What’s new for Java in the Cloud?
summary
Claims a faster Java release cadence and multiple free OpenJDK distributions, shows concrete tooling and measurements: a Spring Batch app runs in Docker with open j9 vs hotspot base images, observed via Docker + docker stats; memory drops from about 800MB vs 150MB for the same workload. Explains Adopt OpenJDK builds, explains support/paid update windows, and demos that swapping JVMs (and using AOT or class sharing) reduces startup time and footprint and succeeds in the demo.
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chapters (38)
- 0:00Introduction
- 1:04Who uses Java
- 2:27The future of Java
- 5:31Release Process
- 6:45New Versions
- 9:32Continuous Delivery
- 11:09Java still free
- 12:01Definition of free
- 13:02Java distributions
- 14:05Is Java free
- 14:51Are Java security updates free
- 15:40What support options do we have
- 18:37Cloudbased scalability
- 19:15Parallel computing
- 19:47Raspberry Pi
- 20:19Cloud scaling
- 21:09How do we adapt
- 21:42New Economics
- 22:25Workload
- 23:19Sprint vs Marathon
- 24:31Scalability vs Demand
- 25:25How to respond to Demand
- 26:15Scaling
- 28:09Agility
- 28:39Scale
- 29:28Hotspot
- 45:16Open JDK
- 46:30Big Data Analytics
- 48:25Machine Learning
- 48:57GPUs
- 49:27How GPUs work
- 49:57IBM initiative
- 51:07Software always changes
- 52:34What does a GPU look like
- 53:02GPU farms
- 53:50Project Panama
- 54:16IBM Quantum Computer
- 57:38New JVM implementations
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