How environmentally friendly organizations can use green coding to drive long-term success.
Twenty years ago, coding had boundaries. Bandwidth restrictions and limited processing power forced developers to always be mindful of the length and complexity of their code. But as technology enabled greater innovation, programmers were no longer constrained by size.
For example, greater computing power allowed faster processing of large files and applications. Open-source libraries and frameworks allowed software engineers to reuse pieces of code in their projects, creating greater possibilities. This also led to programs with more lines of code—and more processing power required to parse it. The unintended consequence was greater energy usage and a higher global electricity demand.
As companies look to transform business and implement more sustainable practices, they’re digging deep into established processes to find new efficiencies. This includes evaluating the building blocks of their business operations, from storing data more efficiently to examining how code is written.
In this post, we’ll explore how green coding helps organizations find innovative ways to prioritize sustainability and reach their energy reduction goals.
What is green coding?
Green coding is an environmentally sustainable computing practice that seeks to minimize the energy involved in processing lines of code and, in turn, help organizations reduce overall energy consumption. Many organizations have set greenhouse emission reduction goals to respond to the climate change crisis and global regulations; green coding is one way to support these sustainability goals.
Green coding is a segment of green computing, a practice that seeks to limit technology’s environmental impact, including reducing the carbon footprint in high-intensity operations, such as in manufacturing lines, data centers and even the day-to-day operations of business teams. This larger green computing umbrella also includes green software—applications that have been built using green coding practices.
Advances in technology—from big data to data mining—have contributed to a massive increase in energy consumption in the information and communications technology sector. According to the Association for Computing Machinery, annual energy consumption at data centers has doubled over the past decade. Today, computing and IT are responsible for between 1.8% and 3.9% of global greenhouse gas emissions.
The high energy consumption of computing
To fully understand how green coding can reduce energy consumption and greenhouse gas emissions, it helps to dive into the energy consumption of software:
- Infrastructure: The physical hardware, networks and other elements of an IT infrastructure all require energy to run. Within any organization, there are likely areas where the computing infrastructure is overly complicated or overprovisioned, which results in inefficient energy use.
- Processing: Software consumes energy as it runs. The more complicated the software or the larger the file, the more processing time it takes and the more energy it consumes.
- DevOps: In the typical coding process, developers write lines of code, which are parsed and processed through a device. The device requires energy, which unless powered by 100% renewable energy, creates carbon emissions. The more code to process, the more energy the device consumes and the higher the level of emissions.
Recent research into the speed and energy use of different programming languages found that C was the most efficient in speed, reducing energy and memory usage and providing another potential opportunity for energy savings. However, there is still some debate in terms of how this is realized and which metrics should be used to evaluate energy savings.
Writing more sustainable software
Green coding begins with the same principles that are used in traditional coding. To reduce the amount of energy needed to process code, developers can adopt less energy-intensive coding principles into their DevOps lifecycle.
The “lean coding” approach focuses on using the minimal amount of processing needed to deliver a final application. For example, website developers can prioritize reducing file size (e.g., switching high-quality media with smaller files). This not only accelerates website load times, but also improves the user experience.
Lean coding also aims to reduce code bloat, a term used to refer to unnecessarily long or slow code that is wasteful of resources. Open-source code can be a contributing factor to this software bloat. Because open-source code is designed to serve a wide range of applications, it contains a significant amount of code that goes unutilized for the specific software. For example, a developer may pull an entire library into an image, yet only need a fraction of the functionality. This redundant code uses additional processing power and leads to excess carbon emissions.
By adopting lean coding practices, developers are more likely to design code that uses the minimal amount of processing, while still delivering desired results.
Implementing green coding
The principles of green coding are typically designed to complement existing IT sustainability standards and practices used throughout the organization. Much like implementing sustainability initiatives in other areas of the organization, green coding requires both structural and cultural changes.
- Improving energy use at the core: Multi-core processor-based applications can be coded to increase energy efficiency. For example, code can directly instruct processors to shut down and restart within microseconds instead of using default energy saving settings that might not be as efficient.
- Efficiency in IT: Sometimes referred to as green IT or green computing, this methodology aims for resource optimization and workload consolidation to reduce energy use. By optimizing IT infrastructure through use of modern tools like virtual machines (VMs) and containers, organizations can reduce the number of physical servers needed for operations, which in turn, reduces energy consumption and carbon intensity.
- Microservices: Microservices are an increasingly popular approach to building applications that break down complicated software into smaller elements, called services. These smaller services are called upon only when needed, instead of running a large monolithic program as a whole. The result is that applications run more efficiently.
- Cloud-based DevOps: Applications running on distributed cloud infrastructure cut the amount of data transported over the network and the network’s overall energy use.
- Empower management and employees: Change is only effective when employees and management are on board. Encouraging adoption with consistent messaging to the entire DevOps team helps support the sustainability agenda and makes people feel like they are part of the solution.
- Encourage innovation: DevOps teams are often driven by the desire to innovate and create solutions to big problems. Encourage teams to look for new ways to use data insights, collaborate with partners and take advantage of other energy-saving opportunities.
- Stay focused on outcomes: Problems will arise when implementing new initiatives like green coding. By anticipating challenges, companies can deal with problems that arise more easily.
Benefits of green coding
Beyond the energy-saving benefits, companies may also find there are additional advantages to green coding practices, including the following:
- Reduced energy costs: It’s the simple principle of use less, spend less. With the increasingly volatile price of energy, organizations want to reduce the amount they spend on power not just for environmental sustainability, but also to maintain the sustainability of the business.
- Accelerated progress toward sustainability goals: Most organizations today have net zero emission goals or strategic initiatives to reduce emissions to increase sustainability. Green coding moves organizations closer to reaching this goal.
- Higher earnings: CEOs that implement sustainability and digital transformation initiatives, such as green coding, report a higher average operating margin than their peers, according to the IBM 2022 CEO Study.
- Better development discipline: Using green coding empowers programmers to simplify elaborate infrastructures and can ultimately save time, reducing the amount of code software engineers write.
Green coding and IBM
To find out more about IBM and green coding, start with the white paper from the Institute for Business Value: IT sustainability beyond the data center.
This white paper investigates how software developers can play a pivotal role in promoting responsible computing and green IT, discusses four major sources of emissions from IT infrastructure, and looks at how to fulfill the promise of green IT with hybrid cloud.
Infrastructure optimization is an important way to reduce your carbon footprint through better resource utilization. One of the fastest ways to make an impact on energy efficiency is to configure resources automatically to reduce energy waste and carbon emissions. IBM Turbonomic Application Resource Management is an IBM software platform that can automate critical actions that proactively deliver the most efficient use of compute, storage and network resources to your apps at every layer of the stack continuously—in real-time—without risking application performance.
When applications consume only what they need to perform, you can increase utilization, reduce energy costs and carbon emissions, and achieve continuously efficient operations. Customers today are seeing up to 70% reduction in growth spend avoidance by leveraging IBM Turbonomic to better understand application demand. Read the latest Forrester TEI study and learn how IT can impact your organization’s commitment to a sustainable IT operation while assuring application performance in the data center and in the cloud.
A final critical way to promote green computing is to choose energy efficient IT infrastructure for on-prem and cloud data centers. For example, IBM LinuxONE Emperor 4 servers can reduce energy consumption by 75% and space by 50% for the same workloads on x86 servers/. Containerization, interpreter/compiler optimization and hardware accelerators can then reduce energy needs further through green coding.