If not planned or understood there can be many pitfalls to cloud migration. Virtana’s recent State of Hybrid Cloud survey is evidence of this, with 7-in-10 (72%) of the 350 IT professionals surveyed stating that they have had to move workloads back to on-premises, after migrating to the public cloud. And such a high number certainly raises questions.
The reasons as to why cloud applications are having to be moved back to on-prem, includes: The migration of applications that should have stayed on-premises, various technical issues with provisioning for the public cloud, application performance degradation, wrong public cloud provider selection and the unexpected costs. But the good news is, these instances and barriers to successful cloud migration can be avoided. We need to consider various attributes of different workloads such as the data, back end, privacy and security requirements and their inherent suitability for a public cloud environment. We have to set clear goals and priorities so that we can make the best decision. Finally, you should understand the detailed health, utilization, and performance characteristics of your workloads in the data center. This baseline provides critical information to help you make migrate-or-stay decisions.
We must also take computing dimensions such as memory usage, IOPS, and network bandwidth into account. Additionally, you may have certain conditions that need to be factored in, such as prepaid reservation commitments or certain types of VMs you want to avoid. Any benefits you gain by moving applications to the cloud are outstripped if performance slows to an unacceptable level. To prevent this, we need to create a baseline of on-premises performance, and model representative workloads in your public cloud configurations before any migration work begins. Baselines are critical because they provide a reference point for comparing workload utilization and performance in the cloud. We need to ensure our baselines reflect any seasonality to give you the most complete view of the health, utilization, and performance characteristics. Then after moving our applications to the target cloud, we must optimize them to stay rightsized for performance and cost.
Too many times companies get a nasty surprise when their end-of-month cloud bill arrives. To do so, a company needs total visibility of how costs could potentially rise. Utilizing ongoing cloud optimization capabilities can provide such visibility, and provide a platform for resources to be adjusted so that bills remain affordable without performance being harmed.