How Uber handles millions of ride/food requests efficiently
https://megtechcorner.medium.com/how-uber-handles-millions-of-ride-food-requests-efficiently-part-1-2aa8db436204
https://medium.com/nerd-for-tech/how-uber-handles-millions-of-ride-food-requests-efficiently-part-2-270f84d2c3c0
Uber’s Fulfillment Platform: Ground-up Re-architecture to Accelerate Uber’s Go/Get Strategy
https://eng.uber.com/fulfillment-platform-rearchitecture/
Building Uber’s Fulfillment Platform for Planet-Scale using Google Cloud Spanner
https://eng.uber.com/building-ubers-fulfillment-platform/
Conducting Better Business with Uber’s Open Source Orchestration Tool, Cadence
https://eng.uber.com/open-source-orchestration-tool-cadence-overview/
Cadence Multi-Tenant Task Processing
https://eng.uber.com/open-source-orchestration-tool-cadence-overview/
Scaling of Uber’s API gateway
https://eng.uber.com/scaling-api-gateway/
The Architecture of Uber’s API gateway
https://eng.uber.com/architecture-api-gateway/
Designing Edge Gateway, Uber’s API Lifecycle Management Platform
https://eng.uber.com/gatewayuberapi/
Real-Time Exactly-Once Ad Event Processing with Apache Flink, Kafka, and Pinot
https://eng.uber.com/real-time-exactly-once-ad-event-processing/
Building Reliable Reprocessing and Dead Letter Queues with Apache Kafka
https://eng.uber.com/reliable-reprocessing/
Introducing Domain-Oriented Microservice Architecture
https://eng.uber.com/microservice-architecture/
Why We Leverage Multi-tenancy in Uber’s Microservice Architecture
Although this is a simplified view, it helps explain how multi-tenancy can help solve integration testing. There are two basic requirements that emerge from testing in production, which also form the basis of multi-tenant architecture:
- Traffic Routing: Being able to route traffic based on the kind of traffic flowing through the stack.
- Isolation: Being able to reliably isolate resources between testing and production thereby causing no side-effects in business-critical microservices.
The isolation requirement here is particularly broad since we want all the possible data-at-rest to be isolated, including configuration, logs, metrics, storage (private or public), and message queues. This isolation requirement is not only for the service that is under test, but for the entire stack, too.
Multi-tenancy paves the way for other use cases beyond integration testing, such as staged deployments and replaying traffic in the stack.
https://eng.uber.com/multitenancy-microservice-architecture/
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严选锁定库存的设计及发展
Qunar 酒店基础数据重构DDD落地实践
微盟SAAS新零售电商业务系统的架构演进实践
软件系统架构应该如何演进？
https://www.zhihu.com/question/52942186/answer/2790772833
B站评论系统架构设计
全链路压测：影子库与影子表之争
https://www.bilibili.com/read/cv17581400/
全链路灰度在数据库上我们是怎么做的？
https://developer.aliyun.com/article/985979?utm_content=m_1000349749