Practice green software patterns vocabulary: demand shaping, hardware efficiency, Software Carbon Intensity (SCI), and Green Software Foundation principles.
0 / 15 completed
1 / 15
The green software team implements ___ shaping: batch jobs are deferred to run when the grid is cleaner.
Demand shaping (or carbon-aware computing) means scheduling flexible workloads — batch processing, model training, backups — for times when the electricity grid has higher renewable generation and lower carbon intensity, reducing the carbon cost of the same work.
2 / 15
The Green Software Foundation promotes ___ efficiency as a core principle: get more work from the same hardware.
Hardware efficiency means maximising the utilisation of existing hardware — running at higher CPU/memory utilisation, using servers closer to end-of-life before buying new ones, and preferring software that needs fewer resources. Manufacturing hardware has high embodied carbon.
3 / 15
The team adopts the ___ CI metric to measure the carbon cost of running the software per unit of work.
SCI (Software Carbon Intensity) is a specification from the Green Software Foundation that measures the carbon emissions produced per functional unit of a software system (e.g., per API call, per user, per transaction). It enables comparison and improvement tracking.
4 / 15
The ___ Software Foundation publishes the principles and specifications for building greener software.
The Green Software Foundation (greensoftware.foundation) is a Linux Foundation project whose members include Microsoft, Google, Thoughtworks, and others. It publishes the Green Software Patterns catalog, the SCI specification, and training materials.
5 / 15
The architecture review considers the ___ emissions of new servers — the carbon already spent manufacturing the hardware.
Embodied carbon (or embedded carbon) refers to the greenhouse gas emissions generated during the manufacture, transport, and end-of-life disposal of hardware. For modern servers, embodied carbon can represent 50–80% of lifetime emissions, making hardware efficiency critical.
6 / 15
Alice (Senior Developer) comments on a PR draft: 'This lambda function is doing *a lot* of string manipulation. It's potentially creating unnecessary garbage collection cycles. Have we considered using a more efficient regex or perhaps batching these operations?' Which Green Software Pattern does Alice most likely refer to?
Alice is concerned about the impact of repeated string manipulation on resource usage. Data Batching directly addresses this by grouping operations to reduce overhead and minimize the number of times data needs to be processed. Options B, C, and D represent different strategies but don't specifically target reducing unnecessary processing or garbage collection.
7 / 15
Ben (DevOps Engineer) writes in a Slack channel: 'Just ran the new CarbonFootprint analysis on our nightly builds. The results show that our microservices architecture is contributing significantly to overall emissions due to frequent, small requests. We need to investigate opportunities for aggregation.' Which Green Software Pattern is Ben discussing?
Ben's message highlights the impact of numerous small requests on resource consumption. API Aggregation focuses on combining multiple requests into fewer, larger ones to reduce network traffic and server load – a key element in minimizing carbon emissions. The other options represent architectural patterns that could *contribute* to problems but don't directly address the core issue of inefficient request handling.
8 / 15
Charlie (Lead Architect) writes in a PR description: 'To optimize our data pipeline, we're implementing a 'warm' and 'cold' tier strategy. Data that isn't frequently accessed is offloaded to cheaper, less energy-intensive storage solutions. This aligns with the principle of minimizing compute resources.' Which Green Software Pattern does Charlie describe?
Charlie's description directly relates to Tiered Storage – strategically distributing data based on access frequency. This approach reduces the need for constant processing and storage of less frequently used data, leading to significant energy savings. Options B, C, and D represent scaling techniques that don't inherently focus on optimizing resource usage related to data storage.
9 / 15
David (Software Engineer) is presenting a new design to the team. He states: 'We're using asynchronous messaging queues for all inter-service communication, allowing services to operate independently and reducing dependencies.' Considering Green Software Patterns, what is David most likely emphasizing?
David's statement highlights the importance of Loose Coupling through asynchronous messaging. This reduces dependencies between services, allowing them to operate independently and avoid unnecessary communication overhead – a core principle for minimizing resource consumption and improving efficiency. While microservices are involved, David's focus is on the *communication* aspect.
10 / 15
Emily (Sustainability Consultant) is reviewing a proposed server deployment and notes: 'The initial design calls for provisioning servers with significant headroom – anticipating peak loads that may never materialize. This represents wasted compute capacity.' Which Green Software Pattern should Emily emphasize to the team?
Emily's observation points to the problem of over-provisioning – allocating more resources than actually needed. Right-Sizing Instances encourages matching server capacity to actual demand, reducing wasted energy and hardware costs. Options B, C, and D are scaling strategies but don't directly address the initial design choice of excessive capacity.
11 / 15
Alice (Senior Developer) comments on a PR draft: 'This lambda function is doing *a lot* of string manipulation. It's potentially creating unnecessary garbage collection cycles. Have we considered using a more efficient regex or perhaps batching these operations?' Which Green Software Pattern does Alice most likely refer to?
Alice is concerned about the impact of repeated string manipulation on resource usage. Data Batching directly addresses this by grouping operations to reduce overhead and minimize the number of times data needs to be processed. Options B, C, and D represent different strategies but don't specifically target reducing unnecessary processing or garbage collection.
12 / 15
Ben (DevOps Engineer) writes in a Slack channel: 'Just ran the new CarbonFootprint analysis on our nightly builds. The results show that our microservices architecture is contributing significantly to overall emissions due to frequent, small requests. We need to investigate opportunities for aggregation.' Which Green Software Pattern is Ben discussing?
Ben's message highlights the impact of numerous small requests on resource consumption. API Aggregation focuses on combining multiple requests into fewer, larger ones to reduce network traffic and server load – a key element in minimizing carbon emissions. The other options represent architectural patterns that could *contribute* to problems but don't directly address the core issue of inefficient request handling.
13 / 15
Charlie (Lead Architect) writes in a PR description: 'To optimize our data pipeline, we're implementing a 'warm' and 'cold' tier strategy. Data that isn't frequently accessed is offloaded to cheaper, less energy-intensive storage solutions. This aligns with the principle of minimizing compute resources.' Which Green Software Pattern does Charlie describe?
Charlie's description directly relates to Tiered Storage – strategically distributing data based on access frequency. This approach reduces the need for constant processing and storage of less frequently used data, leading to significant energy savings. Options B, C, and D represent scaling techniques that don't inherently focus on optimizing resource usage related to data storage.
14 / 15
David (Software Engineer) is presenting a new design to the team. He states: 'We're using asynchronous messaging queues for all inter-service communication, allowing services to operate independently and reducing dependencies.' Considering Green Software Patterns, what is David most likely emphasizing?
David's statement highlights the importance of Loose Coupling through asynchronous messaging. This reduces dependencies between services, allowing them to operate independently and avoid unnecessary communication overhead – a core principle for minimizing resource consumption and improving efficiency. While microservices are involved, David's focus is on the *communication* aspect.
15 / 15
Emily (Sustainability Consultant) is reviewing a proposed server deployment and notes: 'The initial design calls for provisioning servers with significant headroom – anticipating peak loads that may never materialize. This represents wasted compute capacity.' Which Green Software Pattern should Emily emphasize to the team?
Emily's observation points to the problem of over-provisioning – allocating more resources than actually needed. Right-Sizing Instances encourages matching server capacity to actual demand, reducing wasted energy and hardware costs. Options B, C, and D are scaling strategies but don't directly address the initial design choice of excessive capacity.
What will I practise in "Green Software Patterns Vocabulary"?
Practice green software patterns vocabulary: demand shaping, hardware efficiency, Software Carbon Intensity (SCI), and Green Software Foundation principles.
How many exercises are in this module?
This module has 15 multiple-choice exercises, each with instant feedback and a full explanation of the correct answer.
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Where can I find more Green IT exercises?
Browse the full Green IT hub for related drills, or check the "Next up" link below to continue with a connected topic.
How is this different from reading an article on the same topic?
Articles explain vocabulary and concepts in prose; this exercise tests and reinforces that vocabulary through active recall with immediate feedback — the two work best together.
Who writes these exercises?
Every exercise is written by the CoderSlingo team, drawing on real workplace English used in IT roles, then reviewed for accuracy and clarity.