The Principles of Sustainable Software Engineering Microsoft Quiz Answers

Get The Principles of Sustainable Software Engineering Microsoft Quiz Answers

Sustainable Software Engineering is an emerging discipline at the intersection of climate science, software, hardware, electricity markets, and data center design. The Principles of Sustainable Software Engineering are a core set of competencies needed to define, build, and run sustainable software applications.

In this module, you will:

  • Identify the eight principles of Sustainable Software Engineering
  • Understand the two philosophies of Sustainable Software Engineering

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Knowledge Check

Q1. Which of the following options lists the eight principles of Sustainable Software Engineering?

  • Carbon, Alternative Energy, Carbon Intensity, Embodied Carbon, Energy Proportionality, Networking, Datacenter Scaling, Optimization
  • Carbon, Electricity, Carbon Intensity, Embodied Carbon, Energy Proportionality, Networking, Demand Shaping, Optimization
  • Carbon, Electricity, Carbon Intensity, Embedded Carbon, Energy Proficiency, Networking, Demand Shaping, Optimization

Q2. The eight principles are independent of which software elements:

  • Active directory domain, Organization size or type, Cloud vendor or self-hosted, Programming language or framework
  • Application domain, Optimization scale or tenant, Cloud vendor or self-hosted, Programming language or framework
  • Application domain, Organization size or type, Cloud vendor or self-hosted, Programming language or framework

Q3. True or False: to be carbon-efficient is to minimize the amount of carbon emitted per unit of work.

  • True
  • False

Q4. What is the single most significant cause of carbon emissions?

  • Agriculture
  • Industry
  • Energy supply
  • Waste management
  • International aviation

Q5. True or False: reducing the amount of electricity consumed in your application can decrease the carbon intensity of the local grids energy mix.

  • True
  • False
Conclusion:

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This Problem is intended for audiences of all experiences who are interested in learning about Data Science in a business context; there are no prerequisites.

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