How Uber Uses Oracle

This article details Uber's multi-year evolution from static, quota-based rate limiting to an intelligent, priority-aware load management system for their distributed databases (Docstore and Schema...

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

This article discusses Uber's implementation of Apache Pinot to manage and analyze its extensive inventory and catalog data efficiently.

This article discusses how Uber improved MySQL cluster uptime by adopting MySQL Group Replication (MGR) at scale.

This article discusses the improvements made to MySQL cluster uptime at Uber through the implementation of MySQL Group Replication (MGR).

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...

Uber's migration from Spark 2. 4 to Spark 3. 3 involved upgrading over 2 million Spark applications, utilizing innovative automation tools like Iron Dome.

The article discusses the open-source release of Starlark Worker, a tool that integrates Cadence workflow orchestration with the Starlark scripting language.

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

This article discusses how Uber's CacheFront serves over 150 million reads per second while ensuring stronger consistency guarantees.

The article discusses Uber's implementation of encryption at rest and disk isolation at scale using their Stateful Platform, Odin.

The article discusses Finch, Uber's conversational AI data agent designed to streamline financial data retrieval within the Slack environment.

This article details Uber's migration from Apache Hive to Apache Spark SQL for ETL workloads, highlighting the motivations behind the transition, the architecture involved, and the challenges faced...

The article discusses Uber's implementation of a configuration-driven archival and retrieval framework designed to manage vast amounts of regulatory data efficiently.

The article discusses Uber's robust database backup recovery system, highlighting its importance for business continuity and disaster recovery.

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 FixrLeak, a generative AI-based framework developed by Uber to automate the detection and repair of resource leaks in Java applications.

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

The article discusses Profile-Guided Optimization (PGO) in Go programming, detailing its implementation at Uber to enhance performance through runtime profiling data.

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 the MySQL fleet at Uber, which consists of over 2,300 independent clusters that support critical operations for the platform.

The article discusses how Uber leverages Neutrino, an internal fork of Presto, to efficiently serve millions of queries to Apache Pinot, a real-time OLAP database.

The article discusses Uber's implementation of Presto Express, an enhancement to the Presto SQL query engine aimed at reducing the end-to-end Service Level Agreement (SLA) for short-running queries.

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

The article discusses how Uber utilizes Apache Pinot for low-latency offline table analytics, highlighting its capabilities in handling various use cases, including real-time and offline data inges...

The article discusses the Sparkle framework developed by Uber to standardize modular ETL processes, enhancing developer productivity and data quality.

Odin is Uber's stateful platform designed to manage various technologies for data storage efficiently.

This article discusses how Uber has implemented single-zone failure tolerance (SZFT) for its Apache Cassandra® database, ensuring high availability even in the event of a zone failure.

The article discusses how Uber serves over 40 million reads per second from its online storage using an integrated caching solution called CacheFront.

The article discusses Uber's transition to a portable microservices architecture optimized for cloud deployment.

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

Cadence 1. 0 is a powerful open-source workflow orchestration platform designed for building and managing stateful services at scale.

This article discusses Uber's journey in containerizing Hadoop NameNodes within their infrastructure, detailing the motivations, challenges, and architectural strategies employed during the migrati...

Uber's article discusses the implementation of a highly scalable and distributed Remote Shuffle Service (RSS) designed to enhance the efficiency of data processing in Apache Spark.

The article discusses how Uber integrates Presto® and Apache Kafka® to enhance its big data analytics capabilities.

The article features an interview with Shobhana Ahluwalia, Uber's Head of Information Technology, discussing her journey in tech, the challenges of scaling IT infrastructure at Uber, and her insigh...