Energy-Efficient Software Architecture in Practice

about the course

Software architecture encompasses the methods and techniques used to divide software systems in a way that ideally achieves the best balance between competing quality attributes such as maintainability, high performance, security, and uptime.

However, software architects and developers often overlook energy efficiency as a central quality attribute in their work.

Against the backdrop of the climate crisis and increased focus on secure energy supply, energy efficiency has become a factor that should be actively considered.

By optimizing software architecture and programming tasks, it is possible to reduce both the direct energy consumption and the indirect resources required for operating and maintaining systems. Energy efficiency is about getting the most work out of machines with the least possible energy use.

Considerations around green software architecture and programming can significantly reduce energy consumption, especially in organizations working with large data sets.

By implementing efficient technologies, using optimal data formats and databases, and reducing system complexity, developers can lower CPU usage and network traffic – which has a direct effect on overall power consumption. In many cases, this can lead to 10–60 % savings in total energy use, positively impacting both operational costs and an organization’s sustainability profile. An energy-efficient software solution is therefore a win for both the climate and the company’s bottom line.S

Who Is This Course For?

This course is intended for software developers, software architects, and project managers with a technical background who work with programming and software architecture.

What You Will Learn

In this course, you will gain insight into and experience with:

• Processes for working with energy efficiency in your team.
• Tactics (specific design choices) to minimize energy consumption both at the architectural and programming level.
• Tools and techniques for performing reproducible energy measurements.
• Statistical analysis to ensure your results are statistically valid.
• Hands-on experience in conducting experiments and subsequent data processing.

course format

The course combines presentations, discussions, and plenary sessions with group work (3–4 people) on concrete tasks in the Datalogi Energy Laboratory.

Practical Information

Duration: 2 days
Time: 08:30 – 16:00 each day
Format: Teaching and networking sessions

Program overview

Note: Program details are subject to change due to final planning.