‘Lift and shift’ is often exercised as a migration strategy for an application or activity from one environment to another without redesigning. In this approach, some workloads and tasks can be moved from on-premises storage to the cloud, or data processing can be moved from one data center to another.
The application’s complexity is a determining factor in deciding to move it as it is or overhaul its architecture. Out-of-the-box business applications, and those with easy to define schematics, often lend themselves well to the lift and shift approach. However, a redesign may be a better solution for applications that require many resources, such as big data analysis or image rendering applications. In this case, a redesign may indeed be necessary to avoid performance and latency problems.
The lift and shift approach is frequently adopted to replicate on-premises applications in the cloud without the need for tedious and expensive redesign. However, older co-location applications that are transferred to the cloud by this method may not take full advantage of the savings provided by cloud-native features such as ephemeral compute and autoscaling.
Some companies will do an app lift and shift to reduce on-premises infrastructure costs in the short term, then complete reorganization once the app is in the cloud. In a disaster recovery situation, it might be a good idea to quickly move an on-premises legacy application to the cloud to keep it operational, before revamping it afterwards.
The lift and shift can be compared to moving a houseplant: the change of environment can allow it to flourish or, on the contrary, be fatal. Likewise, an IT project that started on an on-premise or old system may not perform as well in a new location. A lift-and-shift project that commences without adequate documentation of requirements or functional design can quickly go awry. The unfortunate consequences often involve data mismatched to its handling systems or data sets that outgrow their environment. Resource-intensive applications may require to be redesigned from scratch as cloud-native apps to evade performance and latency concerns.
The lift and shift is not a simple cut and paste. Such a project launched without sufficient knowledge of the system requirements or functional design can end in failure. It may also result in data incompatible with the processing systems or files that exceed their environment’s capacities. Problems inherent in an application should be resolved before migrating to a new environment.
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