Cloud-Native Streaming and Event-Driven Microservices
Speaker: Marius Bogoevici
See list of all blog posts from conference
Streaming
- Streaming is processing large quantitiesof data as fast as possible -near real time.
- Collection of eents – in order
- Good for real time ELT, predictive maintenance, fraud detection, QoS, etc
- high throughput/low latency
Microservices
- Cohesive, organizational allignment (Conway’s law)/li>
- Development agility – optimized for replacement, enable continuous delivery
- Failure isolation
- Granlar resource tuning – can scale specificparts of pipeline
Event driven microservices
- Communicate thrugh message broker vs http
- Decoupled
- Publish/subscribe makes it easy to add new elements
Think about opertional complexity – need to be able to provision/montitor. Want this part to be boring. It’s not the business value. Hence cloud-native; the platform should take care of these concerns.
Support Spring WebFlow- Cloud Foundry, Apache Mesos, Kubernetes, Apache YARN
Spring XD – first incarnation. In 2015, it turned into Spring Cloud Stream/Task/Data Flow.
Spring Cloud stream
Spring Cloud Data Flow
- Orchestration of services
- Provides Stream DSL
- Describe deployment
- Deploys using SPI (service provider interface)
- Deployment descritpor to specify what want to happen
Interesting. And we got to read more Flux code. Appreciating Victor’s talk from yesterday even more! I would have liked if “opinionated primitives” was described more. While I understand what the concept means, I’m not that clear on how it relates to the framework. I also had to Google the term SPI. This might have been a presentation for which I lacked pre-req knowledge. The session felt longer than the others. Checking the log for this blog post, it was a little longer; but not a ton so. I think just too much sitting for me!