The Value Of Reactive Systems

[@emilbelardo639]

Thank you for sharing this very informative presentation🙂
01:25 - Reactive programming in a nutshell
01:26 -- What is reactive programming?
03:34 -- Reactive programming concepts worth knowing
04:08 -- Functional programming
04:49 -- Asynchronous programming (work stealing) can make debugging difficult
05:33 -- What is non-blocking programming?
06:34 -- Multiple terminal routes: Blocking ( full data or no data ) vs. Non-Blocking ( full data, no data, or partial data )
08:09 -- Overhead on low volume
09:55 - Reality Check Part 1: What are the priorities ( business and otherwise )?
12:47 - Performance Overview
12:48 -- Synchronous Processing: Blocking - Remote Call
14:14 -- Synchronous Processing: Blocking - Slow Client
14:59 -- Asynchronous Processing: Blocking - Remote Call
16:03 -- Asynchronous Processing: Blocking - Slow Client
16:27 -- Non-Blocking and Event Loops
18:22 - Reactive Programming Model
18:24 -- What is backpressure and why is it important?
19:29 - WebMVC ( blocking processing ) vs. WebFlux ( non-blocking processing )
19:55 - Use cases that favor using the reactive programming model and WebFlux
21:42 - Performance
22:36 -- Load Scenario / Description of Test Environment
23:34 -- Scenario 1 - Hello World ( return single string )
23:46 --- Comparison: WebFlux vs. WebMVC
26:02 --- Why is it important to minimize use of old generation heap memory?
28:02 --- Why does WebFlux tend to use less old generation heap memory compared to Web MVC?
30:36 --- Can non-reactive programming and reactive programming coexist on the same server?
31:59 -- Scenario 2 - Hello World with Delay ( slow client simulation )
33:06 --- Comparison: WebMVC 200 vs. WebMVC 200 ( with response delay )
34:28 --- The importance of using tail latency instead of average latency as a benchmark
34:41 --- Comparison: WebMVC 200 ( with response delay ) vs. WebMVC 600 ( with response delay )
35:04 --- Comparison: WebFlux vs. WebFlux ( with response delay )
35:37 -- Scenario 3 - Streaming ( 50 elements )
36:21 --- Comparison: WebFlux vs. WebMVC
36:52 -- Scenario 4 - Streaming with Delay ( slow client simulation )
37:22 --- Comparison: WebFlux vs. WebMVC
37:49 -- Scenario 5 - Remote Call
38:51 --- Comparison: WebFlux vs. WebMVC with RestTemplate
39:37 --- Comparison: WebFlux vs. WebMVC with WebClient
40:43 --- The benefit of replacing RestTemplate with WebClient in a WebMVC application
41:38 -- Scenario 6 - Remote Call with Delay ( slow remote service simulation )
42:12 --- Comparison: WebFlux vs. WebMVC with RestTemplate
42:34 --- Comparison: WebFlux vs. WebMVC with WebClient
44:02 --- Does it still make sense to replace RestTemplate with WebClient in a WebMVC application if it only interacts with one remote service?
45:38 - Reactive Programming Benefit: Built-in Resilience
46:10 -- Prepare for the worst, don't page Ops
46:59 - Tales of Production...
47:21 -- How Netty tries to isolate possible errors like OutOfMemoryError to the offending request
50:26 - Reality Check Part 2: Let's review the priorities again ( business or otherwise )
50:37 -- Reactive allows more productivity in writing state of the art, scalable microservices
51:21 -- Reactive applications are designed to be resilient under stress and lower maintenance
51:52 -- Reactive allows you to run more for less
53:21 - Question & Answer

[@emilbelardo639]

If Gatling was the load testing tool used to measure throughput, does anyone know what tool was used to measure resource usage of the application itself ?
In the presentation, they showed both throughput metrics and resource usage metrics.
As far as I know, Gatling only provides throughput metrics.
So I'm very curious what tool was used for the resource usage metrics.

[@Xposterion]

Thank you for presentation. Slideshare link not valid, could you please re-upload it?

[@ramcorp542]

Thank for the presentation.

[@seonwookim5391]

thank you for the presentation. By the way, can I know what tools you have used to calculate the performance (comparison between WebMVC and Web Flux) ? Looks very useful

[@Azotizca]

Its called gatling

[@rewolfer]

So for scenario 3, the "Response Time" is for receiving the whole stream?
So a p99 of ~5s is for streaming 50 items (of 1k each) => 50k/5s = 10k/s. Comparet with about 5.5k/s on MVC.
I also really like the stddev numbers for the WebFlux results. Much more consistent than MVC.

[@rajivkumar-ub6uj]

You guys are good. Thanks for the awesome presentation

[@itsnaveen007]

very good information