How Uber Uses gRPC

This article introduces uForwarder, Uber's open-source push-based consumer proxy for Apache Kafka's async queuing system.

This article discusses how Uber utilizes a pull-based ingestion model in OpenSearch™ to effectively index streaming data.

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.

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 Uber's strategy for shifting end-to-end (E2E) testing left in their development process to improve efficiency and reduce operational costs.

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.

The article discusses the SLATE tool, which enhances debugging capabilities in microservice architectures by allowing developers to test services in conjunction with production environments.

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.

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

The article discusses D3, an automated system developed by Uber to detect data drifts in datasets, which is crucial for maintaining data quality and ensuring the performance of machine learning mod...

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.

The article discusses Uber's transition from a Server-Sent Events (SSE) architecture to a gRPC-based push platform, detailing the motivations, implementation challenges, and outcomes of this migrat...

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 implementation of a Consumer Proxy to enhance Apache Kafka's asynchronous queuing capabilities.

The article discusses Uber's approach to managing compute clusters efficiently and reliably at scale, emphasizing the importance of CPU utilization and resource scheduling.

The article discusses the architecture of Uber's API gateway, detailing its evolution, components, and functionalities.

Uber's Real-Time Push Platform focuses on enhancing user experiences by transitioning from polling to a gRPC-based bi-directional streaming protocol.

The article discusses the evolution of Uber's API gateway, Edge Gateway, which serves as a self-serve platform for configuring, managing, and monitoring APIs across various business domains.

The article introduces Neuropod, an open-source deep learning inference engine developed by Uber's Advanced Technologies Group (ATG).

The article discusses how Uber integrated GraphQL into its Customer Care Platform to enhance data hydration, streamline developer workflows, and improve error handling.

Uber has announced the open sourcing of Peloton, its unified resource scheduler designed to manage resources across various workloads efficiently.

The article introduces Michelangelo PyML, Uber's platform designed for rapid Python machine learning model development.