How Uber Uses Google Cloud

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...

The article discusses Uber's collaboration with Oracle Cloud Infrastructure (OCI) and Ampere Computing to optimize the OCI AmpereOne M A4 Compute instances.

The article discusses Uber's implementation of I/O observability for its massive petabyte-scale data lake, focusing on the challenges and solutions in monitoring data access patterns across its hyb...

The article discusses the implementation of a Policy Simulator at Uber to enhance the safety and determinism of Identity and Access Management (IAM) policy changes.

This article discusses the architecture and implementation of Uber's HiveSync, a critical service for data replication across its massive data lake.

The article discusses the evolution of Uber's Search Platform, highlighting its transition from Elasticsearch to an in-house solution called Sia, and ultimately to the adoption of OpenSearch.

This article discusses the development of Uber's Multi-Cloud Secrets Management Platform, designed to enhance security across its extensive microservices architecture.

The article discusses Uber's migration of large-scale interactive compute workloads from Peloton to Kubernetes, focusing on minimizing disruption while enhancing resource management and cloud readi...

The article discusses Uber's migration from Apache Mesos to Kubernetes, detailing the motivations, challenges, and solutions encountered during the transition.

The article discusses Uber's transition to a multi-architecture environment by adopting Arm-based hosts at scale.

Uber's article discusses the strategic migration from on-premise data centers to cloud infrastructure while integrating Arm-based computers to enhance cost efficiency and hardware flexibility.

The article discusses how Uber optimizes the training of Large Language Models (LLMs) using both open-source and in-house models.

The article discusses Uber's migration of its batch data platform to the cloud, focusing on the implementation of DataMesh principles.

This article discusses Uber's migration of its Apache Hadoop-based data lake to Google Cloud Storage (GCS) and the security measures implemented during this transition.

Uber is modernizing its batch data infrastructure by migrating to Google Cloud Platform (GCP) to enhance data analytics and machine learning capabilities.

DataCentral is Uber's proprietary platform designed for Big Data observability, chargeback, and governance.

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.

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.

The article discusses Uber's implementation of Attribute-Based Access Control (ABAC) to manage access across its microservices architecture.

This article discusses how Uber engineers successfully halved the CI build time for their Go Monorepo by implementing various optimizations.

This article discusses the development of Uber's Fulfillment Platform using Google Cloud Spanner, focusing on its architecture, scalability, and operational efficiency.

The article discusses Uber's comprehensive re-architecture of its Fulfillment Platform, aimed at enhancing its Go/Get strategy.

This article discusses how Uber implemented the QUIC protocol to enhance the performance of its mobile applications, particularly in low-latency and unreliable network conditions.

The article discusses how Uber manages its data workflows at scale, detailing the evolution from multiple overlapping data workflow systems to a centralized management system called Piper.

The article discusses the challenges of using Android Bundles for data transfer and how Uber Engineering developed the AutoValue: Bundle Extension to streamline this process.