The world of tomorrow will be software-defined. Software is going to play a crucial role in many business models. And the more important software becomes, the more crucial will be the capability to develop software and the ability to ensure high code quality. A European provider for road user services decided to support their developers with AI capabilities from AWS, the Amazon Q Developer.
Individual mobility is increasing across the globe. Despite more efficient combustion engines and electromobility, carbon dioxide emissions in road freight transport are continuing to rise. The increasing traffic puts pressure on infrastructure maintenance and traffic management. Huge investments will be needed to future-proof national traffic systems.
Intelligent tolling systems will be a means to regulate traffic and transform the mobility sector, while simultaneously generating funds for the maintenance of infrastructures and the development of more environmentally friendly modes of transport. In Europe, quite a lot of tolling (or road user services) companies are active as an important contributor to the national traffic systems. They rely on digital infrastructure and software is at the heart of their business to monitor traffic and collect usage-based tolls. Business processes and digitalization are very closely connected in their business models. With their data and platforms, they are also able to provide significant value addition to innovative mobility solutions and national traffic management.
One of these toll providers is focusing on the transformation of road user management through digital innovation and strategic partnerships. The company wants to increase the efficiency and sustainability of transportation networks and is continuously developing its software accordingly.
The tolling provider faced challenges in maintaining and enhancing their code quality while striving to improve their code generation processes. The existing methods for code review and generation were labor-intensive and prone to human error, which would lead to inconsistencies and inefficiencies. The company recognized the need for a more automated and reliable solution to ensure high standards of code quality and accelerate the development lifecycle.
The software provider wanted to leverage the advantages of artificial intelligence (AI) to automate code reviews, enhance code generation, and ultimately improve the overall efficiency and quality of their software development processes. This shift towards AI-driven solutions was critical for maintaining their competitive edge and meeting the growing demands of the transportation technology sector. The company therefore approached T-Systems to introduce AI capabilities to their software development.
Our customer reached a new level of code quality and productivity for code generation using Amazon Q Developer, which we seamlessly integrated into its existing development environments and organization.
To enhance software development efficiency, T-Systems implemented Amazon Q Developer, a generative AI-powered assistant, designed to streamline various tasks throughout the development lifecycle. Amazon Q Developer aids developers and IT professionals with coding, testing, upgrading, troubleshooting, security scanning, AWS resource optimization, and data engineering pipeline creation. It allows for real-time code suggestions, explaining existing code in a codebase, debugging issues, writing unit tests, identifying security vulnerabilities, improving code, and other AI-powered assistance directly within the coding environment.
The service is available directly from AWS and thus integrated into the AWS console. T-Systems seamlessly integrated the service into the company’s existing development environments and command-line interfaces. Developers and IT professionals within the company are organized into specific users and groups. These users interact with the development environment and have varying levels of access based on their roles and responsibilities. AWS SSO is taking care of that. It serves as a single sign-on service managing user identities and permissions across the AWS services.
All the components operate within a specified AWS Cloud region, which ensures low latency and high availability of services. This regional deployment also complies with data residency requirements and optimizes performance.
With profound knowledge of AWS's AI capabilities and expertise in integrating AWS services into the customer’s existing development processes and tools, T-Systems helped the customer achieve convenient usage and a great user experience. The implementation of Amazon Q Developer has yielded significant benefits, notably improving developer productivity and code security. It speeds up deployment and enhances the quality of the code, leading to a more robust and reliable software development environment.
By automating new code creation based on inline code suggestions (as code is written), developers can focus on more complex and innovative tasks, accelerating the overall development process. Additionally, the Amazon Q Developer Agent for software development speeds up and automates the creation of essential documentation and unit tests. This agent also helps to build AWS projects or own applications using natural language for the description of the feature to be developed.
The troubleshooting capabilities for Lambda, EC2, Amazon ECS, Amazon S3 or network-related issues enable developers to identify root causes faster, reducing downtime and operational inefficiencies. Developers can diagnose console error messages directly in the AWS Management Console. Amazon Q provides information about the error and the steps to resolve it.
All these services, and some more, are directly available within the familiar integrated development environment, creating an excellent user experience. Utilizing the Explain feature, the Amazon Q Developer accelerates the onboarding process of new developers, helping them to become productive more quickly and gain a clearer understanding of new projects, which is a huge efficiency boost.
