Companies face psychological, institutional, and technical hurdles when it comes to confidently right-sizing app instances
In a recent post, we noted that many companies are struggling to control their public cloud costs, even though a key driver for moving to the public cloud in the first place was often to cut infrastructure expenses. There is a proven way to slash public cloud costs by as much as 20-40%, however: by right-sizing cloud instances.
If that’s the case, why isn’t everyone already doing it? There are a number of reasons – ranging from the psychological to the technical – why right-sizing cloud instances can be challenging. Most fundamentally, application owners are prone to over-provision IT resources in a bid to avoid resource shortages that can cause app performance issues and unhappy customers.
For example, in the public cloud, if you’ve purchased a cloud instance with four CPUs and you really only need two CPUs to run your application, you’re just wasting money. This kind of over-provisioning is probably the most common cause of waste in public cloud environments. But, why? One reason is that as companies move apps hosted on-premise to the cloud, they simply replicate their existing VM resource allocations without first determining if the app really needs all those resources. Other times the allocation recommendations come from the app vendor themselves and are blindly followed by the team. The vendor wants its clients to be happy so they suggest excessive provisioning of resources taking a “better-safe-than-sorry” approach.
Companies that haven’t instituted a charge-back model to charge application owners for their resource usage are especially prone to over-provisioning abuses, as the app owners have no incentive to scale-back their infrastructure allocations.
Underlying all of these dynamics is a lack of visibility into the amount of IT resources a given application workload needs to meet its performance and service-level requirements. Many cloud management tools are simplistic and provide only broad-brush information about peak loads and other cloud instance data. To right-size cloud applications with confidence – cutting costs without putting performance at risk – you need to understand the detailed work patterns of each app instance.
Densify’s analytics service provides just this type of deep predictive analysis of workload patterns, giving companies the insight they need to optimally leverage public cloud resources reducing operational risk and costs. With this granular data in hand, Densify’s team of Densification Advisors recommend to their customers how to safely right-size their cloud instances or modernize the instances by moving to new offerings from their cloud vendor. The company provides insights on how to do this in a 5-part blog series found here.