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
   

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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
   

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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
   

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4. @holly_cummins #RedHat
   aaaaaaaargh
   

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5. @holly_cummins #RedHat
   aaaaaaaargh?
   

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6. @holly_cummins #RedHat
   be a solutionist
   

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7. @holly_cummins #RedHat
   what should we do?
   

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8. @holly_cummins #RedHat
   should we reduce our
   greenhouse gases?
   

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9. @holly_cummins #RedHat
   • right thing to do
   should we reduce our
   greenhouse gases?
   

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10. @holly_cummins #RedHat
    • right thing to do
    • business benefits
    should we reduce our
    greenhouse gases?
    

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11. @holly_cummins #RedHat
    • right thing to do
    • business benefits
    • lower costs
    should we reduce our
    greenhouse gases?
    

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12. @holly_cummins #RedHat
    • right thing to do
    • business benefits
    • lower costs
    • higher ESG score
    should we reduce our
    greenhouse gases?
    

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13. @holly_cummins #RedHat
    • right thing to do
    • business benefits
    • lower costs
    • higher ESG score
    • competitive advantage
    should we reduce our
    greenhouse gases?
    

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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?
    

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15. @holly_cummins #RedHat
    green software foundation: principles
    

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16. @holly_cummins #RedHat
    carbon
    awareness
    green software foundation: principles
    

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17. @holly_cummins #RedHat
    carbon
    awareness
    green software foundation: principles
    where
    

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18. @holly_cummins #RedHat
    carbon
    awareness
    green software foundation: principles
    where
    when
    

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19. @holly_cummins #RedHat
    carbon
    awareness
    green software foundation: principles
    hardware
    efficiency
    where
    when
    

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20. @holly_cummins #RedHat
    carbon
    awareness
    green software foundation: principles
    hardware
    efficiency
    where
    when
    elasticity
    

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21. @holly_cummins #RedHat
    carbon
    awareness
    green software foundation: principles
    hardware
    efficiency
    where
    when
    elasticity
    utilisation
    

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22. @holly_cummins #RedHat
    carbon
    awareness
    green software foundation: principles
    hardware
    efficiency
    electricity
    efficiency
    where
    when
    elasticity
    utilisation
    

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23. @holly_cummins #RedHat
    algorithms
    carbon
    awareness
    green software foundation: principles
    hardware
    efficiency
    electricity
    efficiency
    where
    when
    elasticity
    utilisation
    

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24. @holly_cummins #RedHat
    algorithms
    stack
    carbon
    awareness
    green software foundation: principles
    hardware
    efficiency
    electricity
    efficiency
    where
    when
    elasticity
    utilisation
    

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25. @holly_cummins #RedHat
    algorithms
    
    
    stack
    carbon
    awareness
    hardware
    efficiency
    electricity
    efficiency
    where
    
    
    when
    elasticity
    
    
    utilisation
    green software foundation: principles
    

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26. step 1: electricity source
    

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27. @holly_cummins #RedHat
    data center location matters
    

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28. @holly_cummins #RedHat
    

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29. @holly_cummins #RedHat
    we need to talk
    about virginia
    

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30. @holly_cummins #RedHat
    look at the sustainability information
    before choosing a hosting region
    

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31. @holly_cummins #RedHat
    look at the sustainability information
    before choosing a hosting region
    choose a cloud provider who make this easy
    

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32. @holly_cummins #RedHat
    time of day matters
    • (most) renewables are intermittent
    
    
    • if grid load is high, shortfalls are filled
    by fossil fuels
    

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33. @holly_cummins #RedHat
    move the workload
    to the greenest place
    

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34. @holly_cummins #RedHat
    move the workload
    to the greenest place
    

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35. @holly_cummins #RedHat
    move the workload
    to the greenest place
    a data problem
    

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36. @holly_cummins #RedHat
    move the workload
    to the greenest place
    a data problem
    an orchestration problem
    

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37. @holly_cummins #RedHat
    carbon
    awareness
    green software foundation: principles
    hardware
    efficiency
    electricity
    efficiency
    

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38. @holly_cummins #RedHat
    carbon
    awareness
    green software foundation: principles
    hardware
    efficiency
    electricity
    efficiency
    elasticity
    

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39. @holly_cummins #RedHat
    carbon
    awareness
    green software foundation: principles
    hardware
    efficiency
    electricity
    efficiency
    elasticity
    utilisation
    

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40. @holly_cummins #RedHat
    

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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
    

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42. #RedHat
    @holly_cummins
    2017 survey
    
    
    25%
    
    
    of 16,000 servers
    doing no useful work
    

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43. #RedHat
    @holly_cummins
    2017 survey
    
    
    25%
    
    
    of 16,000 servers
    doing no useful work
    “perhaps someone
    forgot to turn them off”
    

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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
    

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45. @holly_cummins
    #RedHat
    yes, turning applications off is scary
    

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46. @holly_cummins
    #RedHat
    ultimate elasticity
    
    
    

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47. @holly_cummins
    #RedHat
    ultimate elasticity
    
    
    

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48. @holly_cummins
    #RedHat
    turning it off and on again must
    ultimate elasticity
    
    
    

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49. @holly_cummins
    #RedHat
    turning it off and on again must
    • be fast
    ultimate elasticity
    
    
    

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50. @holly_cummins
    #RedHat
    turning it off and on again must
    • be fast
    • actually work
    ultimate elasticity
    
    
    

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51. @holly_cummins
    #RedHat
    turning it off and on again must
    • be fast
    • actually work
    • idempotency
    ultimate elasticity
    
    
    

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52. @holly_cummins
    #RedHat
    turning it off and on again must
    • be fast
    • actually work
    • idempotency
    • resiliency
    ultimate elasticity
    
    
    

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53. @holly_cummins
    #RedHat
    

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54. @holly_cummins
    #RedHat
    LightSwitchOps
    

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55. @holly_cummins
    #RedHat
    LightSwitchOps
    

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56. @holly_cummins #RedHat
    algorithms
    
    
    stack
    carbon
    awareness
    hardware
    efficiency
    electricity
    efficiency
    where
    
    
    when
    elasticity
    
    
    utilisation
    green software foundation: principles
    

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57. @holly_cummins
    #RedHat
    efficiency
    

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58. @holly_cummins
    #RedHat
    what programming languages
    use the least energy?
    

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59. @holly_cummins
    #RedHat
    what programming languages
    use the most energy?
    

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60. View Slide

61. energy efficiency
    of programming
    languages
    

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62. @holly_cummins
    #RedHat
    

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63. @holly_cummins
    #RedHat
    

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64. View Slide

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
    

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66. @holly_cummins
    #RedHat
    if JVM parameters can make that much difference …
    
    
    … what impact does the framework have?
    

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67. @holly_cummins #RedHat
    

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68. @holly_cummins #RedHat
    

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69. @holly_cummins #RedHat
    does being small and fast reduce carbon footprint?
    

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70. #Quarkus @holly_cummins
    measure, don’t guess.
    

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71. digression:
    
    
    measuring carbon is hard
    

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72. @holly_cummins #RedHat
    step 1: measure power usage
    

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73. @holly_cummins #RedHat
    step 1: measure power usage
    wall power measurement
    

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74. @holly_cummins #RedHat
    step 1: measure power usage
    wall power measurement
    more complete
    

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75. @holly_cummins #RedHat
    step 1: measure power usage
    wall power measurement
    more complete
    needs access to the wall
    

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76. @holly_cummins #RedHat
    step 1: measure power usage
    wall power measurement
    more complete
    needs access to the wall
    and equipment
    

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77. @holly_cummins #RedHat
    step 1: measure power usage
    wall power measurement
    more complete
    needs access to the wall
    and equipment
    and actual paper
    

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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
    

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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
    

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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
    

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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
    

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82. @holly_cummins #RedHat
    

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83. @holly_cummins #RedHat
    

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84. @holly_cummins #RedHat
    

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85. @holly_cummins #RedHat
    load
    

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86. @holly_cummins #RedHat
    Source: Teads EC2 instances carbon dataset
    

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87. @holly_cummins #RedHat
    coal wind
    step 2: convert power usage to carbon solar
    

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88. @holly_cummins #RedHat
    published energy mixes
    (these are made-up energy mixes)
    

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89. @holly_cummins #RedHat
    published energy mixes … but methodologies are not open
    (these are made-up energy mixes)
    

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90. @holly_cummins #RedHat
    published energy mixes … but methodologies are not open
    … or consistent
    (these are made-up energy mixes)
    

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91. @holly_cummins #RedHat
    step 3: embedded carbon
    (manufacturing has costs)
    

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92. @holly_cummins #RedHat
    simpler models
    

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93. @holly_cummins #RedHat
    vrrrrrooooooooom model*
    * a made-up name
    

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94. @holly_cummins
    #RedHat
    

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95. @holly_cummins
    #RedHat
    these two columns
    are almost the same
    

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96. @holly_cummins #RedHat
    energy consumption (sort of, mostly) is proportional to execution time
    

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97. @holly_cummins #RedHat
    economic model*
    

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98. @holly_cummins #RedHat
    economic model*
    * "economic input-output life cycle assessment"
    

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99. @holly_cummins #RedHat
    reducing your cloud spend
    (probably) reducing your carbon footprint*
    hardware spend
    electricity bill
    * if you keep other factors the same
    

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100. @holly_cummins #RedHat
     all models are wrong, some are useful
     

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101. so … quarkus?
     

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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
     

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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
     

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104. • quarkus cuts carbon by ~2x*
     
     
     • native has a slightly smaller carbon
     footprint
     * OOM heuristic
     density test: conclusions
     

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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)
     

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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)
     

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107. • quarkus cuts carbon by ~2-3x*
     
     
     • native consumes more carbon
     than JVM
     
     
     capacity test: conclusions
     * OOM heuristic
     

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108. @holly_cummins #RedHat
     so does quarkus reduce
     carbon emissions?
     

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109. @holly_cummins #RedHat
     so does quarkus reduce
     carbon emissions?
     

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110. @holly_cummins #RedHat
     so does quarkus reduce
     carbon emissions?
     quarkus ‘automatically’ saves
     

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111. @holly_cummins #RedHat
     so does quarkus reduce
     carbon emissions?
     quarkus ‘automatically’ saves
     • time
     

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112. @holly_cummins #RedHat
     so does quarkus reduce
     carbon emissions?
     quarkus ‘automatically’ saves
     • time
     • money
     

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113. @holly_cummins #RedHat
     so does quarkus reduce
     carbon emissions?
     quarkus ‘automatically’ saves
     • time
     • money
     • carbon (~2x)
     

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114. @holly_cummins #RedHat
     so does quarkus reduce
     carbon emissions?
     quarkus ‘automatically’ saves
     • time
     • money
     • carbon (~2x)
     

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115. @holly_cummins #RedHat
     but what about native?
     reminder
     
     
     

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116. @holly_cummins #RedHat
     but what about native?
     use case for native
     reminder
     
     
     

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117. @holly_cummins #RedHat
     but what about native?
     use case for native
     • low workload (throughput isn’t the
     bottleneck)
     reminder
     
     
     

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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
     
     
     

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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
     
     
     

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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
     
     
     

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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
     
     
     

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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
     
     
     

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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
     
     
     

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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
     
     
     

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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
     
     
     

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126. @holly_cummins #RedHat
     yes, those are the same
     optimising
     
     
     • cost
     
     
     • application performance
     
     
     will also be optimising carbon
     

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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
     

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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?
     

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129. @holly_cummins #RedHat
     elasticity
     native quarkus starts
     faster than a light bulb
     

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130. @holly_cummins #RedHat
     but.
     
     
     an app starting fast isn’t elasticity …
     
     
     …unless you also stop the app
     

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131. @holly_cummins #RedHat
     how does quarkus help reduce carbon?
     energy usage
     elasticity
     machine
     selection
     (provisioning)
     

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132. @holly_cummins #RedHat
     how does quarkus help reduce carbon?
     energy usage
     ‘free’
     
     
     direct
     
     
     easy to measure
     elasticity
     machine
     selection
     (provisioning)
     

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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)
     

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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)
     

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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)
     

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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
     

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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
     

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138. @holly_cummins #RedHat
     aaaaaaaargh?
     

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139. @holly_cummins #RedHat
     remember the vrrrrrooooooooom model?
     (probably not, it was a made-up name)
     

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140. @holly_cummins #RedHat
     we need a new mental model
     car:
     
     
     high max speed means high fuel
     usage per mile travelled
     

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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
     

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142. @holly_cummins #RedHat
     carbon
     awareness
     hardware
     efficiency
     electricity
     efficiency
     green software foundation: principles
     utility
     

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143. @holly_cummins #RedHat
     is using this carbon giving value?
     utility
     

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144. @holly_cummins #RedHat
     “no-regrets” solutions
     

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145. @holly_cummins
     #RedHat
     

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146. @holly_cummins
     #RedHat
     co-benefits
     

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147. @holly_cummins
     #RedHat
     co-benefits
     the double win
     

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148. @holly_cummins
     #RedHat
     co-benefits
     the double win
     win-win
     

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149. @holly_cummins
     #RedHat
     co-benefits
     the double win
     win-win
     win-squared
     

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150. @holly_cummins
     #RedHat
     co-benefits
     the double win
     win-win
     win-squared
     1 + 1 = 3
     

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151. @holly_cummins
     #RedHat
     co-benefits
     the double win
     win-win
     win-squared
     1 + 1 = 3
     twofer
     

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152. @holly_cummins
     #RedHat
     co-benefits
     the double win
     win-win
     win-squared
     1 + 1 = 3
     twofer
     überwinden
     

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153. @holly_cummins
     #RedHat
     co-benefits
     the double win
     win-win
     win-squared
     1 + 1 = 3
     twofer
     überwinden
     the extra win
     

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154. @holly_cummins
     #RedHat
     co-benefits
     the double win
     win-win
     win-squared
     1 + 1 = 3
     twofer
     überwinden
     the extra win
     

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155. @holly_cummins #RedHat
     climate solutions can
     make everything better
     

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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
     

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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
     

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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
     

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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
     

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160. @holly_cummins #RedHat
     the double-win
     turning things off saves a lot of money
     

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161. @holly_cummins #RedHat
     the double-win
     renewable electricity is 9x cheaper
     

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162. @holly_cummins #RedHat
     the double-win
     renewable electricity is 9x cheaper
     hosting in Montreal:
     

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163. @holly_cummins #RedHat
     the double-win
     renewable electricity is 9x cheaper
     hosting in Montreal:
     88% less carbon than the same workload in London
     

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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
     

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165. @holly_cummins #RedHat
     the double-win
     

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166. @holly_cummins #RedHat
     the double-win
     

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167. @holly_cummins #RedHat
     “this is not sacrifice. it’s advancement.”
     

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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
     

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169. slides
     thank you
     
     
     @holly_cummins@hachyderm.io
     

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