Rightsizing in cloud cost optimization means adjusting your cloud resources to match the actual workload demands of your applications. Instead of running oversized virtual machines or storage volumes that consume more than needed, you scale each resource to the minimum size that still meets performance requirements. This directly reduces waste and lowers your cloud bill without sacrificing reliability or speed.
Rightsizing is one of the most impactful levers in cloud cost management because most organizations provision resources conservatively at the start and rarely revisit those choices as workloads evolve. The result is persistent overprovisioning that silently inflates costs month after month. The questions below unpack how rightsizing works, what it applies to, and how to build it into your cloud operations effectively.
How does rightsizing actually reduce cloud costs?
Rightsizing reduces cloud costs by eliminating the gap between what you pay for and what you actually use. Cloud providers charge based on the size of the resource you provision, not the amount you consume. When a virtual machine uses 10% of its allocated CPU and memory, you are still paying for 100% of it. Rightsizing closes that gap by selecting a smaller, better-matched resource type.
The savings mechanism is straightforward. A VM that runs at 15% average CPU utilization can often be moved to an instance type half the size with no measurable impact on application performance. Multiply that across dozens or hundreds of resources and the cumulative reduction in monthly spend becomes significant.
Beyond direct cost reduction, rightsizing also improves your cloud unit economics. When resource sizes align with actual workload behavior, your cost-per-transaction or cost-per-user metrics become more accurate and predictable. This makes budgeting and forecasting more reliable, which matters to finance and IT leadership alike.
One important nuance: rightsizing is not about cutting resources to the bone. The goal is the right size, not the smallest size. You need to account for peak usage, not just average utilization, to avoid performance degradation during high-demand periods.
What types of cloud resources can be rightsized?
Virtually any cloud resource that is provisioned with a specific capacity can be rightsized. The most common targets are compute instances, databases, storage volumes, and container configurations. Each resource type has its own utilization signals and resizing mechanics, but the underlying principle is the same across AWS, Azure, and GCP.
- Compute instances (VMs): The most frequent rightsizing target. CPU and memory utilization data reveals whether an instance family or size is appropriate for the workload running on it.
- Managed databases: RDS instances, Azure SQL, and similar services are often overprovisioned to handle anticipated growth that never materializes. Storage IOPS and connection counts guide rightsizing decisions here.
- Storage volumes: Allocated disk sizes and provisioned IOPS can be reduced when actual usage is consistently lower than what was originally requested.
- Containers and Kubernetes workloads: CPU and memory requests and limits set in container configurations directly affect cluster node sizing and therefore cost. Misaligned requests lead to wasted node capacity.
- Networking and load balancers: Throughput tiers on load balancers and NAT gateways can sometimes be downsized when actual traffic volumes are well below provisioned capacity.
In practice, compute and database rightsizing deliver the largest savings for most organizations because these resource categories carry the highest unit costs.
What’s the difference between rightsizing and autoscaling?
Rightsizing and autoscaling are complementary but distinct approaches. Rightsizing sets the correct baseline size for a resource based on observed utilization patterns. Autoscaling dynamically adjusts the number of running instances or the allocated capacity in response to real-time demand. Rightsizing is a deliberate, periodic optimization decision; autoscaling is an automated, continuous operational mechanism.
Think of it this way: rightsizing determines what size each instance should be when running normally, and autoscaling determines how many of those instances should run at any given moment. If your autoscaling group is spinning up instances that are themselves oversized, autoscaling amplifies the waste rather than eliminating it. Rightsizing the base instance type first makes autoscaling more cost-efficient.
Neither approach replaces the other. Autoscaling handles variable demand patterns well, but it does not fix a fundamentally wrong instance type. Rightsizing addresses the baseline configuration, but it does not respond to unpredictable traffic spikes. Organizations that apply both together achieve better cost control and better performance than those that rely on only one.
How do you identify which cloud resources need rightsizing?
You identify rightsizing candidates by analyzing utilization metrics over a meaningful time window, typically 14 to 30 days, and flagging resources where actual usage consistently falls well below provisioned capacity. The most reliable signals are CPU utilization, memory usage, network throughput, and disk I/O, compared against the specifications of the current resource size.
A practical identification process involves three steps:
- Collect utilization data: Pull CPU, memory, and network metrics from your cloud provider’s monitoring tools or a third-party platform. Make sure you capture peak values, not just averages, to avoid undersizing resources that have occasional spikes.
- Set utilization thresholds: Define what “underutilized” means for your organization. A common starting point is flagging resources where average CPU stays below 20-30% and peak CPU stays below 50-60%, but thresholds should reflect your application’s tolerance for performance variation.
- Prioritize by cost impact: Sort candidates by their monthly cost, not by their utilization percentage. A resource running at 15% utilization but costing $50 per month is a lower priority than one running at 25% utilization but costing $2,000 per month.
Involving application teams in the review process is important. Utilization data tells you what a resource is doing, but the application team understands why it was sized that way and whether changing it carries risk.
What tools are used for cloud rightsizing?
Cloud rightsizing tools range from native provider features to dedicated FinOps platforms. Each major cloud provider offers built-in recommendations, but third-party tools provide broader visibility, cross-cloud analysis, and more actionable governance workflows.
Native cloud provider tools
AWS Compute Optimizer uses machine learning to analyze EC2, Lambda, and EBS utilization and recommend right-sized alternatives. Azure Advisor provides similar recommendations for virtual machines and databases within the Azure portal. Google Cloud’s Active Assist offers rightsizing suggestions for Compute Engine instances. These tools are free to use and integrate directly with your existing cloud console, making them a useful starting point.
Third-party FinOps platforms
Platforms such as Apptio Cloudability (part of the IBM Apptio suite) go beyond native tools by aggregating data across multiple cloud providers, mapping costs to business units, and integrating rightsizing recommendations into a broader cost governance workflow. These platforms are particularly useful for organizations running workloads across AWS, Azure, and GCP simultaneously, where a unified view is needed to prioritize actions and track savings over time.
The right tooling choice depends on your cloud footprint, the maturity of your FinOps practice, and how deeply you need to integrate cost data with business reporting.
When should rightsizing be reviewed in a cloud environment?
Rightsizing should be reviewed on a regular cadence, typically monthly or quarterly, rather than treated as a one-time project. Cloud environments change continuously: new workloads are deployed, application usage patterns shift, and teams provision resources for projects that later scale down or end. A single rightsizing exercise quickly becomes outdated without ongoing review.
Specific triggers that should prompt an immediate rightsizing review include:
- A significant change in application traffic or usage patterns
- The completion of a major project or campaign that temporarily drove up resource demand
- A cloud provider releasing a new instance family that offers better performance-to-cost ratios
- A budget cycle review where cloud spend needs to be reconciled against actual business value delivered
- An unexpected spike in your cloud bill that requires rapid investigation
In more mature FinOps practices, rightsizing review becomes part of a structured optimization cadence with defined owners, decision criteria, and a clear process for approving and implementing changes. Without that structure, rightsizing recommendations tend to accumulate in dashboards without being acted on, which is a common failure pattern organizations need to actively avoid.
Building rightsizing into a recurring governance rhythm, rather than treating it as an ad hoc activity, is what separates organizations that consistently reduce cloud waste from those that see only temporary gains.
How we help with cloud rightsizing and cost optimization
At Its Value, we support organizations in moving beyond one-off rightsizing exercises toward a structured, repeatable cloud cost optimization practice. Our FinOps services address the full rightsizing journey, from identifying where your cloud spend is going to building the governance model that keeps it under control over time.
Specifically, we help you with:
- Full cost allocation and visibility: We map cloud costs, including compute, storage, containers, and support charges, to the teams and workloads that generate them, so rightsizing decisions are grounded in accurate, trusted data.
- Rightsizing across AWS, Azure, and GCP: We identify overprovisioned resources across your entire cloud footprint, prioritize by cost impact, and support implementation with the relevant engineering and application teams.
- FinOps Maturity Assessment: If you are unsure where to start, our assessment gives you a clear picture of your current cloud financial management maturity and a practical roadmap for improvement, including rightsizing governance.
- Ongoing optimization cadence: We help you establish the decision rhythms, ownership structures, and tooling integrations needed to make rightsizing a continuous practice rather than a periodic project.
If you want to understand what rightsizing could save your organization and how to build it into a sustainable FinOps practice, get in touch with us to discuss where to start.
This content was generated with the help of AI — it may contain mistakes