How Quarkus makes your apps cheaper, greener, and happier

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how quarkus makes development faster greener happier Holly Cummins Senior Principal Software Engineer, Quarkus London Java Community November 11, 2025 https://bsky.app/profile/hollycummins.com

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how quarkus makes development faster greener happier cheaper Holly Cummins Senior Principal Software Engineer, Quarkus London Java Community November 11, 2025 https://bsky.app/profile/hollycummins.com

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@holly_cummins #Quarkus #IBM #RedHat

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@holly_cummins #Quarkus #IBM #RedHat why are you smiling?

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@holly_cummins #Quarkus #IBM #RedHat why are you smiling? work is not a place to be happy!

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#RedHat @holly_cummins ΑΡΙΣΤΟΤΈΛΗΣ

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#RedHat @holly_cummins «τελειοῖ δὲ τὴν ἐνέργειαν ἡἡδονή» ΑΡΙΣΤΟΤΈΛΗΣ

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#RedHat @holly_cummins «Η ευχαρίστηση στην δουλειά βάζει την τελειότητα στην εργασία» ΑΡΙΣΤΟΤΈΛΗΣ

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#RedHat @holly_cummins “Pleasure in the job puts perfection in the work.” Aristotle

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#RedHat @holly_cummins joy has business value.

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#RedHat @holly_cummins job satisfaction is the no. 1 predictor of organizational performance

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#RedHat @holly_cummins not all software creates joy

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@holly_cummins #RedHat most java web frameworks are verbose there is a lot of typing

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@holly_cummins #RedHat most java web frameworks are resource-hungry they hog cpu and ram

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@holly_cummins #Quarkus #IBM #RedHat

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@holly_cummins #Quarkus #IBM #RedHat “I can’t bring up the microservices in my Java dev stack

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@holly_cummins #Quarkus #IBM #RedHat “I can’t bring up the microservices in my Java dev stack … on my brand new Apple laptop with a M1 chip and 64GB of RAM.” - fintech CTO

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@holly_cummins #Quarkus #IBM #RedHat in production, it’s worse

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@holly_cummins #Quarkus #IBM #RedHat in production, it’s worse

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@holly_cummins #Quarkus #IBM #RedHat in production, it’s worse example microservices maths:

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@holly_cummins #Quarkus #IBM #RedHat in production, it’s worse example microservices maths: airline maintenance scheduling system

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@holly_cummins #Quarkus #IBM #RedHat in production, it’s worse example microservices maths: airline maintenance scheduling system single service: ½ core + 1 GB RAM

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@holly_cummins #Quarkus #IBM #RedHat in production, it’s worse example microservices maths: airline maintenance scheduling system single service: ½ core + 1 GB RAM HA → 3x instances

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@holly_cummins #Quarkus #IBM #RedHat in production, it’s worse example microservices maths: airline maintenance scheduling system single service: ½ core + 1 GB RAM HA → 3x instances ~100 microservices

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@holly_cummins #Quarkus #IBM #RedHat all this resource usage is expensive

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@holly_cummins #Quarkus #IBM #RedHat slow development is expensive

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@holly_cummins #Quarkus #IBM #RedHat why is this happening? mismatch between what we need and what the platform is optimised for

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@holly_cummins #Quarkus #IBM #RedHat java was not designed for the cloud

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@holly_cummins #RedHat old Java frameworks were optimised for …

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@holly_cummins #RedHat long-lived processes old Java frameworks were optimised for …

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@holly_cummins #RedHat long-lived processes annual (!) deployments old Java frameworks were optimised for …

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@holly_cummins #RedHat long-lived processes annual (!) deployments late-binding old Java frameworks were optimised for …

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@holly_cummins #RedHat long-lived processes annual (!) deployments late-binding re-configurable without restart old Java frameworks were optimised for …

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@holly_cummins #Quarkus #IBM #RedHat Container platform machine go go go go go go go go go go go go go go

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@holly_cummins #Quarkus #IBM #RedHat Container platform machine node.js node.js node.js node.js node.js node.js node.js machine go go go go go go go go go go go go go go

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@holly_cummins #Quarkus #IBM #RedHat Container platform machine HotSpot Heap HotSpot Heap HotSpot Heap HotSpot Heap machine node.js node.js node.js node.js node.js node.js node.js machine go go go go go go go go go go go go go go

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can we do better than that?

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enter … quarkus a Java framework that gets you going faster, faster.

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@holly_cummins #Quarkus #IBM #RedHat traditional cloud-native java stack traditional cloud-native java stack traditional cloud-native java stack traditional cloud-native java stack node.js node.js node.js node.js node.js node.js node.js go go machine go go go go go go go go go go go go go go go go go go go quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus spoiler: we made stuff better :) container orchestration machine machine machine https:/ /developers.redhat.com/blog/2017/03/14/java-inside-docker/

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@holly_cummins #Quarkus #IBM #RedHat machine quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus container orchestration machine traditional cloud-native java stack traditional cloud-native java stack traditional cloud-native java stack traditional cloud-native java stack … a lot better quarkus native

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quarkus applications start fast quarkus + graalvm 0.014 Seconds rest application quarkus + open jdk 0.75 Seconds traditional cloud-native stack 4.3 Seconds https://quarkus.io/blog/runtime-performance/

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@holly_cummins to the code! demo!

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@holly_cummins #Quarkus #IBM #RedHat mvn quarkus:build -Pnative target/code-with-quarkus-1.0.0-SNAPSHOT-runner

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thanks to markus eisele for the graphics code https://github.com/holly-cummins/meme-generator

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ok but does startup time matter?

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ok but does startup time matter? fast boot time means auto-scaling works better more resilience to load spikes

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quarkus + GraalVM 13 MB quarkus + OpenJDK 74 MB traditional cloud-native Stack 140 MB rest application https://quarkus.io/blog/runtime-performance/ quarkus improves memory utilization

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#Quarkus @holly_cummins

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#Quarkus @holly_cummins hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus?

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#Quarkus @holly_cummins hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus? uhh … are you supposed to shut down applications after using them?

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ok but does memory footprint matter?

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ok but does memory footprint matter? in the cloud, memory footprint is money

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@holly_cummins #Quarkus #IBM #RedHat remember the airline scheduling application?

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@holly_cummins #Quarkus #IBM #RedHat remember the airline scheduling application? “[With Quarkus], we can run 3 times denser deployments without sacrificing availability and response times of services. ” – Thorsten Pohl

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let’s talk about throughput. https://www.redhat.com/en/resources/mi-quarkus-lab-validation-idc-analyst-paper 48 concurrent connections Traditional cloud native stack 3555 req/s

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let’s talk about throughput. quarkus native 3212 req/s https://www.redhat.com/en/resources/mi-quarkus-lab-validation-idc-analyst-paper 48 concurrent connections Traditional cloud native stack 3555 req/s

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let’s talk about throughput. quarkus native 3212 req/s https://www.redhat.com/en/resources/mi-quarkus-lab-validation-idc-analyst-paper a trade-off of throughput against footprint 48 concurrent connections Traditional cloud native stack 3555 req/s

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@holly_cummins native compilation trade-offs throughput startup time + footprint

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@holly_cummins native compilation trade-offs throughput startup time + footprint

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@holly_cummins native compilation trade-offs throughput startup time + footprint this is a classic tradeoff

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but … traditional cloud native stack 3555 req/s quarkus native 3212 req/s https://www.redhat.com/en/resources/mi-quarkus-lab-validation-idc-analyst-paper a trade-off of throughput against footprint 48 concurrent connections

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but … traditional cloud native stack 3555 req/s quarkus on jvm 6389 req/s quarkus native 3212 req/s https://www.redhat.com/en/resources/mi-quarkus-lab-validation-idc-analyst-paper a trade-off of throughput against footprint 48 concurrent connections

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but … traditional cloud native stack 3555 req/s quarkus on jvm 6389 req/s quarkus native 3212 req/s https://www.redhat.com/en/resources/mi-quarkus-lab-validation-idc-analyst-paper no trade-off, just better :) a trade-off of throughput against footprint 48 concurrent connections

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@holly_cummins we beat the trade-off. throughput startup time + footprint

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@holly_cummins we beat the trade-off. throughput startup time + footprint

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@holly_cummins we beat the trade-off. throughput startup time + footprint it’s a double-win.

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#Quarkus @holly_cummins users care (a lot) about response time

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better startup better footprint better throughput wait, isn’t that something for nothing?

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@holly_cummins #Quarkus #IBM #RedHat the two ways of improving performance •trade off one thing against another •eliminate waste

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@holly_cummins #RedHat where the win comes from

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@holly_cummins #RedHat application frameworks were optimised for dynamism

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@holly_cummins #RedHat application frameworks optimised for dynamism dynamism has a cost

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@holly_cummins #RedHat paying a dynamism tax … even though the app is not dynamic

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