Two decades ago, green coding was subject to limitations such as bandwidth constraints and processing power restrictions, which compelled developers to be mindful of the size and intricacy of their code. However, with the advent of more advanced technology, programmers are no longer bound by these restrictions.
As an illustration, enhanced computing power facilitated quicker processing of vast files and applications. Open-source libraries and frameworks enabled software engineers to recycle segments of code in their projects, opening up greater possibilities. Nonetheless, this resulted in programs with a higher number of lines of code, necessitating more processing power to parse it. As an unintended outcome, this led to increased energy consumption and a surge in global electricity demand.
In the pursuit of advancing sustainable practices and transforming their businesses, companies are delving into their established processes to uncover novel efficiencies. This involves scrutinizing the foundational components of their business operations, such as optimizing data storage and reviewing their coding methods.
Green coding is an environmentally sustainable approach to computing that aims to minimize the energy required to process lines of code, thereby enabling organizations to curtail their overall energy consumption. In response to the crisis of climate change and global regulations, many organizations have established targets for reducing their greenhouse emissions, and green coding represents a means of advancing these sustainability objectives.
Green coding is a subset of green computing, which endeavors to mitigate the environmental impact of technology, including diminishing the carbon footprint of resource-intensive processes like manufacturing lines, data centers, and even the routine operations of business teams. The broader domain of green computing encompasses green software as well, which refers to applications developed using eco-friendly coding practices.
The proliferation of technology, including advancements in big data and data mining, has led to a significant surge in energy usage within the information and communications technology industry. The Association for Computing Machinery reports that energy consumption at data centers has doubled over the past ten years. Presently, computing and IT are accountable for generating between 1.8% and 3.9% of worldwide greenhouse gas emissions.
To gain a comprehensive comprehension of how green coding can curtail energy usage and minimize greenhouse gas emissions, it is useful to delve into the energy consumption of software:
Recent research into the pace and energy consumption of various programming languages has revealed that C is the swiftest and most efficient in terms of diminishing energy usage and memory consumption, thereby presenting another avenue for potential energy savings. Nonetheless, there is some dispute regarding how this is achieved and which metrics should be employed to evaluate energy savings.
Green coding originates from the same principles as traditional coding. To curtail the amount of energy necessary to process code, developers can incorporate less energy-intensive coding principles into their DevOps lifecycle.
The “lean coding” strategy centers on utilizing the minimal amount of processing required to deliver a finished application. For instance, website developers may give priority to decreasing file size, such as substituting high-quality media with smaller files. This approach not only hastens website loading times but also enhances the user experience.
The goal of lean coding is also to minimize code bloat, which refers to code that is needlessly long or sluggish and uses up resources inefficiently. Open-source code can contribute to software bloat since it is meant to support a wide array of applications and consists of a substantial amount of code that is unused for the particular software. For instance, a developer might import an entire library into an image, despite only requiring a fraction of its functionality. This redundant code utilizes extra processing power and leads to superfluous carbon emissions.
When developers implement lean coding practices, they tend to create code that necessitates only the least amount of processing while still accomplishing desired outcomes.
The principles of green coding are generally intended to supplement the present IT sustainability standards and practices employed throughout the organization. Comparable to incorporating sustainability efforts in other departments of the organization, green coding necessitates both cultural and structural modifications.
Apart from the benefits of reducing energy consumption, companies may discover additional advantages to adopting green coding practices, such as:
To learn more about IBM’s approach to green coding, you can begin by reading the white paper from the Institute for Business Value titled “IT Sustainability Beyond the Data Center.”
The white paper explores the important role that software developers can play in advocating for responsible computing and green IT. It examines the four primary sources of emissions from IT infrastructure and examines how the hybrid cloud can fulfill the potential of green IT.
Optimizing your infrastructure is an important step in reducing your carbon footprint and making better use of resources. One of the most efficient ways to improve energy efficiency is to automatically configure resources to minimize energy waste and carbon emissions. IBM’s Turbonomic Application Resource Management is a software platform that can automate important actions to deliver the most efficient use of compute, storage, and network resources to your applications at every layer of the stack in real-time. With this tool, you can achieve greater efficiency without risking application performance.
By ensuring that applications only use the resources they require to function, it is possible to boost utilization, cut energy expenses and carbon emissions, and achieve consistently efficient operations. With IBM Turbonomic, customers have experienced up to a 70% reduction in growth spend avoidance by gaining a better understanding of application demand. Check out the latest Forrester TEI study to learn how IT can contribute to your organization’s drive towards sustainable IT operations while ensuring top-notch application performance both in the data center and the cloud.
One important approach to promote green computing is to opt for energy-efficient IT infrastructure in on-premises and cloud data centers. IBM LinuxONE Emperor 4 servers, for instance, can reduce energy consumption by 75% and space by 50% while providing the same workloads as x86 servers. Green coding can further reduce energy needs by leveraging containerization, interpreter/compiler optimization, and hardware accelerators.
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