If the cloud is a destination you have planned for any of your enterprise workloads, then you need to be prepared to navigate the journey that is the cloud migration process. It’s not unlike planning for a physical trip to a fabulous destination (or maybe we’re just really really ready to start traveling again). Either way, we’ve got some travel tips to ensure that your cloud-bound workloads have a great trip.

We often talk about migrating applications to THE cloud, or running workloads in THE cloud, as if the cloud is one, homogenous environment. The reality is, of course, far more complex. There are private clouds and public clouds—and different public cloud service providers (CSPs) that each have their own particular capabilities and strengths. Modern, digitally transformed businesses usually leverage a combination of these clouds.

Many organizations are shifting vast portions of their applications and infrastructure to the cloud in pursuit of lower IT costs, greater business agility, improved security, and accelerated corporate growth.

Migrating workloads to the cloud can be tricky. In fact, a study Virtana conducted earlier this year found that 72% of respondents had to move applications back on-premises after migrating them to the public cloud because they ran into a variety of problems. Clearly, organizations need to address these showstoppers.

AWS offers a Compute Optimizer tool that uses machine learning to analyze your historical utilization metrics and then recommend optimal AWS resources to help you reduce costs and improve performance. And it is free, you just need to opt in to the service in the AWS Compute Optimizer Console. Sounds great, right? Well, yes and no. It is a useful little tool, but if you do not understand its pros and cons, you will not be as optimized as you may think. Here is a breakdown.