Welcome back.

When we talk about rightsizing, what we really mean is making sure your cloud resources match the way they're actually being used.

In a multi cloud set up, rightsizing is one of the most powerful levers you have for optimization.

The key is simple: don't pay for oversized instances that sit mostly idle, but also don't shrink them down far enough that you end up with performance hurting.

The problem is, rightsizing manually is overwhelming. Reviewing every single VM or instance individually just isn't practical.

That's where the automated rightsizing tools in AWS and Azure come into play. In AWS, we have Compute Optimizer. Now, this is a service that analyzes historical utilization metrics and then recommends instance types that might be a better fit for your workloads. It looks at CPU, memory, network, and disk utilization over the past 14 days or more, and then based on those patterns, it tells you whether you should downsize, upsize, or even switch to a different instance family altogether.

The recommendations cover not just EC2 instances, but also Auto Scaling groups, EBS volumes, and even Lambda functions. Compute Optimizer might recommend dropping down to an M5 Large.

These insights show up right in the AWS Management console, but you can also pull them programmatically, and that's useful in multicloud because it means you can export AWS data and line it up alongside recommendations from Azure.

Now in Azure, we have Azure Advisor, which is a personalized recommendation engine that scans your resources and highlights opportunities to optimize. Cost optimization is one of its five main categories, along with high security, reliability, operational excellence, and performance.

For virtual machines, Azure Advisor analyzes CPU and memory usage, and then flags VMs that are consistently underutilized. The recommendation might be to resize to a smaller SKU or move the workload onto a different purchasing option, such as reserved VM instances.

But Advisor also goes beyond VMs. It can also suggest scaling down or even shutting off unused app service plans, express route circuits, and other services where you might be paying for capacity that isn't actually being used.

So how do these tools fit together in a multicloud practice?

Well, both Compute Optimizer and Azure Advisor look at utilization trends and suggest more efficient configurations, but their insights live inside their own clouds.

To get the full picture, you need to export AWS Compute Optimizer findings and Azure Advisor recommendations and then bring them together in a central dashboard.

For example, you could leverage a tool like Power BI, Tableau, or even Excel Power Query to ingest both data sources, normalize them, and then present them in one dashboard. That unified view makes it easier to compare optimization opportunities across providers, and sometimes the insight goes even further.

It may influence where you choose to run a workload in the first place. If AWS workloads are consistently over-provisioned while Azure workloads are closer to optimal, that might guide future placement decisions.

Now a few best practices to keep in mind. Start with non-production. Apply rightsizing changes in dev or test environments before you roll them into production.

Once you've done that, set thresholds. Don't accept every recommendation at face value. Instead, you want to always validate that performance requirements will still be met.

Third, automate where it makes sense. Both AWS and Azure let you act on recommendations programmatically, which can save huge amounts of time in large environments.

And then finally, review on a regular basis. Because workloads change quickly, you need to make sure that rightsizing reviews are part of your quarterly FinOps rhythm.

So, as we wrap up here, be sure to remember that automated rightsizing tools are like having a cost consultant built directly into your cloud platform. AWS Compute Optimizer and Azure Advisor give you the visibility you need to rightsize with confidence without spending hours digging through utilization metrics by hand. And in a multicloud strategy, pulling those recommendations together is what unlocks true optimization across providers.

Automated instance rightsizing tools

About