Rightsizing Your Cloud: Extend Your Multi-cloud Toolkit
Last summer, we introduced the world to our new, updated Rightsizing Recommendation Engine for AWS – a powerful cost optimizer that shows AWS users how to align their cloud infrastructures tightly to their needs. The feature remains one of our most popular and we are now excited to announce the general availability of Rightsizing recommendations for Azure.
When done right, rightsizing can be a huge win for cloud users. Here’s how it works – and how to use Cloudability to do it properly.
The Advantage of the Cloud: Efficiency and Elasticity
Among the biggest advantages that can be gained by migrating to the cloud are the efficiency and elasticity that it offers. The ability to pick and choose the best cloud resource types for your needs (and to scale with agility in response to workload) allows you to balance the needs of your customers with cost savings. However, you need a nuanced sense of your architectural needs before you can start chipping away at your infrastructure in search of further savings.
Rightsizing is the process of matching your workload to your infrastructure in a way that minimizes cost. One huge benefit of using the cloud is that you can quickly make changes to try to rightsize most effectively; however, when taking a corrective action you need to understand both the risk associated with making the change, in addition to the potential savings.
The Risks of Reckless Cost Cutting – and of Excessive Caution
Savings are great, but not when they come at the cost of degraded performance. That’s why “clipping” is such a tricky problem. “Clipping” refers to provisioning a resource that works fine for your workload most of the time, but which maxes out your instance during peak periods, resulting in performance problems and server errors. For a web app or service that faces consumer traffic, compromised availability can have profound consequences – so the risk is significant.
Many companies are so concerned with avoiding this problem that they overprovision instead – and end up paying much higher costs than they really need to.
Visualize Your Options with High-confidence Recommendations
Rightsizing involves two considerations: risk and savings. An option with higher savings carries greater risk, while an option with lower risk comes with lower cost savings but a better guarantee in terms of performance.
While calculating potential savings might be simpler, it is the ability to determine valid resource types and find a way to represent and mitigate risk for each option that makes a critical difference. That’s why Cloudability’s Rightsizing Recommendations Engine for AWS and Azure uses statistical modeling and risk measurement algorithms to provide multiple recommendations for each customer, providing a clear sense of potential savings while making the risk known upfront.
Here’s how it works. The Recommendations Engine leverages the time series data of relevant utilization metrics for your resources, then creates a statistical model around average and peak utilization periods. The tool leverages historical utilization data to identify performance characteristics across instance types, families and zones to provide valid recommendations for your workload.
Rightsizing delivers a set of recommendations, each with a unique savings/risk profile. These recommendations are represented visually and overlay the recommended lower-cost resource utilization on top of your chosen workload. For example with compute, you can visualize all four key metrics of utilization: CPU, disk, memory and bandwidth. This makes it easy to visually inspect headroom and the potential for clipping.
You’ll see the top recommendation first – the one with the most potential savings and the lowest risk. However, customers also want the ability to update the recommendations based on the requirements of their organization. For example, in case of Amazon EC2 we recommend the newest generation instances, but you may have pricing or infrastructure needs that require that you resize only to prior generation instances. Likewise, you may prefer to stay within the same instance family for ease of resizing, as is the case for some Azure Compute workloads. Because of this, we allow you to select options on the details page that will update the recommendations. This ability to visualize multiple recommendations and simulate resource utilization has been game-changing for our customers.
Get Recommendations Across Instance Families
Our Rightsizing recommendations engine, especially for AWS, delivers the ability to generate recommendations across families, while most other tools only recommend between sizes. This is crucial when you consider how often the “shape” of an instance doesn’t actually match the true workload – for example, an instance may have excessive memory while constantly maxing out CPU. The ability to scenario plan across families opens up tons of opportunity for extra savings, and can help you land on an instance type that most closely matches your needs.
Get Rightsized Today
Ready to rightsize your infrastructure? Download our Rightsizing Tech Brief to learn more about Cloudability’s Rightsizing Recommendation Engine for AWS and Azure or reach out to one of our experts directly.