How Uber Uses MySQL

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.

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.

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 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.

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.

The article discusses Uber's upgrade of its MySQL fleet from version 5. 7 to 8. 0, detailing the motivations, challenges, and solutions implemented during the process.

The article discusses Uber's implementation of differential backups for MyRocks-based distributed databases, addressing the challenges and solutions related to backup efficiency and cost.

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 Uber's overhaul of flaky tests through the introduction of Testopedia, a centralized system designed to enhance visibility and control over test reliability.

The article discusses how Uber's LedgerStore manages trillions of indexes to support its vast transactional data, emphasizing the architecture and indexing strategies that ensure data integrity and...

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

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

This article discusses Uber's experience with garbage collection (GC) tuning to enhance the reliability of Presto, an open-source distributed SQL query engine.

The article discusses Uber's experience in adopting SPIFFE/SPIRE at scale, detailing the challenges and solutions encountered in implementing a Zero Trust security model across a complex microservi...

This article discusses Uber's experience migrating a large-scale invoice generation service from a legacy system to a new service called Invoicer.

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.

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

The article discusses the Unified Action Platform (uAct) developed by Uber, aimed at consolidating various internal communication systems into a single interface for managing requests and notificat...

The article discusses how Uber optimizes the timing of push notifications using machine learning and linear programming.

This article discusses Uber's migration from MySQL to MyRocks, a storage engine that integrates with RocksDB, to address disk space bottlenecks and improve operational efficiency.

The article discusses Uber's implementation of an automated vertical CPU scaling system that optimizes resource allocation for storage workloads, leading to significant cost savings and improved re...

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 discusses strategies to avoid CPU throttling in a containerized environment, particularly at Uber, where stateful workloads run on a large fleet of hosts.

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 initiatives to enhance the efficiency of its Big Data platform, focusing on cost reduction through optimizations in file formats, HDFS erasure coding, YARN scheduling i...

The article discusses how Uber maintains operational excellence in data quality through a consolidated data quality platform (UDQ).

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

The article discusses Uber's 'Orders Near You' feature, which utilizes real-time geospatial data analytics to enhance user experience in the Uber Eats app.

The article discusses Uber's Customer Support Automation Platform, focusing on the development and implementation of the Policy Engine (PE) to enhance customer service efficiency.