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Enterprises migrating to Cloud always are anxious to know the actual deployment time factor in the total migration process. However, there is no exact calculation of the process; a tentative time frame can be arrived at by taking in aspects of Cloud deployment.
CoreIT explains here some of the deciding factors that determines the time taken to move applications to Cloud. By rules of thumb one can arrive based on the function and object points, data coupling factors, cloud native features and complexities involved.
For enterprises that move to Cloud without modifying existing applications by the ‘lift and shift’ means, the time required is very less for deployment purposes. However, the advantages of cloud-native features such as identity management, governance, asset management and speed get compromised greatly.
Another approach is rebuilding the applications on native Cloud resources where the metrics of the existing applications are different. In this approach, complexity increases as refactoring of developing apps become irreplaceable.
Apart from these, factors such as resource usage versus availability, existing access mechanisms, security, IT managed services, integration, replication and application architecture also plays in deciding the time factor for migration and deployment.
Employing additional resources and tools to increase the speed of deployment process but it will require additional investment from the enterprises. Various providers may recommend a cloud-only approach, but this may not always be the best solution for all your applications. A careful design that accounts for all IT environment factors and business outcomes may instead yield a hybrid solution.
CoreIT advises that when moving an application to the cloud one must fully understand how an application will work and perform in the cloud. Refactoring the applications and moving with a DevOps approach, can result in massive benefits. This refactoring time spent is actually mitigated by taking that as a training opportunity to grow your organization to do things much quicker.
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