According to Gartner, the cloud services market will top $200 billion in 2016 and the wave of enterprise applications migrating to the cloud has yet to crest. The benefits of lower costs, increased speed of IT delivery and the flexibility of anywhere, anytime access to services continues to fuel the growth of the category.
However, migrating to the cloud is becoming even more challenging with the growth and fragmentation of cloud offerings. How do you choose the best platform for your applications?
Don’t Rely on Half Measures to Calculate Success
The industry is ripe with analytics on cloud performance by vendor including the recent emergence of cloud service provider performance indices. Too often migration teams rely solely on the component performance statistics that they receive from the cloud providers. This approach, more often than not, results in several shifts in the application architecture until the optimal platform is identified. This trial and error approach can be avoided with the proper planning and the right tools.
The core challenge in achieving an accurate match of the application to the cloud service involves the complexity of determining the scope of your application workload and how that applies to the different cloud capabilities. Simply relying on cloud vendor data and industry comparisons only tells a partial story. If the benchmarking was done on a single machine then it can be terribly misleading and inaccurate. In order to be effective in migrating an application to the cloud you have to identify the application workload demand and apply it to the different cloud platforms to gain a true assessment of how that application will behave in each instance.
Dramatically Reduce the TCO of Cloud Migrations
Matching the application workload intensity to the performance capabilities of each cloud platform can reduce the TCO of cloud migrations by eliminating iterative hops from one platform to the next in order to achieve the best operating environment. In addition, workload to cloud capability matching eliminates the common mistake of over-provisioning platform resources to ensure performance while driving-up costs.
The Growth in Multiple Clouds
More and more enterprises are finding that multiple cloud deployments are needed to support their growing list of applications that are expanding into the cloud. Google Cloud Platform, Microsoft Azure, Amazon Web Services, Softlayer by IBM, private clouds and hybrid clouds all can offer viable application environments, however, choosing the right platform for your application can be challenging. The same stack on each platform can have vast performance variations based on the region and the relationship between resources even within the same cloud provider because thousands of variables are involved.
The only way to get it right and ensure that your application will perform at the desired level while minimizing over-provisioning is to match the application workload to the exact capabilities of each platform instance. Therefore, if there is not a suitable option with one cloud provider, enterprises are forced to expand into multiple clouds which can create a management challenge.
To experience a demonstration of how CloudQoS matches application workloads to cloud capabilities click here.