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+ + \ No newline at end of file diff --git a/build/CNAME b/build/CNAME new file mode 100644 index 0000000..155241c --- /dev/null +++ b/build/CNAME @@ -0,0 +1 @@ +maturity-matrix.greensoftware.foundation diff --git a/build/assets/css/styles.6428fb43.css b/build/assets/css/styles.6428fb43.css new file mode 100644 index 0000000..ad099a1 --- /dev/null +++ b/build/assets/css/styles.6428fb43.css @@ -0,0 +1 @@ +@import url(https://fonts.googleapis.com/css2?family=Nunito+Sans&display=swap);.col,.container{padding:0 var(--ifm-spacing-horizontal);width:100%}.markdown>h2,.markdown>h3,.markdown>h4,.markdown>h5,.markdown>h6{margin-bottom:calc(var(--ifm-heading-vertical-rhythm-bottom)*var(--ifm-leading))}pre,table{overflow:auto}blockquote,pre{margin:0 0 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The green software maturity matrix is a framework for assessing the level of a tech organization\u2019s ability to handle the energy transition."}),"\n",(0,i.jsx)(t.p,{children:"The purpose of moving up the GSMM levels is not merely to be \u201cethical\u201d or good. It is a risk management strategy to provide resilience to:"}),"\n",(0,i.jsxs)(t.ul,{children:["\n",(0,i.jsx)(t.li,{children:"Tightening ESG and other (e.g. EU) reporting requirements around sustainable IT."}),"\n",(0,i.jsx)(t.li,{children:"Physical disruption to IT systems caused by climate change."}),"\n",(0,i.jsx)(t.li,{children:"Pricing changes, for example the impact of highly differential dynamic electricity tariffs or reuse, repair, and recycle rules from the EU."}),"\n",(0,i.jsx)(t.li,{children:"Hiring and retaining employees who want to be part of the solution to humanity\u2019s greatest challenge. 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Remember, this alone saved VMWare 66% on their emissions when they moved one DC in Singapore."}),"\n",(0,o.jsx)(n.li,{children:"Do a one-off right-sizing exercise on all your servers because everything tends to be overprovisioned to start with."}),"\n",(0,o.jsx)(n.li,{children:"Are you turning off your test systems in the evening and on weekends?"}),"\n",(0,o.jsx)(n.li,{children:"Because of its extreme multi-tenancy, the cloud already uses only a fraction of the electricity of an on prem DC. AWS claims to be 3.4 times more energy efficient than an average US DC and 5 times more efficient than a European one. Move some stuff there. (Note - you could also call on your non-cloud hosting providers to be more efficient. That isn\u2019t likely to pay off inside 6 months but you need to play the long game if you want to stay out of the cloud)."}),"\n",(0,o.jsx)(n.li,{children:"If you are already in the cloud, review your instance types. 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e.languages.kotlin["class-name"];var t={"interpolation-punctuation":{pattern:/^\$\{?|\}$/,alias:"punctuation"},expression:{pattern:/[\s\S]+/,inside:e.languages.kotlin}};e.languages.insertBefore("kotlin","string",{"string-literal":[{pattern:/"""(?:[^$]|\$(?:(?!\{)|\{[^{}]*\}))*?"""/,alias:"multiline",inside:{interpolation:{pattern:/\$(?:[a-z_]\w*|\{[^{}]*\})/i,inside:t},string:/[\s\S]+/}},{pattern:/"(?:[^"\\\r\n$]|\\.|\$(?:(?!\{)|\{[^{}]*\}))*"/,alias:"singleline",inside:{interpolation:{pattern:/((?:^|[^\\])(?:\\{2})*)\$(?:[a-z_]\w*|\{[^{}]*\})/i,lookbehind:!0,inside:t},string:/[\s\S]+/}}],char:{pattern:/'(?:[^'\\\r\n]|\\(?:.|u[a-fA-F0-9]{0,4}))'/,greedy:!0}}),delete e.languages.kotlin.string,e.languages.insertBefore("kotlin","keyword",{annotation:{pattern:/\B@(?:\w+:)?(?:[A-Z]\w*|\[[^\]]+\])/,alias:"builtin"}}),e.languages.insertBefore("kotlin","function",{label:{pattern:/\b\w+@|@\w+\b/,alias:"symbol"}}),e.languages.kt=e.languages.kotlin,e.languages.kts=e.languages.kotlin}(T),T.languages.c=T.languages.extend("clike",{comment:{pattern:/\/\/(?:[^\r\n\\]|\\(?:\r\n?|\n|(?![\r\n])))*|\/\*[\s\S]*?(?:\*\/|$)/,greedy:!0},string:{pattern:/"(?:\\(?:\r\n|[\s\S])|[^"\\\r\n])*"/,greedy:!0},"class-name":{pattern:/(\b(?:enum|struct)\s+(?:__attribute__\s*\(\([\s\S]*?\)\)\s*)?)\w+|\b[a-z]\w*_t\b/,lookbehind:!0},keyword:/\b(?:_Alignas|_Alignof|_Atomic|_Bool|_Complex|_Generic|_Imaginary|_Noreturn|_Static_assert|_Thread_local|__attribute__|asm|auto|break|case|char|const|continue|default|do|double|else|enum|extern|float|for|goto|if|inline|int|long|register|return|short|signed|sizeof|static|struct|switch|typedef|typeof|union|unsigned|void|volatile|while)\b/,function:/\b[a-z_]\w*(?=\s*\()/i,number:/(?:\b0x(?:[\da-f]+(?:\.[\da-f]*)?|\.[\da-f]+)(?:p[+-]?\d+)?|(?:\b\d+(?:\.\d*)?|\B\.\d+)(?:e[+-]?\d+)?)[ful]{0,4}/i,operator:/>>=?|<<=?|->|([-+&|:])\1|[?:~]|[-+*/%&|^!=<>]=?/}),T.languages.insertBefore("c","string",{char:{pattern:/'(?:\\(?:\r\n|[\s\S])|[^'\\\r\n]){0,32}'/,greedy:!0}}),T.languages.insertBefore("c","string",{macro:{pattern:/(^[\t 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T.languages.c.boolean,T.languages.objectivec=T.languages.extend("c",{string:{pattern:/@?"(?:\\(?:\r\n|[\s\S])|[^"\\\r\n])*"/,greedy:!0},keyword:/\b(?:asm|auto|break|case|char|const|continue|default|do|double|else|enum|extern|float|for|goto|if|in|inline|int|long|register|return|self|short|signed|sizeof|static|struct|super|switch|typedef|typeof|union|unsigned|void|volatile|while)\b|(?:@interface|@end|@implementation|@protocol|@class|@public|@protected|@private|@property|@try|@catch|@finally|@throw|@synthesize|@dynamic|@selector)\b/,operator:/-[->]?|\+\+?|!=?|<<?=?|>>?=?|==?|&&?|\|\|?|[~^%?*\/@]/}),delete T.languages.objectivec["class-name"],T.languages.objc=T.languages.objectivec,T.languages.reason=T.languages.extend("clike",{string:{pattern:/"(?:\\(?:\r\n|[\s\S])|[^\\\r\n"])*"/,greedy:!0},"class-name":/\b[A-Z]\w*/,keyword:/\b(?:and|as|assert|begin|class|constraint|do|done|downto|else|end|exception|external|for|fun|function|functor|if|in|include|inherit|initializer|lazy|let|method|module|mutable|new|nonrec|object|of|open|or|private|rec|sig|struct|switch|then|to|try|type|val|virtual|when|while|with)\b/,operator:/\.{3}|:[:=]|\|>|->|=(?:==?|>)?|<=?|>=?|[|^?'#!~`]|[+\-*\/]\.?|\b(?:asr|land|lor|lsl|lsr|lxor|mod)\b/}),T.languages.insertBefore("reason","class-name",{char:{pattern:/'(?:\\x[\da-f]{2}|\\o[0-3][0-7][0-7]|\\\d{3}|\\.|[^'\\\r\n])'/,greedy:!0},constructor:/\b[A-Z]\w*\b(?!\s*\.)/,label:{pattern:/\b[a-z]\w*(?=::)/,alias:"symbol"}}),delete T.languages.reason.function,function(e){for(var t=/\/\*(?:[^*/]|\*(?!\/)|\/(?!\*)|<self>)*\*\//.source,n=0;n<2;n++)t=t.replace(/<self>/g,(function(){return 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T.languages.go["class-name"],function(e){var t=/\b(?:alignas|alignof|asm|auto|bool|break|case|catch|char|char16_t|char32_t|char8_t|class|co_await|co_return|co_yield|compl|concept|const|const_cast|consteval|constexpr|constinit|continue|decltype|default|delete|do|double|dynamic_cast|else|enum|explicit|export|extern|final|float|for|friend|goto|if|import|inline|int|int16_t|int32_t|int64_t|int8_t|long|module|mutable|namespace|new|noexcept|nullptr|operator|override|private|protected|public|register|reinterpret_cast|requires|return|short|signed|sizeof|static|static_assert|static_cast|struct|switch|template|this|thread_local|throw|try|typedef|typeid|typename|uint16_t|uint32_t|uint64_t|uint8_t|union|unsigned|using|virtual|void|volatile|wchar_t|while)\b/,n=/\b(?!<keyword>)\w+(?:\s*\.\s*\w+)*\b/.source.replace(/<keyword>/g,(function(){return t.source}));e.languages.cpp=e.languages.extend("c",{"class-name":[{pattern:RegExp(/(\b(?:class|concept|enum|struct|typename)\s+)(?!<keyword>)\w+/.source.replace(/<keyword>/g,(function(){return t.source}))),lookbehind:!0},/\b[A-Z]\w*(?=\s*::\s*\w+\s*\()/,/\b[A-Z_]\w*(?=\s*::\s*~\w+\s*\()/i,/\b\w+(?=\s*<(?:[^<>]|<(?:[^<>]|<[^<>]*>)*>)*>\s*::\s*\w+\s*\()/],keyword:t,number:{pattern:/(?:\b0b[01']+|\b0x(?:[\da-f']+(?:\.[\da-f']*)?|\.[\da-f']+)(?:p[+-]?[\d']+)?|(?:\b[\d']+(?:\.[\d']*)?|\B\.[\d']+)(?:e[+-]?[\d']+)?)[ful]{0,4}/i,greedy:!0},operator:/>>=?|<<=?|->|--|\+\+|&&|\|\||[?:~]|<=>|[-+*/%&|^!=<>]=?|\b(?:and|and_eq|bitand|bitor|not|not_eq|or|or_eq|xor|xor_eq)\b/,boolean:/\b(?:false|true)\b/}),e.languages.insertBefore("cpp","string",{module:{pattern:RegExp(/(\b(?:import|module)\s+)/.source+"(?:"+/"(?:\\(?:\r\n|[\s\S])|[^"\\\r\n])*"|<[^<>\r\n]*>/.source+"|"+/<mod-name>(?:\s*:\s*<mod-name>)?|:\s*<mod-name>/.source.replace(/<mod-name>/g,(function(){return n}))+")"),lookbehind:!0,greedy:!0,inside:{string:/^[<"][\s\S]+/,operator:/:/,punctuation:/\./}},"raw-string":{pattern:/R"([^()\\ 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A Green Software Maturity Matrix

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What does this mean in a green software context for an organization? Let’s be realistic. Almost all enterprises are at level 1 right now. Going green is the most difficult project our industry faces.

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Green Software Maturity Matrix!

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Level 1 - Aspiring

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You have individuals in your organization who care about green targets for technology but no systemic interest, processes or commitments. Some development teams measure their carbon emissions. This is where almost all of us are today.

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Level 2 - Aware

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You know your organization’s scope 1 and 2 emissions. You have a few projects driving greenness within your organization and beyond it using this data (by putting pressure on suppliers, for example). Your engineers have had some training in green systems, operations and patterns.

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Level 3 - Acting

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You know your scope 1, 2 and 3 emissions on a daily, weekly, monthly or annual basis. You have been acting on reducing the scope 1 and 2 emissions for a while and your carbon footprint is going down per some consistent, org-specific unit of output, e.g per order. You have defined processes for every team including regular reporting and reviewing of CO2 equivalent emissions for all IT related operations. Your PM teams have a remit to avoid waste, for example saving no more data than is necessary or implementing any functionality before need, and you can switch off zombie or low use services immediately (“Lightswitch Ops”). You have automatic resilience to weather-related operational risks (e.g. DC outages). You are aware of and discuss the tradeoffs between embodied carbon and carbon generated by energy usage. You have plans in place to minimize your embodied carbon footprint, including significantly extending the life expectancy of both the servers and end user devices you run on.

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Level 4 - Awesome

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You have a measurement system in place that is producing good real-time scope 1, 2, and 3 data and although it’s not currently driving the business day-to-day, the business is very aware of it. Using the more limited scope 1, 2, and 3 data you have had for a while, you have already achieved net carbon zero using no more than 10% offsets. (Note offsets are highly problematic but they demonstrate you are regularly measuring). You perform demand shaping; pre-calculation and caching; and time and location shifting, for example, to adapt your workloads to current conditions. You automatically delete or archive data that isn’t in regular use. Services no longer in use are automatically turned off and rightsizing happens automatically (i.e. you apply SRE principles). Your applications are Lean and you constantly review and retire functionality that is insufficiently used. Your organizational strategy has been aligned with being green as a business goal - perhaps for reasons of ESG, cost, resilience, or market access to the EU - and delivery on CO2 targets is regularly discussed and reported at senior level. Your total carbon footprint is going down even as you grow. You are also actively driving the carbon footprint of your suppliers to go down. You never cause hardware less than ten years old to become end of life either by lack of security patches or lack of backwards compatibility in your applications. You are actively driving the carbon footprint of your customers to go down (beyond simply their use of your services and devices) for example by providing scope 3 reporting for your goods and services. Examples (for some of it): Google, AWS, MS.

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Level 5 - Inspiring

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You’ve got there. You have achieved 24/7 CFE and require no more than 1% offsets to handle hard to shift embodied carbon. You have team level measurable goals (OKRs etc) for your CO2 measurements. You are optimizing for minimal CO2 emissions using your dynamic, real-time data. You and the services you rely on use real-time information including dynamic grid energy data to make rapid, quantitative decisions that allow you to be greener. This could (and probably will) be via a service you use rather than something you built yourself. You are already an SRE-aware organization that thinks in terms of error budgets for outages and downtime and you now think about carbon budgets in the same way. Using predictions based on factors such as weather and grid congestion, you change and move almost all of your workloads ahead of time to match your electricity requirements to local green power availability (aka 24/7 CFE) and any time sensitive workloads are highly optimized for minimal electricity use. You never cause hardware to become end of life either by lack of security patches or lack of backwards compatibility. You are ready for the energy transition and won’t be caught by surprise by sudden new rules or constraints.

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Axes (Matrix Rows)

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  • Whole organization energy commitments
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  • Carbon footprint
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  • CO2 equivalent metrics
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  • Server resource management
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  • Energy resource management
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  • Minimize end user device embodied carbon waste (assume circular economy)
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  • Minimize server hardware embodied carbon waste
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  • Product management
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  • Education
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Scope

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  • Small business: Maturity matrix per company
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  • Small and Midsize Enterprise (SME): Maturity matrix per company
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  • Larger organization: Maturity matrix per business unit rather than per company
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+ + \ No newline at end of file diff --git a/build/gsmm/level-1/index.html b/build/gsmm/level-1/index.html new file mode 100644 index 0000000..3da998d --- /dev/null +++ b/build/gsmm/level-1/index.html @@ -0,0 +1,15 @@ + + + + + +Level 1 - Aspiring | Green Software Maturity Matrix + + + + +
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Level 1 - Aspiring

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You have individuals in your organization who care about green targets for technology but no systemic interest, processes or commitments. Some development teams measure their carbon emissions. This is where almost all of us are today.

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AxisState
Whole organization energy commitmentsnone/CZero by 2050
Carbon footprintyou don’t know what it is
CO2 equivalent metricsNo metrics
Server resource managementNo rightsizing takes place and zero knowledge about unused ”zombie” systems
Energy resource managementNone - running on demand
Minimize end user device embodied carbon waste (assume circular economy)No end user device longevity targets
Minimize server hardware embodied carbon wasteNo server utilization targets
Product managementNot carbon aware
EducationNone/ad-hoc, individual
+ + \ No newline at end of file diff --git a/build/gsmm/level-2/index.html b/build/gsmm/level-2/index.html new file mode 100644 index 0000000..d8be865 --- /dev/null +++ b/build/gsmm/level-2/index.html @@ -0,0 +1,15 @@ + + + + + +Level 2 - Aware | Green Software Maturity Matrix + + + + +
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Level 2 - Aware

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You know your organization’s scope 1 and 2 emissions. You have a few projects driving greenness within your organization and beyond it using this data (by putting pressure on suppliers, for example). Your engineers have had some training in green systems, operations and patterns.

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AxisState
Whole organization energy commitmentsCZero for scope 1, 2 and 3 by 2040 (note you may already be so-called “Carbon neutral”)
Carbon footprintyou know what it is (scope 1 and 2)
CO2 equivalent metricsannual, quarterly or monthly numbers from all suppliers (including outsourcers) and own systems for scope 1/2
Server resource managementoccasional spring cleans where you manually turn off idle or low value systems and delete/archive unneeded data
Energy resource managementhosting in green regions/buying renewable energy
Minimize end user device embodied carbon waste (assume circular economy)some adhoc targets in place
Minimize server hardware embodied carbon wastesome adhoc systems and some systems using multi-tenancy to improve utilization
Product managementcarbon awareness part of product design
Educationbasic training for all engineers & PMs. Champions are trained
+ + \ No newline at end of file diff --git a/build/gsmm/level-3/index.html b/build/gsmm/level-3/index.html new file mode 100644 index 0000000..1397541 --- /dev/null +++ b/build/gsmm/level-3/index.html @@ -0,0 +1,15 @@ + + + + + +Level 3 - Acting | Green Software Maturity Matrix + + + + +
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Level 3 - Acting

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You know your scope 1, 2 and 3 emissions on a daily, weekly, monthly or annual basis. You have been acting on reducing the scope 1 and 2 emissions for a while and your carbon footprint is going down per some consistent, org-specific unit of output, e.g per order. You have defined processes for every team including regular reporting and reviewing of CO2 equivalent emissions for all IT related operations. Your PM teams have a remit to avoid waste, for example saving no more data than is necessary or implementing any functionality before need, and you can switch off zombie or low use services immediately (“Lightswitch Ops”). You have automatic resilience to weather-related operational risks (e.g. DC outages). You are aware of and discuss the tradeoffs between embodied carbon and carbon generated by energy usage. You have plans in place to minimize your embodied carbon footprint, including significantly extending the life expectancy of both the servers and end user devices you run on.

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AxisState
Whole organization energy commitmentsalready net CZero with offsets
Carbon footprintyou know what it is (scope 1, 2 and 3) and it is reducing per unit of output, e.g. orders
CO2 equivalent metricsdaily numbers from all suppliers and own systems for scope 1/2/3 and embodied carbon
Server resource managementall systems can be safely switched off (aka Lightswitch Ops) and there are processes for doing so. You have knowledge of what is running on all your machines and there are no zombie services. You save no unnecessary data and it is maintained in the optimal medium (e.g. tape if the data is not required for real time queries)
Energy resource managementat least part of your systems are dynamically managed based on green electricity availability (either via direct orchestration or through a cloud service)
Minimize end user device embodied carbon waste (assume circular economy)defined processes in place that ensure ten year old hardware is supported by your software for most commonly used devices (90%+)
Minimize server hardware embodied carbon wastedefined utilization targets. All systems use some form of multi-tenancy. Servers all have a 5 year life expectancy
Product managementall new product design supports demand shifting/shaping and Lean concepts are followed. End user devices prompt for green/off peak charging. No more data is saved than necessary
Educationadvanced training for all engineers & PMs
+ + \ No newline at end of file diff --git a/build/gsmm/level-4/index.html b/build/gsmm/level-4/index.html new file mode 100644 index 0000000..a30c83d --- /dev/null +++ b/build/gsmm/level-4/index.html @@ -0,0 +1,15 @@ + + + + + +Level 4 - Awesome | Green Software Maturity Matrix + + + + +
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Level 4 - Awesome

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You have a measurement system in place that is producing good real-time scope 1, 2, and 3 data and although it’s not currently driving the business day-to-day, the business is very aware of it. Using the more limited scope 1, 2, and 3 data you have had for a while, you have already achieved net carbon zero using no more than 10% offsets. (Note offsets are highly problematic but they demonstrate you are regularly measuring). You perform demand shaping; pre-calculation and caching; and time and location shifting, for example, to adapt your workloads to current conditions. You automatically delete or archive data that isn’t in regular use. Services no longer in use are automatically turned off and rightsizing happens automatically (i.e. you apply SRE principles). Your applications are Lean and you constantly review and retire functionality that is insufficiently used. Your organizational strategy has been aligned with being green as a business goal - perhaps for reasons of ESG, cost, resilience, or market access to the EU - and delivery on CO2 targets is regularly discussed and reported at senior level. Your total carbon footprint is going down even as you grow. You are also actively driving the carbon footprint of your suppliers to go down. You never cause hardware less than ten years old to become end of life either by lack of security patches or lack of backwards compatibility in your applications. You are actively driving the carbon footprint of your customers to go down (beyond simply their use of your services and devices) for example by providing scope 3 reporting for your goods and services. Examples (for some of it): Google, AWS, MS.

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AxisState
Whole organization energy commitmentsalready net CZero with no more than 10% offsets
Carbon footprintit is reducing full stop and so is that of your suppliers
CO2 equivalent metricsReal time through easy standardized APIs together with projections
Server resource managementall turning off and rightsizing happens automatically and data that is not regularly accessed is automatically deleted or archived
Energy resource managementall your systems support demand shifting and shaping based on energy data
Minimize end user device embodied carbon waste (assume circular economy)automated processes ensure ten year old hardware is supported by your software for all devices
Minimize server hardware embodied carbon wasteoptimal utilization achieved for every server using automated orchestration. Servers all have a 10 year life expectancy
Product managementcarbon emissions are tracked per feature. Feature use is monitored and low use/poor carbon ROI features retired
Educationonly basic training needed - everything is green by default
+ + \ No newline at end of file diff --git a/build/gsmm/level-5/index.html b/build/gsmm/level-5/index.html new file mode 100644 index 0000000..f6daca6 --- /dev/null +++ b/build/gsmm/level-5/index.html @@ -0,0 +1,15 @@ + + + + + +Level 5 - Inspiring | Green Software Maturity Matrix + + + + +
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Level 5 - Inspiring

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You’ve got there. You have achieved 24/7 CFE and require no more than 1% offsets to handle hard to shift embodied carbon. You have team level measurable goals (OKRs etc) for your CO2 measurements. You are optimizing for minimal CO2 emissions using your dynamic, real-time data. You and the services you rely on use real-time information including dynamic grid energy data to make rapid, quantitative decisions that allow you to be greener. This could (and probably will) be via a service you use rather than something you built yourself. You are already an SRE-aware organization that thinks in terms of error budgets for outages and downtime and you now think about carbon budgets in the same way. Using predictions based on factors such as weather and grid congestion, you change and move almost all of your workloads ahead of time to match your electricity requirements to local green power availability (aka 24/7 CFE) and any time sensitive workloads are highly optimized for minimal electricity use. You never cause hardware to become end of life either by lack of security patches or lack of backwards compatibility. You are ready for the energy transition and won’t be caught by surprise by sudden new rules or constraints.

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AxisState
Whole organization energy commitmentsalready 24/7 CFE with no more than 1% offsets, monitored by a tight carbon error budget
Carbon footprintit is as close to zero as achievable
CO2 equivalent metricsReal time through easy standardized APIs together with projections
Server resource managementyou have a rigorous carbon error budget including your scope 3 embodied carbon and all your resource use is tracked and managed through it
Energy resource managementyou run 24/7 CFE with a rigorous carbon error budget
Minimize end user device embodied carbon waste (assume circular economy)automated processes ensure backwards compatibility and security patches for all devices (software never kills a working device). Devices last forever al la Theseus’ ship/George Washington’s axe/Trigger’s broom
Minimize server hardware embodied carbon wastehardware use is minimized by using full grid-aware integration with end user devices including phones, laptops, smart clothing, fridges…
Product managementyour features are tracked against your scope 1/2/3 carbon error budget
Educationyou train others in what you have achieved
+ + \ No newline at end of file diff --git a/build/history/index.html b/build/history/index.html new file mode 100644 index 0000000..37b06ad --- /dev/null +++ b/build/history/index.html @@ -0,0 +1,39 @@ + + + + + +What is a Maturity Matrix? | Green Software Maturity Matrix + + + + +
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What is a Maturity Matrix?

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Maturity matrices are used in fields like project management and cybersecurity to help organizations grok where they currently stand in terms of best practices, as well as the steps they can take to achieve higher levels of performance. The green software maturity matrix is a framework for assessing the level of a tech organization’s ability to handle the energy transition.

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The purpose of moving up the GSMM levels is not merely to be “ethical” or good. It is a risk management strategy to provide resilience to:

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  • Tightening ESG and other (e.g. EU) reporting requirements around sustainable IT.
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  • Physical disruption to IT systems caused by climate change.
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  • Pricing changes, for example the impact of highly differential dynamic electricity tariffs or reuse, repair, and recycle rules from the EU.
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  • Hiring and retaining employees who want to be part of the solution to humanity’s greatest challenge. This is particularly true for younger staff.
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The history of maturity matrices

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The Capability Maturity Model Integration (CMMI), which is a bit of a mouthful, was originally developed by the Software Engineering Institute (SEI) at Carnegie Mellon University. The CMMI is a framework for assessing and guiding organizations' process improvement efforts, and has 5 maturity levels:

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[[PLACEHOLDER FOR CMMI IMAGE]]

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  • Level 1 - Initial: Processes are unpredictable, poorly controlled, and reactive at best.
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  • Level 2 - Reactively managed: Per-project processes. Often still reactive.
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  • Level 3 - Defined: Processes are standardized, documented, well understood and reviewed.
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  • Level 4 - Quantitatively Managed: Processes are measured and controlled.
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  • Level 5 - Optimizing: Continuous improvement occurs based on quantitative feedback.
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We reckon this broadly means:

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  • Level 1: You are floundering. No organization level strategy. Maybe a few individuals who care and/or are knowledgeable. Purely reactive. This is where most of us are on being green at this point.
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  • Level 2: You are starting to get some handle on it but without consistency. Mostly reactive. How advanced you are varies by project and team. You have the bare minimum of data.
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  • Level 3: You are good. You have decent, basic org-wide green tech knowledge and data. You have defined processes for handling that data that are applied across your organization.
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  • Level 4: You are awesome. You can measure your progress dynamically (i.e. you have real -time data).
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  • Level 5: You have ascended to the next plane of existence. You monitor and improve based on your real-time data. You give aspirational talks at tech conferences and what people are aspiring to is what you have been doing for ages. You are the tech equivalent of a being of pure energy. Think Yoda with a keyboard.
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Green Software Maturity Matrix

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Executive Summary

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The Green Software Maturity Matrix (GSMM) is a self-assessment tool. It helps organizations understand the extent to which they have implemented green principles, patterns, and processes for building and operating their software systems. The purpose is to “raise the floor and the ceiling.” I.e. to lift the behavior of the laggards on sustainable strategy and inspire those doing well to achieve more by showing what the leaders in this area are aiming for.

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The Green Software Maturity Matrix is a project run through the Community Working Group in the Green Software Foundation.

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Solutions

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Start to list tools that are available that can help get to each level

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Level 1 > 2

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Challenge - cut your resource use by 50%:

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  • Identify and switch off those zombie servers that aren’t doing anything (or anything much). Remember, this alone saved VMWare 66% on their emissions when they moved one DC in Singapore.
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  • Do a one-off right-sizing exercise on all your servers because everything tends to be overprovisioned to start with.
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  • Are you turning off your test systems in the evening and on weekends?
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  • Because of its extreme multi-tenancy, the cloud already uses only a fraction of the electricity of an on prem DC. AWS claims to be 3.4 times more energy efficient than an average US DC and 5 times more efficient than a European one. Move some stuff there. (Note - you could also call on your non-cloud hosting providers to be more efficient. That isn’t likely to pay off inside 6 months but you need to play the long game if you want to stay out of the cloud).
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  • If you are already in the cloud, review your instance types. Could you be using Burstable instances or autoscaling?
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Pini Reznik of GreenOps consultancy re:cinq told us that, in his experience, "An average cloud system can cut its resource consumption by up to 50% just using ops best practice tuning and optimization." This is relatively straightforward stuff.

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You can measure the scale of cut you’ve achieved by the reduction in your like-for-like hosting bills. Hosting cost is only a rough proxy for emissions but it’s good enough at this stage and it’s simple to explain and track. No clever tools required!

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Hurray! You’ve saved loads of money and you are now working on level 2 of the maturity matrix.

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Level 2 > 3

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Challenge - cut your resource use by another 30%:

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  • Make sure your hosting provider or operations team has extremely tough carbon zero hosting targets. Compare them with the cloud and pile on some pressure.
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  • Ensure machines are hosted on grids and in regions with a high renewable or nuclear mix (AWS currently has 19 100% renewable regions, for example).
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  • Choose only green platforms that are committed to a low carbon future and have a community that will hold them to that commitment. Move to those platforms if necessary.
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  • Choose an architecture that will support demand shifting and shaping (i.e. usually not on demand monoliths).
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  • Set high bars for operational efficiency and machine utilization because the best way to both cut emissions and embodied carbon is to use fewer servers. The public clouds are comparatively very efficient. Again, that is because of scale and incentives rather than saintliness. We don’t care. In most cases we can cut our emissions very significantly by moving to a public cloud and using its services well (‘lift and shift’ buys you something but you can move beyond it).
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  • Design products and systems to support demand shaping and shifting for carbon awareness.
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  • Do less and be LEAN in approach. Don’t build and save stuff before need.
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  • Make sure your software is never the final nail in the coffin for working end user devices because of the lack of backwards compatibility or security patches.
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  • Build basic performance metrics into your systems and do at least basic performance analysis. Resolve any egregious bottlenecks that you find (and you will). They are just bugs that are slowing you down, costing you money and emitting greenhouse gasses. Performance is often a good proxy for carbon emissions.
  • +
  • Start to automate the right-sizing you did at level 1 and look at LightswitchOps so you can turn off systems at will if you think they are no longer used. You’ll need some simple metrics for that too so you can spot low activity servers.
  • +
  • For code that has to run on demand, make it efficient.
  • +
+

Level 3 > 4

+
    +
  • You analyze cloud builds e.g. cloud carbon footprint tool.
  • +
+

Level 4 > 5

+

Level 5

+ + \ No newline at end of file diff --git a/src/css/custom.css b/src/css/custom.css index 0a802de..c7e84c6 100644 --- a/src/css/custom.css +++ b/src/css/custom.css @@ -23,6 +23,12 @@ --docusaurus-highlighted-code-line-bg: rgba(0, 0, 0, 0.1); } +@media (min-width: 997px) { + :root #__docusaurus { + --docusaurus-announcement-bar-height: auto; + } +} + /* For readability concerns, you should choose a lighter palette in dark mode. */ [data-theme="dark"] { --ifm-color-primary: #25c2a0;