This list is about cloud resources, not staff, since people also use “rightsizing” for cutting headcount. It is for IT heads, cloud and platform owners and engineers at mid-size companies in India and the GCC. They run workloads on AWS, Azure or both and are about to change the size of a resource, perhaps after a rightsizing recommendation from AWS or Azure. It gives a cloud rightsizing checklist of 19 checks in four parts, each with a suggested owner, the evidence to collect and the risk of skipping it. Run it for one resource at a time before the change.
Last reviewed 2026-11-01 by Manish Sharma.
Cloud Rightsizing Checklist: The Short Answer
The 19 checks run in four parts: evidence before you choose a size, validating the target, planning the change, and what to do after it. This is not a scan for wasted spend. Our cloud cost optimization checklist finds the candidates, and rightsizing recommendations from the providers’ tools are one input to it. Here you already have a candidate, so the job is to confirm that the change is safe.
How to Use the 19 Checks
Take one resource at a time, because each change needs its own evidence. A check passes only with its evidence, so attach it. Record the tool’s look-back window and who set any thresholds. The owners in the tables are suggestions to adapt to your team.
Rightsizing is matching a resource’s size to what the workload really uses. Utilization is the share of capacity in use. A percentile (P95 or P99) shows behavior at the busiest times, in place of the average. Headroom is the spare capacity you keep above the observed peak. A canary is a small first release used to test a change. Rollback is returning to the previous state. A stateful system holds data that must survive a change. A look-back window is the period a tool analyzes.
Cloud Rightsizing Checklist, Part 1: Evidence Before You Choose a Size
Six checks confirm that the evidence is enough. The tools’ default windows are short, so our explainer on rising cloud costs lists the defaults (14 days for AWS Compute Optimizer, per AWS documentation, and 7 days for Azure Advisor, per Microsoft Learn, as of November 2026) and notes that you can extend both.
| Check | Suggested owner | Evidence to collect | Risk if skipped |
|---|---|---|---|
| 1. A named owner, purpose, environment and criticality for the resource, and whether it is stateful | Resource owner | A one-line record, so anyone can see who owns the resource | Otherwise, no one can approve or reverse the change |
| 2. An evidence window that covers a full normal cycle, with the tool’s window setting recorded | Platform engineer | The window used, so a reviewer can see the setting in AWS Compute Optimizer or Azure Advisor | As a result, a quiet week hides the busy period |
| 3. Peaks and percentiles recorded, not averages | Platform engineer | P95 and P99 for each dimension, since averages hide peaks | So a low average hides the spikes that cause failures |
| 4. Memory and other signals reported, with an agent or outside source where the platform does not report them | Platform engineer | Memory, disk and network data, plus where it came from when an agent supplied it | Otherwise, the change is sized on CPU alone |
| 5. Application health signals recorded: latency, errors, queue depth, throttling, swap, out-of-memory events, job completion | Application owner | A baseline of each signal, taken before the change | As a result, you cannot tell afterward whether the change hurt |
| 6. Real peaks separated from waste: batch jobs, backups, month-end processing, deployments | Application owner | A list of scheduled loads on the resource, including month-end runs | So a real peak is read as waste |
Reading the Look-Back Window
Choose a window that includes the busiest period.
After you change Azure Advisor’s look-back, its recommendations can take up to 48 hours to update. Compare lists only when they come from the same settings, because a list taken the same day may still show the old window.
Cloud Rightsizing Checklist, Part 2: Validate the Target
Five checks confirm that the new size is right and available.
| Check | Suggested owner | Evidence to collect | Risk if skipped |
|---|---|---|---|
| 7. A concrete target size and family, one step from the current one (or a step up where there is a bottleneck) | Platform engineer | The chosen target and the reason, so a reviewer can follow it | Otherwise, a large jump hides the cause of any problem |
| 8. The target offered in the resource’s zone and region | Platform engineer | Availability confirmed in the provider’s console or documentation, before the change | As a result, the change fails at the point of making it |
| 9. Attached-resource compatibility: local storage, accelerators, network and storage limits, licensing | Architect | A list of attachments checked against the target, including licensing | So an attached resource stops working at the new size |
| 10. Every reference to the old size updated: launch templates, scaling groups, infrastructure as code, load-balancer health checks | Platform engineer | A search result showing each reference, so none is missed | As a result, the old size returns at the next deployment |
| 11. Headroom decided and recorded, with who set it, tied to service objectives | Application owner | A written headroom decision, so the number has an owner | Otherwise, an unowned number becomes an outage later |
What Can Make a Cheaper Target Unusable
A target can be cheaper and still unusable. On Azure, Advisor’s resize criteria say the new size must be available in the resource’s region and still support Accelerated Networking and Premium Storage (Microsoft Learn, as of November 2026). For a virtual machine scale set, Advisor prioritizes instance-count changes over size changes because count changes are easier to act on, so ask whether a count change is enough.
Key Takeaway Headroom is a decision with an owner. Do not copy a number from a guide.
Cloud Rightsizing Checklist, Part 3: Plan the Change
Five checks make the change safe to run. Our cloud cost optimization checklist has a separate warning-box for removal precautions.
| Check | Suggested owner | Evidence to collect | Risk if skipped |
|---|---|---|---|
| 12. Owner approval, and the rightsizing recommendation checked against the cases to dismiss or postpone: sized for upcoming traffic, uses other resources, under specific testing, must stay a matching size, used for disaster recovery | Resource owner | A signed approval and a note on each case, if it applies | So a rightsizing recommendation breaks something the tool could not see |
| 13. The previous size and configuration recorded, a restorable image checked and a revert path tested | Platform engineer | The saved configuration and a revert test result, run before the change | As a result, you cannot go back |
| 14. A test on staging, a clone, a replica or a canary, with its result | Platform engineer | A test report, so the result is on record | Otherwise, production is the first test |
| 15. A maintenance window and change process, because a resize can stop and restart the resource | Change owner | An approved window, because a restart may happen | So an unplanned restart interrupts users |
| 16. Baseline metrics and alerts captured before the change | Operations owner | A saved snapshot of the baseline metrics and alerts | As a result, you cannot show whether the change helped |
Key Takeaway Test the way back before the change, because a revert nobody has run is untested.
For a database or stateful system, run the test against a replica or clone. Check the memory working set, IOPS, connection limits and query latency there before you touch production.
Cloud Rightsizing Checklist, Part 4: After the Change
Three checks close the loop. A revert is a valid result. AWS’s Right Sizing page calls right sizing an ongoing process, so set the next review date as part of the record.
| Check | Suggested owner | Evidence to collect | Risk if skipped |
|---|---|---|---|
| 17. Monitoring for a full workload cycle, not a day | Operations owner | Monitoring that covers the cycle, including its busiest period | Otherwise, a slow failure shows after you stop watching |
| 18. Performance, errors and saturation compared with the baseline, with a keep-or-revert decision on the rightsizing recommendation | Application owner | A comparison, and the decision to keep or revert when the result is clear | So a degraded service stays in place |
| 19. The result recorded next to the baseline and the next review date set | Resource owner | A change record, so the history is available next time | As a result, the same question returns with no history |
If the comparison is unclear, keep watching or revert.
The Go/No-Go Rule
Change only if there is evidence for every part and a named approver. The finding record pattern is in our cloud cost optimization checklist.
Parts 1 and 2 have evidence, and the window covers a full cycle.
Part 3 is done, including the revert.
One named person, with the date.
What This Checklist Does Not Cover
This checklist is for one resource before a resize. It does not find candidates, give the reasons behind each step or compare how each provider produces rightsizing recommendations. This list has no template file, so use the evidence column as your structure. It gives no savings figures.
For the wider picture, see how Signisys helps you right-size cloud resources and cut waste. Our page on cloud cost optimization and FinOps adds detail. See also our cloud services and platform engineering.
FAQ: Cloud Rightsizing Checklist
What should be on a cloud rightsizing checklist?
How is this different from a cloud cost optimization checklist?
Who should own each check?
When is a resource ready to be resized?
How long should we monitor after a resize?
Do the checks work for both AWS and Azure?
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