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# Warm Up Fast, Run Lean: Vertical Scaling for Java on Kubernetes with Azul Prime and Kedify

**[Foojay.io](https://daily.dev/sources/foojayio)** · 12 min read · 0 upvotes · 0 comments

## Summary

Java applications on Kubernetes face a warm-up challenge: JIT compilation requires extra CPU at startup but wastes resources if that allocation persists into steady state. This post explains how to use Azul Prime's JMX metric (TotalOutstandingCompiles) as a readiness signal combined with Kedify's PodResourceProfiles (PRPs) to dynamically allocate elevated CPU during JVM warm-up and automatically shrink it once optimization completes — all without pod restarts. The approach leverages Kubernetes in-place pod resource resize (GA in v1.33), a JMX-based readiness probe that gates traffic until the compilation queue drains, and a declarative PRP that transitions from 10 CPU cores during warm-up to 4 cores at steady state (~60% reclaimed). Azul Zing's 'finishWarmup' JMX method also adjusts internal thread pools to prevent CPU overconsumption after scale-down. The pattern complements horizontal autoscaling: new replicas get a temporary CPU boost, warm up faster, and then run lean.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://foojay.io/today/warm-up-fast-run-lean-vertical-scaling-for-java-on-kubernetes-with-azul-prime-and-kedify>

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---

Tags: [#kubernetes](https://daily.dev/tags/kubernetes), [#java](https://daily.dev/tags/java), [#jvm](https://daily.dev/tags/jvm)

[View this post on daily.dev](https://daily.dev/posts/warm-up-fast-run-lean-vertical-scaling-for-java-on-kubernetes-with-azul-prime-and-kedify-bzofmptgn)

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