads
Uber developed Peloton to help us balance resource use, elastically share resources, and plan for future capacity needs.
Preview 7 Open Source Projects from the Uber Open Summit
Uber open source projects leads give updates on seven of our projects, all of which will be showcased at the upcoming Uber Open Summit 2018.
Announcing Uber Open Summit 2018: Collaboration at Scale
Keynote speakers include Jim Zemlin, executive director of the Linux Foundation, and Zoubin Ghahramani, chief scientist at Uber AI Labs.
Forecasting at Uber: An Introduction
In this article, we provide a general overview of how our teams leverage forecasting to build better products and maintain the health of the Uber marketplace.