Migrating legacy applications is a complex process with quite several challenges. Here is the way I approach those issues
Compatibility and Dependency Issues: Many legacy applications rely on older versions of libraries or special types of hardware. Dependency check is the very first task by identifying the incompatible components, but also testing alternatives is quite key too. To encapsulate all these dependencies, it usually involves using Docker, and through which I create a consistently cloud-compatible runtime environment.
Monolithic Architectures and Refactoring: Legacy applications largely have monolithic architectures which are not very well scalable to work in the environment of the cloud. My application of the strangler pattern is slow and takes apart the monolith into microservices over time. In this regard, refactoring incrementally somehow compensates for some of the reduced risk as parts of an application are being updated piecemeal.
No Downtime Data Migration: Migration of data involves special care, especially if the data set is humongous or updated at all times. Services such as AWS Database Migration Service or Azure's migration tools enable continuous replication; therefore, near real-time synchronization occurs in the process.
Testing and Validation: I test the migrated application in a quasi-production environment by using shadow deployments or canary releases. This allows real testing of user interactions and performance without full commitment to the new arrangement, thus reducing risks.
Post-Migration Optimization: Following migration, I apply some cloud-native tools for monitoring and cost management to ensure the application is efficient in performance and cost-efficient in its new environment.
