Writing Greener Java Applications

The code we write has a climate impact. But how big is that impact? How do we measure it? How do we reduce it? Is the cloud helping? What’s going on with Virginia? Are we still allowed to do CI/CD? Will native compilation save us? Is Java even a good choice anymore? This talk discusses some of the trade-offs for a modern software developer, and provides a roadmap to figuring out the right thing.

Disclosure: I work on Quarkus. Along the way, I will talk about Quarkus sustainability measurements we’ve been doing … but it’s ok, because the Quarkus carbon data is exciting and interesting, I promise.

Transcript

1. Holly Cummins Senior Principal Software Engineer, Quarkus Devoxx UK May 10, 2023 @holly_cummins@hachyderm.io Writing Greener Java Applications
2. @holly_cummins #RedHat Sources: https://www.greenit.fr/wp-content/uploads/2019/11/GREENIT_EENM_etude_EN_accessible.pdf https://ourworldindata.org/ghg-emissions-by-sector the digital world creates more carbon emissions than aviation
3. @holly_cummins #RedHat Lighter area represents high and low estimates, where available. Sources: https://www.iea.org/fuels-and-technologies/data-centres-networks https://ourworldindata.org/grapher/electricity-demand?tab=table&country=USA~GBR~FRA~DEU~IND~BRA data centres use as much electricity as a medium country
4. @holly_cummins #RedHat aaaaaaaargh
5. @holly_cummins #RedHat aaaaaaaargh?
6. @holly_cummins #RedHat be a solutionist
7. @holly_cummins #RedHat what should we do?
8. @holly_cummins #RedHat should we reduce our greenhouse gases?
9. @holly_cummins #RedHat • right thing to do should we reduce our greenhouse gases?
10. @holly_cummins #RedHat • right thing to do • business benefits should we reduce our greenhouse gases?
11. @holly_cummins #RedHat • right thing to do • business benefits • lower costs should we reduce our greenhouse gases?
12. @holly_cummins #RedHat • right thing to do • business benefits • lower costs • higher ESG score should we reduce our greenhouse gases?
13. @holly_cummins #RedHat • right thing to do • business benefits • lower costs • higher ESG score • competitive advantage should we reduce our greenhouse gases?
14. @holly_cummins #RedHat • right thing to do • business benefits • lower costs • higher ESG score • competitive advantage • recruitment advantage should we reduce our greenhouse gases?
15. @holly_cummins #RedHat green software foundation: principles
16. @holly_cummins #RedHat carbon awareness green software foundation: principles
17. @holly_cummins #RedHat carbon awareness green software foundation: principles where
18. @holly_cummins #RedHat carbon awareness green software foundation: principles where when
19. @holly_cummins #RedHat carbon awareness green software foundation: principles hardware efficiency where when
20. @holly_cummins #RedHat carbon awareness green software foundation: principles hardware efficiency where when elasticity
21. @holly_cummins #RedHat carbon awareness green software foundation: principles hardware efficiency where when elasticity utilisation
22. @holly_cummins #RedHat carbon awareness green software foundation: principles hardware efficiency electricity efficiency where when elasticity utilisation
23. @holly_cummins #RedHat algorithms carbon awareness green software foundation: principles hardware efficiency electricity efficiency where when elasticity utilisation
24. @holly_cummins #RedHat algorithms stack carbon awareness green software foundation: principles hardware efficiency electricity efficiency where when elasticity utilisation
25. @holly_cummins #RedHat algorithms stack carbon awareness hardware efficiency electricity efficiency where when elasticity utilisation green software foundation: principles
26. step 1: electricity source
27. @holly_cummins #RedHat data center location matters
28. @holly_cummins #RedHat
29. @holly_cummins #RedHat we need to talk about virginia
30. @holly_cummins #RedHat look at the sustainability information before choosing a hosting region
31. @holly_cummins #RedHat look at the sustainability information before choosing a hosting region choose a cloud provider who make this easy
32. @holly_cummins #RedHat time of day matters • (most) renewables are intermittent • if grid load is high, shortfalls are filled by fossil fuels
33. @holly_cummins #RedHat move the workload to the greenest place
34. @holly_cummins #RedHat move the workload to the greenest place
35. @holly_cummins #RedHat move the workload to the greenest place a data problem
36. @holly_cummins #RedHat move the workload to the greenest place a data problem an orchestration problem
37. @holly_cummins #RedHat carbon awareness green software foundation: principles hardware efficiency electricity efficiency
38. @holly_cummins #RedHat carbon awareness green software foundation: principles hardware efficiency electricity efficiency elasticity
39. @holly_cummins #RedHat carbon awareness green software foundation: principles hardware efficiency electricity efficiency elasticity utilisation
40. @holly_cummins #RedHat
41. @holly_cummins #RedHat elasticity 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
42. #RedHat @holly_cummins 2017 survey 25% of 16,000 servers doing no useful work
43. #RedHat @holly_cummins 2017 survey 25% of 16,000 servers doing no useful work “perhaps someone forgot to turn them off”
44. #RedHat @holly_cummins@hachyderm.io 2014 survey 29% of 4,000 active less than 5% of the time https://www.anthesisgroup.com/wp-content/uploads/2019/11/Comatose-Servers-Redux-2017.pdf
45. @holly_cummins #RedHat yes, turning applications off is scary
46. @holly_cummins #RedHat ultimate elasticity
47. @holly_cummins #RedHat ultimate elasticity
48. @holly_cummins #RedHat turning it off and on again must ultimate elasticity
49. @holly_cummins #RedHat turning it off and on again must • be fast ultimate elasticity
50. @holly_cummins #RedHat turning it off and on again must • be fast • actually work ultimate elasticity
51. @holly_cummins #RedHat turning it off and on again must • be fast • actually work • idempotency ultimate elasticity
52. @holly_cummins #RedHat turning it off and on again must • be fast • actually work • idempotency • resiliency ultimate elasticity
53. @holly_cummins #RedHat
54. @holly_cummins #RedHat LightSwitchOps
55. @holly_cummins #RedHat LightSwitchOps
56. @holly_cummins #RedHat algorithms stack carbon awareness hardware efficiency electricity efficiency where when elasticity utilisation green software foundation: principles
57. @holly_cummins #RedHat efficiency
58. @holly_cummins #RedHat what programming languages use the least energy?
59. @holly_cummins #RedHat what programming languages use the most energy?
61. energy efficiency of programming languages
62. @holly_cummins #RedHat
63. @holly_cummins #RedHat
65. @holly_cummins #RedHat “Our results show that some JVM platforms can exhibit up to 100% more energy consumption.” https://hal.inria.fr/hal-03275286/document
66. @holly_cummins #RedHat if JVM parameters can make that much difference … … what impact does the framework have?
67. @holly_cummins #RedHat
68. @holly_cummins #RedHat
69. @holly_cummins #RedHat does being small and fast reduce carbon footprint?
70. #Quarkus @holly_cummins measure, don’t guess.
71. digression: measuring carbon is hard
72. @holly_cummins #RedHat step 1: measure power usage
73. @holly_cummins #RedHat step 1: measure power usage wall power measurement
74. @holly_cummins #RedHat step 1: measure power usage wall power measurement more complete
75. @holly_cummins #RedHat step 1: measure power usage wall power measurement more complete needs access to the wall
76. @holly_cummins #RedHat step 1: measure power usage wall power measurement more complete needs access to the wall and equipment
77. @holly_cummins #RedHat step 1: measure power usage wall power measurement more complete needs access to the wall and equipment and actual paper
78. @holly_cummins #RedHat step 1: measure power usage wall power measurement more complete needs access to the wall and equipment and actual paper RAPL
79. @holly_cummins #RedHat step 1: measure power usage wall power measurement more complete needs access to the wall and equipment and actual paper RAPL programmatically accessible
80. @holly_cummins #RedHat step 1: measure power usage wall power measurement more complete needs access to the wall and equipment and actual paper RAPL programmatically accessible misses some components
81. @holly_cummins #RedHat step 1: measure power usage wall power measurement more complete needs access to the wall and equipment and actual paper data costs carbon RAPL programmatically accessible misses some components
82. @holly_cummins #RedHat
83. @holly_cummins #RedHat
84. @holly_cummins #RedHat
85. @holly_cummins #RedHat load
86. @holly_cummins #RedHat Source: Teads EC2 instances carbon dataset
87. @holly_cummins #RedHat coal wind step 2: convert power usage to carbon solar
88. @holly_cummins #RedHat published energy mixes (these are made-up energy mixes)
89. @holly_cummins #RedHat published energy mixes … but methodologies are not open (these are made-up energy mixes)
90. @holly_cummins #RedHat published energy mixes … but methodologies are not open … or consistent (these are made-up energy mixes)
91. @holly_cummins #RedHat step 3: embedded carbon (manufacturing has costs)
92. @holly_cummins #RedHat simpler models
93. @holly_cummins #RedHat vrrrrrooooooooom model* * a made-up name
94. @holly_cummins #RedHat
95. @holly_cummins #RedHat these two columns are almost the same
96. @holly_cummins #RedHat energy consumption (sort of, mostly) is proportional to execution time
97. @holly_cummins #RedHat economic model*
98. @holly_cummins #RedHat economic model* * "economic input-output life cycle assessment"
99. @holly_cummins #RedHat reducing your cloud spend (probably) reducing your carbon footprint* hardware spend electricity bill * if you keep other factors the same
100. @holly_cummins #RedHat all models are wrong, some are useful
101. so … quarkus?
102. @holly_cummins #RedHat density Source: Clement Escoffier cost impact of framework choice Setup: • 800 requests/second, over 20 days • SLA > 99% • AWS instances Assumptions: • Costs are for us-east-1 data centre
103. @holly_cummins #RedHat Setup: • 800 requests/second, over 20 days • SLA > 99% Assumptions: • 50% load • us-east-1 data centre • Teads dataset Source: Clement Escoffier x Teads cloud carbon impact of framework choice
104. • quarkus cuts carbon by ~2x* • native has a slightly smaller carbon footprint * OOM heuristic density test: conclusions
105. @holly_cummins #RedHat capacity Source: John O’Hara Setup: • REST + CRUD • large heap • RAPL energy measurement Assumptions: • US energy mix climate impact at low load (single instance)
106. @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 climate impact at high load (multiple instances)
107. • quarkus cuts carbon by ~2-3x* • native consumes more carbon than JVM capacity test: conclusions * OOM heuristic
108. @holly_cummins #RedHat so does quarkus reduce carbon emissions?
109. @holly_cummins #RedHat so does quarkus reduce carbon emissions?
110. @holly_cummins #RedHat so does quarkus reduce carbon emissions? quarkus ‘automatically’ saves
111. @holly_cummins #RedHat so does quarkus reduce carbon emissions? quarkus ‘automatically’ saves • time
112. @holly_cummins #RedHat so does quarkus reduce carbon emissions? quarkus ‘automatically’ saves • time • money
113. @holly_cummins #RedHat so does quarkus reduce carbon emissions? quarkus ‘automatically’ saves • time • money • carbon (~2x)
114. @holly_cummins #RedHat so does quarkus reduce carbon emissions? quarkus ‘automatically’ saves • time • money • carbon (~2x)
115. @holly_cummins #RedHat but what about native? reminder
116. @holly_cummins #RedHat but what about native? use case for native reminder
117. @holly_cummins #RedHat but what about native? use case for native • low workload (throughput isn’t the bottleneck) reminder
118. @holly_cummins #RedHat but what about native? use case for native • low workload (throughput isn’t the bottleneck) • resource-constrained or old hardware (especially memory) reminder
119. @holly_cummins #RedHat but what about native? use case for native • low workload (throughput isn’t the bottleneck) • resource-constrained or old hardware (especially memory) • high re-deploy rate (applications never get warmed up before being spun down) reminder
120. @holly_cummins #RedHat but what about native? use case for native • low workload (throughput isn’t the bottleneck) • resource-constrained or old hardware (especially memory) • high re-deploy rate (applications never get warmed up before being spun down) • serverless (of course) reminder
121. @holly_cummins #RedHat but what about native? use case for native • low workload (throughput isn’t the bottleneck) • resource-constrained or old hardware (especially memory) • high re-deploy rate (applications never get warmed up before being spun down) • serverless (of course) use case for JVM reminder
122. @holly_cummins #RedHat but what about native? use case for native • low workload (throughput isn’t the bottleneck) • resource-constrained or old hardware (especially memory) • high re-deploy rate (applications never get warmed up before being spun down) • serverless (of course) use case for JVM • high workload (you need lots of throughput) reminder
123. @holly_cummins #RedHat but what about native? use case for native • low workload (throughput isn’t the bottleneck) • resource-constrained or old hardware (especially memory) • high re-deploy rate (applications never get warmed up before being spun down) • serverless (of course) use case for JVM • high workload (you need lots of throughput) • long-lived processes (the rapid start of native doesn’t save you much over the lifetime) reminder
124. @holly_cummins #RedHat but what about native? use case for native • low workload (throughput isn’t the bottleneck) • resource-constrained or old hardware (especially memory) • high re-deploy rate (applications never get warmed up before being spun down) • serverless (of course) use case for JVM • high workload (you need lots of throughput) • long-lived processes (the rapid start of native doesn’t save you much over the lifetime) • stable workload or very little elasticity in underlying orchestration reminder
125. @holly_cummins #RedHat use case for native • low workload (so throughput isn’t the bottleneck) • resource-constrained or old hardware (especially memory) • high re-deploy rate (applications never get warmed up before being spun down) • serverless (of course) 
 use case for JVM • high workload (you need lots of throughput) • long-lived processes (the rapid start of native doesn’t save you much over the lifetime) • stable workload or very little elasticity in underlying orchestration but what about native? to optimise carbon
126. @holly_cummins #RedHat yes, those are the same optimising • cost • application performance will also be optimising carbon
127. @holly_cummins #RedHat native vs JVM is not an either-or • consider hybrid deployment models • a strength of Quarkus is application code is the same for native and JVM
128. @holly_cummins #RedHat native CLIs? • native is not just for serverless • native Java makes great CLIs • is a CLI usually the most carbon- efficient way to do something?
129. @holly_cummins #RedHat elasticity native quarkus starts faster than a light bulb
130. @holly_cummins #RedHat but. an app starting fast isn’t elasticity … …unless you also stop the app
131. @holly_cummins #RedHat how does quarkus help reduce carbon? energy usage elasticity machine selection (provisioning)
132. @holly_cummins #RedHat how does quarkus help reduce carbon? energy usage ‘free’ direct easy to measure elasticity machine selection (provisioning)
133. @holly_cummins #RedHat how does quarkus help reduce carbon? energy usage ‘free’ direct easy to measure lower memory usage higher throughput for same resources elasticity machine selection (provisioning)
134. @holly_cummins #RedHat how does quarkus help reduce carbon? energy usage ‘free’ direct easy to measure lower memory usage higher throughput for same resources ‘enabled behaviours’ harder to measure real world impact depends on people taking advantage elasticity machine selection (provisioning)
135. @holly_cummins #RedHat how does quarkus help reduce carbon? energy usage ‘free’ direct easy to measure lower memory usage higher throughput for same resources ‘enabled behaviours’ harder to measure real world impact depends on people taking advantage elasticity machine selection (provisioning)
136. @holly_cummins #RedHat how does quarkus help reduce carbon? energy usage ‘free’ direct easy to measure lower memory usage higher throughput for same resources ‘enabled behaviours’ harder to measure real world impact depends on people taking advantage elasticity machine selection (provisioning) running the same workload on a smaller machine saves energy saves embodied carbon
137. @holly_cummins #RedHat how does quarkus help reduce carbon? energy usage ‘free’ direct easy to measure lower memory usage higher throughput for same resources ‘enabled behaviours’ harder to measure real world impact depends on people taking advantage elasticity machine selection (provisioning) scaling workloads down (ideally to 0) serverless a good example (but not the only one) running the same workload on a smaller machine saves energy saves embodied carbon
138. @holly_cummins #RedHat aaaaaaaargh?
139. @holly_cummins #RedHat remember the vrrrrrooooooooom model? (probably not, it was a made-up name)
140. @holly_cummins #RedHat we need a new mental model car: high max speed means high fuel usage per mile travelled
141. @holly_cummins #RedHat software: high max transactions means low carbon per transaction we need a new mental model car: high max speed means high fuel usage per mile travelled
142. @holly_cummins #RedHat carbon awareness hardware efficiency electricity efficiency green software foundation: principles utility
143. @holly_cummins #RedHat is using this carbon giving value? utility
144. @holly_cummins #RedHat “no-regrets” solutions
145. @holly_cummins #RedHat
146. @holly_cummins #RedHat co-benefits
147. @holly_cummins #RedHat co-benefits the double win
148. @holly_cummins #RedHat co-benefits the double win win-win
149. @holly_cummins #RedHat co-benefits the double win win-win win-squared
150. @holly_cummins #RedHat co-benefits the double win win-win win-squared 1 + 1 = 3
151. @holly_cummins #RedHat co-benefits the double win win-win win-squared 1 + 1 = 3 twofer
152. @holly_cummins #RedHat co-benefits the double win win-win win-squared 1 + 1 = 3 twofer überwinden
153. @holly_cummins #RedHat co-benefits the double win win-win win-squared 1 + 1 = 3 twofer überwinden the extra win
154. @holly_cummins #RedHat co-benefits the double win win-win win-squared 1 + 1 = 3 twofer überwinden the extra win
155. @holly_cummins #RedHat climate solutions can make everything better
156. @holly_cummins #RedHat remember the zombie servers? https://www.business2community.com/cloud-computing/overprovisioning-always-on-resources-lead-to-26-6-billion-in-public-cloud-waste-expected-in-2021-02381033
157. @holly_cummins #RedHat remember the zombie servers? $26.6 billion https://www.business2community.com/cloud-computing/overprovisioning-always-on-resources-lead-to-26-6-billion-in-public-cloud-waste-expected-in-2021-02381033
158. @holly_cummins #RedHat remember the zombie servers? $26.6 billion wasted https://www.business2community.com/cloud-computing/overprovisioning-always-on-resources-lead-to-26-6-billion-in-public-cloud-waste-expected-in-2021-02381033
159. @holly_cummins #RedHat remember the zombie servers? $26.6 billion wasted in 2021 https://www.business2community.com/cloud-computing/overprovisioning-always-on-resources-lead-to-26-6-billion-in-public-cloud-waste-expected-in-2021-02381033
160. @holly_cummins #RedHat the double-win turning things off saves a lot of money
161. @holly_cummins #RedHat the double-win renewable electricity is 9x cheaper
162. @holly_cummins #RedHat the double-win renewable electricity is 9x cheaper hosting in Montreal:
163. @holly_cummins #RedHat the double-win renewable electricity is 9x cheaper hosting in Montreal: 88% less carbon than the same workload in London
164. @holly_cummins #RedHat the double-win renewable electricity is 9x cheaper hosting in Montreal: 88% less carbon than the same workload in London and it’s 15% cheaper
165. @holly_cummins #RedHat the double-win
166. @holly_cummins #RedHat the double-win
167. @holly_cummins #RedHat “this is not sacrifice. it’s advancement.”
168. @holly_cummins #RedHat we all have a part to play • choose your hosting wisely • use your buying power to encourage businesses to do make greener choices • turn things off when you’re not using them • choose an energy-efficient framework • all of this is a win anyway
169. slides thank you @holly_cummins@hachyderm.io