O Gartner, a world leader in research and advice for companies, announces the main strategic technology trends in Software Engineering for the coming years.
Joachim Herschmann, vice president and analyst at Gartner
“Software engineering leaders are under continuous pressure to adopt modern architectures and technologies. To be successful, they need to know which trends have the greatest potential impact for their digital business efforts within a planning horizon,” says Joachim Herschmann, vice president and analyst at Gartner. For him, the main trends highlighted by Gartner represent a set of approaches and technologies that software engineering leaders should take advantage of in the next two to three years to stay ahead of the market, innovate and thrive in an environment of constant disruption.
The main technological trends for software engineering fall into three distinct categories: training developers for teams to unleash their full potential, improving teams using Artificial Intelligence technologies and focusing on program development scaling trends. According to Gartner, the main trends are:
InnerSource: InnerSource is a software development strategy that applies open source practices to proprietary code. By adopting an open source mindset for software development, companies can bridge gaps and break down silos, leading to a stronger, more structured program development lifecycle. “Ultimately, InnerSource helps teams build software faster and work better together, resulting in higher-quality, better-documented development,” says Herschmann.
Developer Experience: Developer experience refers to all aspects of interactions between developers and the tools, platforms, processes, and people they work with to create and deliver products, software, and services. Improving the developer experience is critical to succeeding with digital initiatives and build high performance teams. Gartner points out that the developer experience goes beyond its tools and technologies. “The tools used in daily work certainly play a role in improving the quality of developer workflows. However, the developer experience also depends on non-technological factors such as dedicating time to deep, creative and meaningful work, as well as having the personal freedom to try new things without fear of failure”, says the Gartner analyst
Software Engineering Teams Prepared to Use Artificial Intelligence: Software engineering augmented by Artificial intelligence leverages its technologies to help software engineering teams build and deliver applications faster. Teams can quickly generate different types of systems, including design elements, application code or test cases, which can be refined and reused, thus accelerating the overall development process. “Software engineering augmented with Artificial Intelligence requires making engineering teams more efficient in their work, relieving them of a tedious professional routine, rather than allowing technology to replace them,” explains Herschmann.
Applications Powered by Artificial Intelligence Technology: The combination of available enterprise data, advanced model building capabilities and generative Artificial Intelligence services will result in improved applications of data that drive better business decisions. Artificial Intelligence-enabled applications can enrich the information available in companies, automate workflows and create models that assess risks or recommend next best actions. To be successful when using Artificial Intelligence, software engineering leaders must treat the development of their models differently from application development and coordinate activities between the model development and building teams.
Platform Engineering: Platform Engineering is the discipline of building and operating internal, self-service development platforms for software delivery and lifecycle management. Helps developers discover, operate, secure, improve, and evolve complex, distributed IT systems — especially when they are not technical experts in the underlying systems. Platforms improve the overall developer experience with a curated set of tools and services. They also improve the consistency and quality of IT solutions and reduce redundant tools and processes, consolidate parallel efforts from multiple teams, enforce security and compliance standards, and include widespread automation.
Digital Immune System: Digital Immunity interconnects practices from the areas of observability, software testing, chaos engineering, software development, website reliability engineering, and software supply chain security to ensure high resilience and quality of applications. “Many software engineering organizations are already using some of these strategies, but none of these practices alone will be sufficient to achieve the goal of building highly resilient systems,” says Herschmann. “Together, these practices constitute a powerful continuous quality approach to ensuring that complex digital systems continue to function even if the ‘house is on fire’.”
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