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YOW! The Efficiency Paradox & How to Save Yourself and the World Holly Cummins Red Hat

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@holly_cummins #RedHat now senior principal software engineer helping to build Quarkus

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@holly_cummins #RedHat now senior principal software engineer helping to build Quarkus 2007 let’s make garbage collection more efficient!

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@holly_cummins #RedHat now senior principal software engineer helping to build Quarkus 2007 let’s make garbage collection more efficient! 2015 lean and xp makes your team more efficient!

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@holly_cummins #RedHat now senior principal software engineer helping to build Quarkus 2007 let’s make garbage collection more efficient! 2015 lean and xp makes your team more efficient! 2022 quarkus is wonderfully efficient!

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@holly_cummins #RedHat “this provisioning software is broken”

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@holly_cummins #RedHat what we sold “this provisioning software is broken” 10 minute provision-time

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@holly_cummins #RedHat what we sold “this provisioning software is broken” 10 minute provision-time 3 month provision- time what the client thought they’d got

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@holly_cummins #RedHat what we sold “this provisioning software is broken” 10 minute provision-time 3 month provision- time what the client thought they’d got the reason 84-step pre-approval process

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@holly_cummins #RedHat waste

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@holly_cummins #RedHat 1700s machine

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@holly_cummins #RedHat 1700s machine energy

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@holly_cummins #RedHat 1700s machine energy energy

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@holly_cummins #RedHat 1700s machine energy energy useful

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@holly_cummins #RedHat 1700s waste machine energy energy useful

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@holly_cummins #RedHat 1890s processes

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@holly_cummins #RedHat time money 1890s processes

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@holly_cummins #RedHat time money 1890s value processes

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@holly_cummins #RedHat time money 1890s value processes

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@holly_cummins #RedHat time money 1890s value processes waste

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@holly_cummins #RedHat software 1960s

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@holly_cummins #RedHat software time electricity hardware 1960s

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@holly_cummins #RedHat software time electricity hardware answers 1960s

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@holly_cummins #RedHat software time electricity hardware answers 1960s waste

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@holly_cummins #RedHat waste is killing the planet

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@holly_cummins #RedHat e-waste is killing the planet

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@holly_cummins #RedHat energy waste is killing the planet

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@holly_cummins #RedHat slow code is killing the planet

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@holly_cummins #RedHat https://blog.linkedin.com/2017/august/3/making-linkedin-more-accessible-via-linkedin-lite Nashik

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@holly_cummins #RedHat https://blog.linkedin.com/2017/august/3/making-linkedin-more-accessible-via-linkedin-lite “my heart sank … our new feature failed to load because of poor internet connectivity” Nashik

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@holly_cummins #RedHat https://blog.linkedin.com/2017/august/3/making-linkedin-more-accessible-via-linkedin-lite modern web is so inefficient it is useless for part of its audience “my heart sank … our new feature failed to load because of poor internet connectivity” Nashik

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@holly_cummins #RedHat forgotten code is killing the planet

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#RedHat @[email protected] 25% of 16,000 servers doing no useful work https://www.anthesisgroup.com/wp-content/uploads/2019/11/Comatose-Servers-Redux-2017.pdf zombie servers

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#RedHat @[email protected] the average server: 12 - 18% of capacity https://www.nrdc.org/sites/default/files/data-center-efficiency-assessment-IB.pdf

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@holly_cummins #RedHat unused data is killing the planet

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#RedHat @[email protected] 68% of data is stored and never used https://www.nrdc.org/sites/default/files/data-center-efficiency-assessment-IB.pdf https://www.seagate.com/gb/en/news/news-archive/seagates-rethink-data-report-reveals-that-68-percent-of-data-available-to-businesses-goes-unleveraged-pr-master/

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@holly_cummins #RedHat it’s not just money

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@holly_cummins #RedHat it’s not just electricity it’s not just money

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@holly_cummins #RedHat it’s not just electricity it’s not just money it’s embodied carbon

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@holly_cummins #RedHat it’s not just electricity it’s water it’s not just money it’s embodied carbon

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@holly_cummins #RedHat it’s not just electricity it’s water it’s e-waste it’s not just money it’s embodied carbon

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@holly_cummins #RedHat we have solutions good news, everyone

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@holly_cummins #RedHat making turning servers off as safe and easy as turning lights off. and then automate it.

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@holly_cummins #RedHat solution: LightSwitchOps making turning servers off as safe and easy as turning lights off. and then automate it.

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@holly_cummins #RedHat absurdly simple scripts my shell script to power down machines overnight saved my school €12,000

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@holly_cummins #RedHat simple automation we used to leave our applications running all the time @darkandnerdy, Chicago DevOpsDays

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@holly_cummins #RedHat simple automation we used to leave our applications running all the time when we scripted turning them off at night, we reduced our cloud bill by 30% @darkandnerdy, Chicago DevOpsDays

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@holly_cummins #RedHat fancier scripts … with a frontend and a backend

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@holly_cummins #RedHat

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@holly_cummins #RedHat saves energy

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@holly_cummins #RedHat saves energy saves money

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@holly_cummins #RedHat saves energy saves money bonus: tests disaster recovery

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@holly_cummins #RedHat saves energy saves money bonus: tests disaster recovery

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@holly_cummins #RedHat

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@holly_cummins #RedHat solution: faster code

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@holly_cummins the vrroooom model

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@holly_cummins

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@holly_cummins invented by Dr. Vroom (really!)

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@holly_cummins naming is the hardest problem in computer science invented by Dr. Vroom (really!)

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@holly_cummins naming is the hardest problem in computer science

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@holly_cummins my vrroooom model

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@holly_cummins #RedHat

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@holly_cummins #RedHat these two columns are almost the same

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@holly_cummins #RedHat Energy 1 10 100 Time 1 10 100 energy efficiency across programming languages Python Rust Java Go

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@holly_cummins #RedHat Energy 1 10 100 Time 1 10 100 the trend line is more or less straight energy efficiency across programming languages Python Rust Java Go

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case study Quarkus

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@holly_cummins #RedHat Java application frameworks needed dynamic dependencies the distant past

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@holly_cummins #RedHat cloud apps are immutable now

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@holly_cummins #RedHat cloud apps are immutable now

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@holly_cummins #RedHat a highly dynamic runtime in a container is pointless

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@holly_cummins Java dynamism

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@holly_cummins Java dynamism build time

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@holly_cummins Java dynamism build time runtime

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@holly_cummins Java dynamism build time runtime

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@holly_cummins Java dynamism packaging (maven, gradle…) build time runtime

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@holly_cummins Java dynamism build time runtime

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@holly_cummins Java dynamism build time runtime

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@holly_cummins Java dynamism > build time runtime load and parse • config files • properties • yaml • xml • etc.

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@holly_cummins Java dynamism > build time runtime

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@holly_cummins Java dynamism @ @ > build time runtime • classpath scanning and annotation discovery • attempt to load class to enable/disable features

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@holly_cummins Java dynamism @ @ > build time runtime

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@holly_cummins Java dynamism @ @ > build time runtime build a metamodel of the world

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@holly_cummins Java dynamism @ @ > build time runtime

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@holly_cummins Java dynamism @ @ > build time runtime start • thread pools • I/O • etc.

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@holly_cummins Java dynamism @ @ > build time runtime ready to do work!

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@holly_cummins what if we start the application more than once? @ @ >

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@holly_cummins what if we start the application more than once? @ @ > @ @ >

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@holly_cummins what if we start the application more than once? @ @ > @ @ > @ @ >

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@holly_cummins what if we start the application more than once? @ @ > @ @ > @ @ > @ @ >

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@holly_cummins what if we start the application more than once? @ @ > @ @ > @ @ > @ @ >

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@holly_cummins what if we start the application more than once? @ @ > @ @ > @ @ > @ @ > so much work gets redone every time

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@holly_cummins Hibernate speed example: JTA auto-wiring

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@holly_cummins Hibernate speed example: JTA auto-wiring Class.forName(“LikelyJTAImplementation”);

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@holly_cummins Hibernate speed example: JTA auto-wiring Class.forName(“LikelyJTAImplementation”);

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@holly_cummins Hibernate speed example: JTA auto-wiring Class.forName(“LikelyJTAImplementation”); Class.forName(“APossibleJTAImplementation”);

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@holly_cummins Hibernate speed example: JTA auto-wiring Class.forName(“LikelyJTAImplementation”); Class.forName(“APossibleJTAImplementation”); Class.forName(“AnotherJTAImplementation”);

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@holly_cummins Hibernate speed example: JTA auto-wiring Class.forName(“LikelyJTAImplementation”); Class.forName(“APossibleJTAImplementation”); Class.forName(“AnotherJTAImplementation”); …

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@holly_cummins Hibernate speed example: JTA auto-wiring Class.forName(“LikelyJTAImplementation”); Class.forName(“APossibleJTAImplementation”); Class.forName(“AnotherJTAImplementation”); Class.forName(“NicheJTAImplementation”); …

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@holly_cummins Hibernate speed example: JTA auto-wiring Class.forName(“LikelyJTAImplementation”); Class.forName(“APossibleJTAImplementation”); Class.forName(“AnotherJTAImplementation”); Class.forName(“NicheJTAImplementation”); Class.forName(“VeryNicheJTAImplementation”); …

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@holly_cummins Hibernate speed example: JTA auto-wiring Class.forName(“LikelyJTAImplementation”); Class.forName(“APossibleJTAImplementation”); Class.forName(“AnotherJTAImplementation”); Class.forName(“NicheJTAImplementation”); Class.forName(“VeryNicheJTAImplementation”); …

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@holly_cummins Hibernate speed example: JTA auto-wiring Class.forName(“LikelyJTAImplementation”); Class.forName(“APossibleJTAImplementation”); Class.forName(“AnotherJTAImplementation”); Class.forName(“NicheJTAImplementation”); Class.forName(“VeryNicheJTAImplementation”); … ~129 auto-wiring attempts

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@holly_cummins Hibernate speed example: JTA auto-wiring Class.forName(“LikelyJTAImplementation”); Class.forName(“APossibleJTAImplementation”); Class.forName(“AnotherJTAImplementation”); Class.forName(“NicheJTAImplementation”); Class.forName(“VeryNicheJTAImplementation”); … ~129 auto-wiring attempts every single start.

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@holly_cummins the true cost of loaded classes isn’t just memory + start time

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@holly_cummins the true cost of loaded classes isn’t just memory + start time method dispatching:

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@holly_cummins interface the true cost of loaded classes isn’t just memory + start time method dispatching:

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@holly_cummins unused implementation the one we want interface unused implementation unused implementation the true cost of loaded classes isn’t just memory + start time method dispatching:

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@holly_cummins unused implementation the one we want interface unused implementation unused implementation the true cost of loaded classes isn’t just memory + start time method dispatching:

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@holly_cummins unused implementation the one we want interface megamorphic call slow dispatching unused implementation unused implementation the true cost of loaded classes isn’t just memory + start time method dispatching:

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@holly_cummins the true cost of loaded classes isn’t just memory + start time the one we want interface

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@holly_cummins the true cost of loaded classes isn’t just memory + start time the one we want monomorphic call fast dispatching interface

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@holly_cummins how do we fix all this?

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@holly_cummins @ @ > build time runtime what if we initialize at build time?

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@holly_cummins @ @ > build time runtime what if we initialize at build time?

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@holly_cummins @ @ > build time runtime ready to do work! what if we initialize at build time?

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@holly_cummins @ @ > build time runtime ready to do work! start • thread pools • I/O • etc. what if we initialize at build time?

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@holly_cummins @ @ > repeated starts are now efficient

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@holly_cummins @ @ > repeated starts are now efficient

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@holly_cummins @ @ > repeated starts are now efficient

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@holly_cummins @ @ > repeated starts are now efficient

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@holly_cummins @ @ > repeated starts are now efficient

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@holly_cummins @ @ > repeated starts are now efficient

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@holly_cummins @ @ > repeated starts are now efficient less wasted work

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@holly_cummins #RedHat Setup: • REST + CRUD • large heap • RAPL energy measurement • multiple instances to support high load
 Assumptions: • US energy mix Source: John O’Hara effect on energy consumption (RAPL measurements)

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@holly_cummins #RedHat Setup: • REST + CRUD • large heap • RAPL energy measurement • multiple instances to support high load
 Assumptions: • US energy mix Source: John O’Hara effect on energy consumption (RAPL measurements) vrrooom model in action quarkus on JVM has the lowest carbon … because it has the highest throughput

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@holly_cummins 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

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

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@holly_cummins we beat another trade-off. human efficiency machine efficiency

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@holly_cummins we beat another trade-off. human efficiency machine efficiency

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@holly_cummins we beat another trade-off. human efficiency machine efficiency another double-win.

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@holly_cummins #RedHat boilerplate code

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@holly_cummins #RedHat boilerplate code

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@holly_cummins #RedHat package com.example; import org.jboss.logging.Logger; public class Thing { private static final Logger log = Logger.getLogger(Thing.class); public void doSomething() { log.info("It works!"); } } example: logging

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@holly_cummins #RedHat package com.example; import org.jboss.logging.Logger; public class Thing { private static final Logger log = Logger.getLogger(Thing.class); public void doSomething() { log.info("It works!"); } } example: logging import io.quarkus.logging.Log; Log

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@holly_cummins #RedHat @ApplicationScoped public class GreetingRepository { public Entity findByName(int name) { return find("name", name).firstResult(); } void persist(Entity entity) {} void delete(Entity entity) {} Entity findById(Id id) {} List list(String query, Sort sort, Object... params) { return null; } Stream stream(String query, Object... params) { return null; } long count() { return 0; } long count(String query, Object... params) { return 0; } } example: hibernate with panache

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@holly_cummins #RedHat @ApplicationScoped public class GreetingRepository { public Entity findByName(int name) { return find("name", name).firstResult(); } void persist(Entity entity) {} void delete(Entity entity) {} Entity findById(Id id) {} List list(String query, Sort sort, Object... params) { return null; } Stream stream(String query, Object... params) { return null; } long count() { return 0; } long count(String query, Object... params) { return 0; } } example: hibernate with panache

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@holly_cummins #RedHat DAO example: hibernate with panache @ApplicationScoped public class GreetingRepository implements PanacheRepository { public Entity findByName(int name) { return find("name", name).firstResult(); } }

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@holly_cummins #RedHat developer joy

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@holly_cummins #RedHat the ai-lephant in the room

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@holly_cummins #RedHat

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@holly_cummins #RedHat we don’t need to have a nice programming model; people can just use AI to write the bad code!

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@holly_cummins #RedHat

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@holly_cummins #RedHat 15%

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@holly_cummins #RedHat efficiency of kangaroo- powered renewable energy 15%

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@holly_cummins #RedHat

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@holly_cummins #RedHat disclaimer:

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@holly_cummins #RedHat disclaimer: this isn’t a thing.

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@holly_cummins #RedHat disclaimer: this isn’t a thing. researchers did not use kangaroos on trampolines for electricity generation.

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@holly_cummins #RedHat

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@holly_cummins #RedHat

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@holly_cummins #RedHat

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@holly_cummins #RedHat

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@holly_cummins #RedHat

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@holly_cummins #RedHat

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@holly_cummins #RedHat

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@holly_cummins #RedHat

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@holly_cummins #RedHat 70% unnecessary code

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@holly_cummins #RedHat “illusion of efficiency”

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@holly_cummins #RedHat we have a solution

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@holly_cummins #RedHat -small fine-tuned models -small model + RAG -hybrid: symbolic reasoning + model solution:

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@holly_cummins #RedHat illusions of efficiency are everywhere

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@holly_cummins #RedHat

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@holly_cummins #RedHat

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@holly_cummins #RedHat how efficient can we get?

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@holly_cummins #RedHat how efficient do we want to get?

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@holly_cummins #RedHat

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@holly_cummins #RedHat speed

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@holly_cummins #RedHat speed vs resiliency

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@holly_cummins #RedHat #RedHat

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@holly_cummins #RedHat highly efficient (optimum number of legs) #RedHat

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@holly_cummins #RedHat highly efficient (optimum number of legs) less efficient (more legs than needed) #RedHat

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@holly_cummins #RedHat highly efficient (optimum number of legs) less efficient (more legs than needed) resilient #RedHat

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@holly_cummins #RedHat highly efficient (optimum number of legs) less efficient (more legs than needed) resilient #RedHat

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@holly_cummins #RedHat highly efficient (optimum number of legs) no resiliency less efficient (more legs than needed) resilient #RedHat

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@holly_cummins #RedHat highly efficient (optimum number of legs) no resiliency less efficient (more legs than needed) resilient #RedHat resiliency lowers efficiency

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@holly_cummins #RedHat let’s talk about your multi-region failover.

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@holly_cummins resiliency efficiency

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@holly_cummins #RedHat ok but how efficient can we get?

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@holly_cummins #RedHat Jevon’s paradox limit 1

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@holly_cummins #RedHat what we imagine when we widen roads

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@holly_cummins #RedHat what we get

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@holly_cummins #RedHat limit 2

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@holly_cummins #RedHat even for machines, there is a limit to efficiency limit 2

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@holly_cummins #RedHat even for machines, there is a limit to efficiency …and it’s lower than you think limit 2

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@holly_cummins #RedHat source: http://geosci.uchicago.edu/~moyer/GEOS24705/2016/Assignments/PS7.pdf physics limit 2

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@holly_cummins #RedHat limit 2

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@holly_cummins #RedHat limit 2

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@holly_cummins #RedHat theoretical max efficiency of a combustion engine limit 2

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@holly_cummins #RedHat theoretical max efficiency of a combustion engine limit 2 37%

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@holly_cummins #RedHat limit 2

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@holly_cummins #RedHat limit 2 ~20%

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@holly_cummins #RedHat if we want the engine to not wear out limit 2 ~20%

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@holly_cummins #RedHat it’s the same for people

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@holly_cummins #RedHat it’s the same for people all work and no play is … not efficient

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@holly_cummins #RedHat

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@holly_cummins #RedHat

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@holly_cummins #RedHat hi colleague, could you ple-

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@holly_cummins #RedHat hi colleague, could you ple- argh! &!*$*%@!{*%^!^! busy! NO! I CANNOT!

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@holly_cummins #RedHat the value of slack

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@holly_cummins #RedHat the value of slack

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@holly_cummins #RedHat the value of slack

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@holly_cummins #RedHat the value of slack naming is still the hardest problem in computer science

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@holly_cummins #RedHat the value of slack

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@holly_cummins #RedHat

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@holly_cummins #RedHat

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@holly_cummins #RedHat

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@holly_cummins #RedHat studies show…

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@holly_cummins #RedHat studies show… employee slack

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@holly_cummins #RedHat studies show… employee slack

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@holly_cummins #RedHat studies show… employee slack harder working

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@holly_cummins #RedHat studies show… employee slack harder working more productivity

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@holly_cummins #RedHat studies show… employee slack harder working more productivity less sick leave

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@holly_cummins #RedHat a lot of studies

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@holly_cummins #RedHat a lot of studies

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@holly_cummins #RedHat https:/ /hbr.org/2012/01/positive-intelligence

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@holly_cummins #RedHat “Your brain at positive is 31% more productive than your brain at negative, neutral or stressed. " https:/ /hbr.org/2012/01/positive-intelligence

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#RedHat @holly_cummins

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@holly_cummins #RedHat https:/ /wrap.warwick.ac.uk/63228/7/WRAP_Oswald_681096.pdf

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@holly_cummins #RedHat "Individuals [who just watched a comedy video] have approximately 12% greater productivity." https:/ /wrap.warwick.ac.uk/63228/7/WRAP_Oswald_681096.pdf

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@holly_cummins #RedHat play

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@holly_cummins #RedHat play efficiency

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@holly_cummins #RedHat doing nothing

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@holly_cummins #RedHat doing nothing efficiency

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@holly_cummins #RedHat the default mode network idle minds can solve hard problems

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#RedHat @holly_cummins

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#RedHat @holly_cummins

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#RedHat @holly_cummins

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#RedHat @holly_cummins

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#RedHat @holly_cummins 14% took showers specifically for the purpose of coming up with ideas

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@holly_cummins #RedHat psychology says we need idle time; maths agrees

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@holly_cummins #RedHat queueing theory says systems need to run under-capacity to function psychology says we need idle time; maths agrees

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@holly_cummins #RedHat queuing theory basics

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@holly_cummins #RedHat queuing theory basics arrival process

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@holly_cummins #RedHat queuing theory basics arrival process Poisson distribution

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@holly_cummins #RedHat queuing theory basics queue arrival process Poisson distribution

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@holly_cummins #RedHat queuing theory basics queue arrival process Poisson distribution

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@holly_cummins #RedHat queuing theory basics queue arrival process servers Poisson distribution

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@holly_cummins #RedHat queuing theory basics queue arrival process servers Poisson distribution

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@holly_cummins #RedHat queuing theory basics queue arrival process servers completed work Poisson distribution

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@holly_cummins #RedHat if arrival rates are low, servers will be idle queue arrival process servers completed work

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@holly_cummins #RedHat queue arrival process servers completed work if server capacity is too low, wait times are high

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@holly_cummins #RedHat utilisation lead time http://brodzinski.com/2015/01/slack-time-value.html assuming Poisson distribution of arrivals

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@holly_cummins #RedHat utilisation lead time http://brodzinski.com/2015/01/slack-time-value.html assuming Poisson distribution of arrivals 80% utilisation → 90% utilisation: wait times double

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@holly_cummins #RedHat utilisation http://brodzinski.com/2015/01/slack-time-value.html cost delay cost assuming Poisson distribution of arrivals 80% utilisation → 90% utilisation: wait times double

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@holly_cummins #RedHat utilisation http://brodzinski.com/2015/01/slack-time-value.html cost delay cost cost of idle capacity assuming Poisson distribution of arrivals 80% utilisation → 90% utilisation: wait times double

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@holly_cummins #RedHat

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@holly_cummins #RedHat “Eight Hour Day Parade”

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@holly_cummins #RedHat “Eight Hour Day Parade” 1907

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@holly_cummins #RedHat

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@holly_cummins #RedHat

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@holly_cummins #RedHat

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@holly_cummins #RedHat productivity stayed the same

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@holly_cummins #RedHat

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@holly_cummins #RedHat

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@holly_cummins #RedHat 42% decrease in resignations

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@holly_cummins #RedHat 42% decrease in resignations 36% increase in revenue

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@holly_cummins #RedHat efficiency may not look how we expect

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@holly_cummins #RedHat most efficient land animal efficiency may not look how we expect

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@holly_cummins #RedHat most efficient land animal cool and bouncy efficiency may not look how we expect

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@holly_cummins #RedHat most efficient land animal cool and bouncy uncool and floppy efficiency may not look how we expect

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@holly_cummins #RedHat most efficient land animal cool and bouncy uncool and floppy whole body is basically slack efficiency may not look how we expect

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@holly_cummins #RedHat most efficient land animal cool and bouncy uncool and floppy whole body is basically slack most efficient animal efficiency may not look how we expect

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@holly_cummins #RedHat inverse Jevon’s paradox doing less achieves more

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@holly_cummins being effective working less

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@holly_cummins being effective working less

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@holly_cummins being effective working less another double-win.

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@holly_cummins #RedHat tl;dpa (too long; didn’t pay attention)

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@holly_cummins #RedHat tl;dpa ⁃ don’t accept waste; our world deserves better (too long; didn’t pay attention)

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@holly_cummins #RedHat tl;dpa ⁃ don’t accept waste; our world deserves better ⁃ work less; achieve more (too long; didn’t pay attention)

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@holly_cummins #RedHat tl;dpa ⁃ don’t accept waste; our world deserves better ⁃ work less; achieve more ⁃ happiness is not waste (too long; didn’t pay attention)

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@holly_cummins #RedHat tl;dpa ⁃ don’t accept waste; our world deserves better ⁃ work less; achieve more ⁃ happiness is not waste ⁃ idleness is not waste (too long; didn’t pay attention)

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@holly_cummins #RedHat tl;dpa ⁃ don’t accept waste; our world deserves better ⁃ work less; achieve more ⁃ happiness is not waste ⁃ idleness is not waste ⁃ look for double-wins everywhere (too long; didn’t pay attention)

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