Flink 的过去 offline Real-time Batch Processing Continuous Processing & Streaming Analytics Event-driven Applications ✔ 现在 Flink 1.9 的架构变化 Runtime Distributed Streaming Dataflow Query Processor Flink 的现在 offline Real-time Batch Processing Continuous Processing & Streaming Analytics Event-driven Applications ✔ ✔ 未来 Micro Services O_0 O_1 I_0 I_1 I_2 P_0 P_1 P_2 S_0 S_1 Order Flink 的未来 offline Real-time Batch Processing Continuous Processing & Streaming Analytics Event-driven Applications ✔ ✔ ✔ 扫码加入社群 与志同道合的码友一起 Code Up 阿里云开发者社区 Apache Flink China 2群 粘贴二维码 谢谢！

KEDA proposal Context KEDA allows for fine-grained autoscaling (including to/from zero) for event-driven Kubernetes workloads. KEDA serves as a Kubernetes Metrics Server and allows users to define autoscaling RocketMQ now. So we need to create PR in KEDA repo for new support for RocketMQ - KEDA has event-driven scaling which means it scales based on events instead of RAM or CPU usage, also can be combined

@xurime Blog: https://xuri.me Agenda Serialize and Deserialize 01 • Document Object Model • Event-driven (Simple API for XML) • Serialize and Deserialize Control Handle Complex XML 02 • Partial Load int } encoding/xml:xml.go StartElement EndElement CharData Comment ProcInst Directive Event-driven (Simple API for XML) decoder := xml.NewDecoder(strings.NewReader(data)) for { token, _ := decoder

#mobiletea Service Worker API @giorgionatili // #mobiletea In a Nutshell • Service workers are event-driven workers that act as proxy servers that sit between web applications, the browser, and the network

“frontend” App “backend” OpenCensus Distributed Calculator D E M O Functions with Dapr Event-driven Stateless Easy replication and sharing Input/Triggers App Output/Bindings Functions with Dapr

containers Long-running Bring existing code Fully-managed orchestration AWS Fargate Serverless event-driven code execution Short-lived All language runtimes Data source integrations AWS Lambda Serverless

Concurrent Architecture Active Object Monitor Object ReactorReactor The Reactor pattern is an event-driven framework to demultiplex and dispatch service requests concurrently onto various service providers

open source project which provides a set of components (Serving and Eventing) that introduce event-driven and serverless capabilities for Kubernetes clusters for deploying, running, and managing serverless

and incrementally adoptable equivalents that can run anywhere Introducing Dapr A portable, event-driven, serverless runtime for building distributed applications across cloud and edge Runs on multiple

Principles and philosophy ● A thin wrapper to rcl -- same mindset, fast & easier to adapt change ● Event-driven, non-blocking (promise/event) -- advantage of async IO, very simple & efficient ● Able to use