It’s 9:00 AM on a Wednesday. You’re in the boardroom giving a status update on the latest migration project that will remove most of the vulnerabilities found during the recent pandemic. This is the third migration project, all less than 100 workloads and 10 data sets. All have taken place in parallel, and all leverage different cloud migration teams.
Company leadership notes that the metrics were very different between the projects. Project One shows nearly 80 percent efficiency in terms of code refactoring, testing, deployment, security implementation, etc. The others were closer to 30 and 40 percent. Why the differences?
Most efficiency issues arise from dynamic versus static migration approaches and tools. Most people who currently do cloud migrations gravitate toward the specific processes, approaches, and migration tool suites that worked for past projects. This static approach to cloud migration forces a specific set of processes and tools onto a wide variety of migration projects and problem domains. The misuse of specific processes and tools as generic solutions often leads to failure.