Solving Tech Challenges Without Disruption: Exploring Rehosting, Replatforming, and Refactoring
Many businesses struggle with legacy systems. Outdated technology holding your business back. Many core applications in enterprises contain extremely large codebases, written in languages or frameworks that feel ancient. Modernizing such applications is full of risks. To reduce those risks, the parts of the legacy system that are not problematic should be left as they are. In this blog posts, we’ll explore less disruptive approaches to modernization and 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 doesn’t have to involve rebuilding or re-architecting the whole application. In this case, the business logic embedded within is sound and the architecture is not undermining functionality either. What one can still be faced with though, is a significant quantity of technical debt, running on dated/unsupported platforms or code, or utilizing technology that ultimately is now too expensive to use. These factors all pose risks to continuing the operation of the application as it becomes a highly complex process to adapt to skills shortages, compliance requirements, supportability, or other concerns.
When the problem is less deeply rooted, the modernization process need not necessarily be as disruptive. Rebuilding a legacy application with technological problems for instance could get the job done, but may also be overkill given the amount of resources it requires in costs, time, and effort. Not to mention the risk of business disruption. Instead, turning to replatforming, refactoring, and rehosting is more desirable as these methods inherently involve less risk and resource intensity in their methods.
Deciding on the modernization strategy comes down to determining the depth of the technological problems within the application. At the most shallow and unintrusive level, rehosting is an option. Rehosting involves migrating an application to a different cloud infrastructure without modifying its code or functionality. Changes within the application tend to be purely configurational to ensure compatibility with the new host platform. It therefore also means that the legacy application should be free of significant technical debt. Most often, rehosting is performed as a means of switching cloud providers for cost reductions, entailing that a large degree of modernization has already taken place.
Replatforming involves migrating an application to a new runtime platform with minimal codebase changes to ensure compatibility with the new environment. This approach enhances the application’s performance and scalability by leveraging modern cloud-native features like managed services, containerization, or modern database systems. However, the application’s core structure, features, and functionalities remain unchanged.
At the deepest level of intervention, refactoring is possible. Refactoring restructures an application’s internal architecture to enhance maintainability, performance, and scalability while retaining its external behavior. Syntactically changing the codebase, this approach eliminates technical debt, improves nonfunctional attributes (e.g., efficiency or reliability), and enables the adoption of modern architectures such as microservices or serverless.
Replatforming and Refactoring in Practice
Where modernization projects historically have been time-consuming and costly, Gartner predicts that by 2027 modernization costs will be reduced by 70% by using AI-driven app modernization software.
At SUE, we’re dedicated to helping our customers innovate faster. That is why our R&D department has developed Re:App. Re:App represents a paradigm shift in replatforming legacy applications, leveraging cutting-edge 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 full rearchitecting, making it an essential tool for businesses looking to retain core application functionality while improving scalability and maintainability.
Re:App simply takes the address of some application’s codebase, such as a GitHub repository, and analyzes the codebase to understand its structure, dependencies, and functionality. This AI-driven analysis builds the foundation that ensures an application is optimized to cultivate its greatest potential. It does so in several ways:
- Containerization: Re:App generates containerized versions of applications using industry standards like Docker and Kubernetes. The tool creates Dockerfiles, Kubernetes YAML manifests, and ensures the application is fully operational in cloud-native platforms such as OpenShift or AWS EKS.
- Deployment Automation: Re:App generates deployment manifests tailored to the target platform, adhering to the latest industry best practices for security, performance, and stability. For example, it enforces principles like running containers as non-root users and ensures compatibility with platform-specific standards.
- CI/CD Pipeline Generation: It automates the creation of CI/CD pipeline configurations, integrating tools like Jenkins or GitHub Actions for seamless build, test, and deployment workflows. This reduces manual intervention, enabling faster and more reliable application rollouts.
- Error Resolution and Validation: Leveraging recursive rebuild and deployment simulations, Re:App detects and resolves non-fatal errors in the application, ensuring the generated output functions as expected. The platform also validates the automated outputs in a simulated cloud-native environment to ensure compliance and functionality. This is done using a cutting edge technique known as retrieval augmented generation.
- Security and Performance Optimizations: Re:App incorporates best practices for container security, such as minimal image sizes, regular patching, and vulnerability scanning. It also enhances performance through optimized resource configurations and dependency management.
Automating these processes, Re:App eliminates many of the manual, time-intensive tasks traditionally associated with modernization and its disruptiveness. Time horizons shift from weeks to minutes, whilst still producing an output that is tested, verified, and up to date with best practices in security, stability, and performance. Furthermore, it is also in line with the continuous modernization mindset as the door is always left open to continuously improving the application stack.
Should I Put My Data in an LLM?
The business case is clear: GenAI will speed up legacy code modernization. Still, many companies refrain from putting their code into an LLM and use the output in production environments.
That is why we made Re:App risk-free. All changes are 100% reviewable before applying actions and all output can be tested by simulating deployments. But the most important feature might be that Re:App can be used in offline environments.
Many of our customers don’t want to put their data in an LLM that is connected to the internet. And thus, we made Re:App usable in isolated environments. By doing so, every company can profit from the benefits of AI in their modernization efforts.
Looking for more information?
Are you struggling with legacy systems? Need help by choosing the right modernization approach or would you like to reduce time and risk? Let us know! We’re happy to have a pressure-free chat to see how we can help.
