KubeCon + CloudNativeCon + Open Source Summit + AI_dev China 2024

Kubernetes makes container orchestration and management simple and easy. However, with the surge of applications and middleware onboard Kubernetes, it is difficult to analyze and identify the relationship and dependencies between huge amounts of services and middleware. The most general way requires the business side to make code changes to expose more information, which is impossible to cover for all applications. In this session, we will share: * How does Shopee leverage eBPF to build a universal map for a million containers in production environments? * How do we implement distributed tracing for arbitrary third-party middleware with different protocols and usage patterns? * How do we optimize eBPF code and Linux Kernel to minimize the impacts for injected containers? * How did we integrate with BigData and AI Stack to fully utilize the data for abnormal detection and incident troubleshooting?

Kubernetes使容器编排和管理变得简单易行。然而，随着应用程序和中间件在Kubernetes上的激增，分析和识别大量服务和中间件之间的关系和依赖关系变得困难。最常见的方法需要业务方进行代码更改以公开更多信息，这对所有应用程序来说是不可能覆盖的。 在本场演讲中，我们将分享： *Shopee如何利用eBPF在生产环境中为百万个容器构建通用映射？ *我们如何为具有不同协议和使用模式的任意第三方中间件实现分布式跟踪？ *我们如何优化eBPF代码和Linux内核以最小化对注入容器的影响？ *我们如何与大数据和人工智能堆栈集成，充分利用数据进行异常检测和故障排除？