Challenges in Application Modernization
In today's world, application modernization is crucial to stay competitive. To achieve successful modernization, a combination of expert knowledge, advanced tools, and a highly proven methodology that guides and ensures the success of these initiatives is needed.
Application modernization can be a complex and difficult process, with obstacles that can hinder the final goal. One of the most significant challenges in application modernization is the lack of knowledge and documentation about the legacy system. Many legacy systems were developed decades ago, and over time, the developers who created and maintained them may have left the organization or moved on to other projects. This can lead to a lack of understanding of how the system works, making it difficult to identify what needs to be modernized.
Moreover, modernizing a complete IT system can take months or even years, depending on the complexity of the application, the size of the organization, and the resources available. This can pose a significant challenge for companies that need to remain competitive and agile in the current digital environment.
Another significant challenge in application modernization is the lack of experts and technical profiles available to carry out the project. Modernizing legacy systems requires specialized competencies and knowledge, such as experience in modern technologies, data migration, and application integration. Finding experts with these skills can be a significant challenge, especially in areas where there is high demand for technical talent.
Artificial Intelligence as an Accelerator for Application Modernization
The latest advances in artificial intelligence in language models applied to code generation allow us to perform a series of tasks that were previously difficult or even impossible to accomplish. Some of the possibilities opened up by these advances include:
- Automated code generation: AI-based language models can generate code automatically, saving a significant amount of time and effort.
- Code description: providing a functional description of the existing code and how it works, which is especially useful and relevant in legacy applications with a lack of documentation, absence of comments in the code, or unfamiliarity by the development and maintenance teams.
- Code error identification: language models can analyze and detect patterns of common errors in the code, which can be very useful for improving the quality of the generated code.
- Code refactoring: suggestions for refactoring, optimizing existing code, or adapting to new architectures or frameworks.
- Reduction of repetitive tasks: AI-based language models can help automate many tasks that previously required advanced programming skills.
- Performance: language models can help optimize the code for better efficiency and performance.
In general, advances in artificial intelligence in language models are transforming the way code is created, modified, and managed, opening a world of possibilities and opportunities for innovation in this area.
Azure OpenAI Services
One of the most advanced language models oriented towards commercial applications is GPT-3/4, available in Microsoft's Azure Open AI services.
Azure OpenAI Services is an artificial intelligence platform that allows developers to generate code in an automated way, improving efficiency and effectiveness in application development. What sets Azure OpenAI apart from other similar solutions is its ability to generate code supervised by developers, giving them more control over the generated code. In addition, being hosted on a Microsoft Azure infrastructure ensures data privacy, security, and compliance aspects.
These advanced capabilities will have a greater impact if they are integrated into a comprehensive approach to the application modernization process, where all these aspects are combined:
- Combination of expert team, methodology, and automation platforms: The use of an expert team, methodology, and automation platforms can be a very powerful tool to achieve specific objectives.
- End-to-end vision of the process when combining these elements: In this way, it can be ensured that all elements fit and work together to achieve the desired objectives.
- Ability to customize the generated result to the specific architectures and frameworks of each organization: Each organization has its own set of specific architectures and frameworks, and it is important that the generated results can be customized to fit these unique needs.
- Include tasks such as quality improvement, security enhancement, and refactoring: In addition to developing efficient and customized solutions, it is important to include additional tasks to ensure the quality and security of the process.
Automation Platform: Coding by NTT DATA
NTT DATA has an application modernization strategy that incorporates all the advantages of the most advanced artificial intelligence solutions.
For this, we have the Coding automation platform, for which we have worked since early 2022 to integrate the capabilities of Azure OpenAI Services, combining artificial intelligence with NTT DATA's expert knowledge in application modernization and maintenance.
NTT DATA’s Coding platform is one of the most disruptive and high-potential assets in our Modernization Studio toolkit.
Although language models offer valuable functionalities out of the box, their application in the modernization processes of complex legacy applications is not immediate. It is necessary to provide additional layers of value that allow modernization teams to preprocess the source code, understanding both its technical and functional structure, carry out specific AI training to efficiently solve code transformation, following the specific development architectures and frameworks of the organization. It is essential to facilitate the task of modernization teams in aspects such as the limitation of the input size that you can provide to the AI or the prompt engineering (natural language request to the language model), to achieve high levels of productivity that ensure the ROI of the project.
NTT DATA’s Coding platform has all these functionalities, in addition to a knowledge base of specific use cases that have already been successfully implemented in modernization projects for leading organizations belonging to different sectors of activity and with a diverse portfolio of applications in their technological stack and in their level of obsolescence prior to the adoption of the cloud environment.
In application modernizations, NTT DATA’s Coding powered services allow potential efficiencies to be obtained at a ratio of 20-40% compared to a 100% manual transformation.
An example of these use cases, very common in sectors such as Banking and Insurance, is the updating of database engines to take advantage of the capabilities of the cloud available today. The modernization of these database engines can be a complex process that requires time, effort, and experience, but with NTT DATA’s Coding platform and modernization services, very significant efficiencies are achieved thanks to the specific training for these use cases already available on the platform.