Solving technical challenges without disruption: exploring rehosting, replatforming, and refactoring
Many organizations struggle with legacy systems. Outdated technology that holds your business back. Many core applications within enterprises consist of extremely large codebases, written in languages or frameworks that now feel outdated.
Modernizing such applications involves many risks. To limit those risks, it is better to leave the parts of the legacy system that are not causing problems as they are. In this blog post, we explore less disruptive approaches to modernization and show how new technologies can help reduce risks and modernization costs.
Choosing the right App Modernization approach
When the problem with a legacy application is purely technological, application modernization does not necessarily mean that you have to rebuild or rearchitect the entire application. In such cases, the business logic is solid and the architecture does not undermine functionality. What you may encounter, however, is a significant amount of technical debt, running on outdated or unsupported platforms or code, or using technology that has simply become too expensive. These factors all pose risks to the continuation of the application, as it becomes increasingly complex to deal with skill shortages, compliance requirements, supportability, and other issues.
When the problem is less deep-rooted, the modernization process does not necessarily have to be disruptive. Completely rebuilding a legacy application with technological problems can solve the problem, but is often overkill given the costs, time, and effort involved. Not to mention the risk of disrupting the business. Instead, replatforming, refactoring, and rehosting are often more attractive, as these methods are inherently less risky and less resource-intensive.
Determining the right modernization strategy boils down to assessing the depth of the technological problems within the application. At the most superficial and least disruptive level, rehosting is an option. Rehosting involves migrating an application to a different cloud infrastructure without modifying the code or functionality. Changes within the application are usually purely configurational, to ensure compatibility with the new platform. This also means that the legacy application must be free of significant technical debt. Rehosting is often used when switching cloud providers to reduce costs, which implies that a significant degree of modernization has already taken place.
Replatforming involves migrating an application to a new runtime platform, with minimal changes to the codebase to ensure compatibility with the new environment. This approach improves performance and scalability by leveraging modern cloud-native features such as Managed Services, containerization, or modern databases. The core structure, features, and functionalities of the application remain unchanged.
At the deepest level of intervention, refactoring is possible. Refactoring restructures the internal architecture of an application to improve maintainability, performance, and scalability, while keeping the external behavior the same. By syntactically modifying the codebase, technical debt is eliminated, non-functional properties (such as efficiency and reliability) are improved, and the way is paved for modern architectures such as microservices or serverless.
Replatforming and Refactoring in Practice
Where modernization projects have historically been time-consuming and costly, Gartner predicts that modernization costs will decrease by 70% by 2027 through the use of AI-driven software for application modernization.
At SUE, we are committed to helping our customers innovate faster. That is why our R&D department developed Re:App. Re:App represents a paradigm shift in the replatforming of legacy applications and uses advanced AI technologies to streamline the transition from monolithic or legacy codebases to cloud-native environments. As a replatforming tool, Re:App automates the modernization of legacy applications without the need for complete rearchitecting. This makes it an essential tool for organizations that want to retain core functionality while improving scalability and maintainability.
Re:App simply takes the address of an application codebase, such as a GitHub repository, and analyzes it to understand its structure, dependencies, and functionality. This AI-driven analysis forms the basis for optimizing an application and getting the most out of it. Re:App does this in several ways:
- Containerization. Re:App generates containerized versions of applications according to industry standards such as Docker and Kubernetes. The tool creates Dockerfiles and Kubernetes YAML manifests and ensures that the application is fully operational on cloud-native platforms such as OpenShift or AWS EKS.
- Deployment automation. Re:App generates deployment manifests that are tailored to the target platform and comply with the latest best practices in terms of security, performance, and stability. Examples include enforcing non-root containers and compatibility with platform-specific standards.
- CI/CD pipeline generation. The tool automates the creation of CI/CD pipeline configurations and integrates tools such as Jenkins or GitHub Actions for seamless build, test, and deployment workflows. This reduces manual operations and ensures faster and more reliable releases.
- Error resolution and validation. Using recursive rebuild and deployment simulations, Re:App detects and fixes non-fatal errors in the application, ensuring that the generated output functions as expected. In addition, the platform validates the automated outputs in a simulated cloud-native environment to ensure compliance and functionality. This is done using an advanced technique known as retrieval augmented generation.
- Security and performance optimizations. Re:App applies best practices for container security, such as minimal image sizes, regular patching, and vulnerability scanning. It also improves performance through optimized resource configurations and dependency management.
By automating these processes, Re:App eliminates many of the manual and time-consuming tasks traditionally associated with modernization and the associated disruption. Lead times shift from weeks to minutes, while the output is tested, validated, and fully aligned with current best practices in security, stability, and performance. What's more, Re:App aligns with a continuous modernization mindset, where the door is always open to further improve the application stack.
Should I put my data in an LLM?
The business case is clear: GenAI accelerates the modernization of legacy code. Yet many organizations are reluctant to put their code into an LLM and use the output in production environments.
That's why we've made Re:App completely risk-free. All changes are 100% reviewable before actions are applied, and all output can be tested by simulating deployments. But perhaps the most important feature is that Re:App can also be used in offline environments.
Many of our customers do not want to offer their data to an LLM connected to the internet. That is why we have made Re:App suitable for use in isolated environments. This allows every organization to benefit from the advantages of AI in their modernization efforts, without compromising on security or control.
More information
Is your organization struggling with legacy systems? Do you need help choosing the right modernization approach, or do you want to reduce time and risk? Let us know! We would be happy to talk to you, without obligation, to see how we can help you.
