Green coding – energy reduced software development
Green coding, often referred to as "sustainable programming", seeks to minimize the energy usage associated with software development. This initiative emphasizes key aspects such as software architecture, software components, and the underlying operating platform. The goal of reducing energy consumption is regarded as a non-functional requirement, similar to considerations of performance, efficiency, and security.
“Each line of code carries the potential to minimize energy usage”
The principles of green coding should be considered from the design stage. During the documentation of functional and technical specifications, designers and developers can, for instance, evaluate the necessity of dynamic reloading in a web application. They also assess whether all data processing needs to occur in real time. Additional technical strategies, such as decreasing server requests, choosing energy-efficient algorithms, and implementing caching or compression techniques, can further enhance energy efficiency. The implementation of database indexes and an optimized software configuration for uninterrupted operation – such as appropriately set log levels and optimized database settings – contributes to a decrease in energy usage.
During the implementation phase, it is crucial to establish quantifiable metrics for energy consumption and to monitor these metrics throughout the process.
For instance, energy consumption can be assessed using the jPowerMonitor developed by msg, which tracks the active functions and their CPU time utilization within running Java applications.
Green operating platform
When utilizing the software, green coding prioritizes the reduction of CO2 emissions through energy-efficient data processing. Operating in the cloud is generally more advantageous compared to traditional company-owned data centers: This is due to the fact that virtual servers are activated only when necessary, leading to greater energy efficiency and, consequently, lower CO2 emissions. It is essential for local servers to be sized according to the actual workload they handle. Additionally, the secondary utilization of waste heat is becoming increasingly significant.
The rise of artificial intelligence and digitalization is driving up the demand for both computing power and electricity. As a result, software operators are increasingly considering the use of renewable energy sources when selecting data centers, opting for green data centers whenever feasible.
To maximize the benefits of surplus energy periods in the supply grid, IT developers and software users can configure the timing of their calculations. “When combined with stationary NaION or LFP power storage systems, data centers can function as grid-friendly consumers.. This principle also applies to processing on end devices.” emphasizes Thorben Schulte.
Consequently, the optimizations achieved through green coding have a direct effect on the calculation of a company's CO2 emissions, particularly in relation to scope 2 and scope 3 emissions.
The automotive sector is particularly relevant in discussions surrounding green coding
The opportunities presented by green coding are especially significant within this industry.
- The ongoing digital transformation of private transportation is resulting in an increase in both data and processing volumes.
- Adhering to the notion that "each line of code carries the potential to minimize energy usage", effective optimization strategies can yield significant reductions in energy usage and system resources. This is particularly relevant in the domains of telemetry and autonomous driving, whether or not backend support is utilized, as well as for any vehicle's backend connectivity.
- When processing occurs "on edge", meaning within the vehicle itself, it can lead to substantial power demands, potentially affecting the range of fully electric vehicles. In such scenarios, implementing optimization techniques based on green coding can enhance the vehicle's range.
- Furthermore, the efficient and judicious use of transmission bandwidth constitutes another essential aspect of green coding. "Beyond mere data processing, mobile transmission also contributes to energy consumption. It is crucial to eliminate redundancies and adopt strategies such as information bundling or the selection of appropriate transmission windows." summarizes Thorben Schulte.
Further developments
In light of legal requirements across the European Union, the significance of sustainability and the demonstration of sustainable practices are poised to increase in the future. These requirements will progressively become more defined, simultaneously presenting numerous opportunities for specialist departments, IT architecture, development, and operations to contribute meaningfully to climate protection initiatives. This checklist serves as a resource for those in charge, outlining essential tasks related to green coding:
- Non-functional requirements for green IT and green coding have been established
- IT architects and developers have received appropriate training
- Systems are designed to scale dynamically and to power down during periods of inactivity
- The use of dynamic content and real-time processing is minimized whenever feasible
- The following points incorporate principles of green coding and development patterns:
- Efficient code with optimized algorithms
- Prevention of unnecessary round trips
- Caching
- Optimized data volume
- Compressed network communication
- Database indexes
- Optimized use of resources through optimized configuration
- Zero waste code
- Principle: "Each line of code carries the potential to minimize energy usage"
- Components that consume the most energy are identified
- Performance engineering: It is clear what is measured, when and how
- What: Complete system, process, component, method
- When: Unit test, integration test, operation
- How: Open hardware monitor or smart plugs, frameworks
- Resource consumption: Optimization of CPU, RAM, memory, network
- DevOps and operation
- DevOps pipeline is optimized to improve energy consumption
- Container-based platform featuring intelligent and dynamic scaling is used
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