How Uber Uses Azure
13 engineering articles about Azure from Uber's engineering team
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This article details how Uber built and scaled Apache Hudi to power one of the world's largest data lakes, managing 19,500 datasets with trillions of records across a multi-hundred-petabyte reposit...
Prashant Wason, Balajee Nagasubramaniam, Surya Prasanna Kumar Yalla, Meenal Binwade, Xinli Shang, Jack Song
19 min read
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This article introduces Kafka Tiered Storage at Uber, detailing its architecture and the motivation behind its implementation.
Satish Duggana, Kamal Chandraprakash, Abhijeet Kumar
9 min read
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The article discusses how Uber utilizes Apache Pinot for real-time analytics of mobile app crashes, enhancing their ability to detect and resolve issues quickly.
Kriti Dangi, Anil Purohit, Parijat Bansal, Rohit Yadav
17 min read
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The article discusses the evolution of Data Lifecycle Management (DLM) at Uber, detailing the journey from initial implementations to the development of a unified system.
Sumanth Srinivasa Krishnaswamy, Matt Mathew, Sonali Goyal
13 min read
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This article discusses the implementation of finer-grained encryption in Apache Parquet™, focusing on how it addresses data access restrictions, retention, and encryption at rest.
Xinli Shang, Mohammad Islam, Pavi Subenderan, Jianchun Xu
19 min read
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The article discusses the integration of Elastic Horovod with Ray, focusing on how this combination enhances distributed deep learning training by enabling autoscaling and fault tolerance.
ApacheApache SparkAutoMLAWSAzureDaskDeep LearningKubernetesMachine LearningModinPandasPyTorchXGBoost
Travis Addair, Xu Ning, Richard Liaw
15 min read
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The article discusses Uber's development of uWorc, a no-code workflow orchestrator designed to simplify the creation of batch and streaming data pipelines.
Horovod v0. 21 introduces significant enhancements aimed at optimizing network utilization for distributed deep learning training.
Kerri Brown
8 min read
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The article discusses the latest updates to Horovod, a distributed deep learning framework, which now includes support for PySpark and Apache MXNet, along with features aimed at enhancing training ...
Carsten Jacobsen
7 min read
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The article introduces Alex Sergeev, the lead of the Horovod project at Uber, detailing the motivations behind open sourcing Horovod, a distributed deep learning framework.
Molly Vorwerck
9 min read
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Horovod, Uber's open-source distributed training framework, has joined the LF Deep Learning Foundation, enhancing its support for open-source innovation in AI and deep learning.
Uber
2 min read
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The article highlights seven open source projects showcased at the Uber Open Summit, emphasizing Uber's contributions to the open source community.
ApacheApache SparkAWSAzureCassandraGraphQLJavaScriptKerasKubernetesMachine LearningPrometheusPyTorchTensorFlow
Wayne Cunningham
7 min read
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The article discusses Uber's transition from IPv4 to IPv6, highlighting the necessity of this upgrade due to the rapid growth of its user base and the exhaustion of IPv4 addresses.
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