A Cloud-Native Dev is Eating my Cheese! (How to get it back?)

Speakers: Eder Ignatowic & Alex Porcelli

For more blog posts, see The Oracle Code One table of contents

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Requirements for Cloud Native

• Microservices scenarios
• Java tools and frameworks not optimized for cold starts and low memory consumptions

Problems now

• We pre-fetch a lot in memory
• New developers perspective
• Java developers need a lot of RAM on laptop

History

• 199x – early adopters – Java cool, big/reliable servers, app servers, app always up, JVM optimized for the long run
• 200x – majority, cloud computing, commodity hardware. expect failure
• 201x – late majority

Cloud generations

• 199x – Virtualization – hypervisor, app servers as best practice (JavaEE). Tomcat/Jetty as outliers
• 200x – Containers – Microservices, Docker, SpringBoot, go/node as outliners
• 201x – Orchestration – Microservices maturity, Kubernetes, Go/node skyrocketing, Operator/Service Mesh as outliner.

Advantages of Java

• Microprofile standard
• Lots of libraries
• Tons of developers
• IDE/Tooling

Quarkus

• Java EE standards + NodeJS Dev experience (no restart)
• Size of a Go binary
• Can use GraalVM

Kogito

• Build automation tool
• Based on Drools
• jBPM

Demo

• Used VS Code
• Showed Kognito business rule – uses custom DSL

My take

It was fine, but not what I expected. My brain was full before I walked in so seeing a demo was hard. I’d seen a Quarkus demo recently. It’s still cool. (I left early and missed the end)