Cost assessment
Review billing, usage, ownership and commitments.
Ranked findings with assumptions and validation requirements.
Cloud bills grow quietly. A test VM nobody switched off, disks left behind when a server was deleted, a database sized for a launch that never needed it. We find the waste, resize what's oversized, and set up scaling and budgets so the bill follows real usage.

/ Fit check
Best for
Businesses running workloads in Azure or AWS whose monthly bill has drifted upwards
Not for
Hyperscale platforms that need a dedicated in-house FinOps team
Deliverables
Costed findings, a resize plan, budgets, alerts and a tagging standard
/ Direct answer
An Azure cost reduction consultant reviews your subscriptions, finds resources that are idle, oversized or on the wrong pricing model, and fixes them without breaking the workloads that depend on them. Typical changes include right-sizing virtual machines, deleting orphaned disks and IP addresses, scheduling non-production shutdowns, moving steady workloads to reservations or savings plans, and setting budgets and alerts so costs stay visible. The same work applies in AWS, where the equivalent tools are Cost Explorer, Compute Optimizer, Savings Plans and Reserved Instances.
/ Scope your engagement
A cost concern does not always require a migration. Start with the decision, then agree the platform access and evidence needed to assess it.
Review billing, usage, ownership and commitments.
Ranked findings with assumptions and validation requirements.
Test approved capacity and scaling changes against real workload needs.
Measured performance and a rollback path before acceptance.
Review new spend, idle resources and agreed budgets.
Owner-assigned recommendations and review records.
This example illustrates the record format. It is not a client result or a service-level commitment. Your proposal lists the deliverables and responsible people.
| Finding | Check before changing | Proposed action |
|---|---|---|
| Underused compute | Usage history, peak load, dependencies and recovery needs | Test a smaller configuration; measure performance before accepting |
| Unused subscription | Owner, data retention, integration and contract obligations | Approve removal only after dependencies and data are resolved |
| Backup uncertainty | Workload coverage, retention and last successful restore | Document the gap and agree a recovery validation task |
Azure or AWS estate, billing period, usage patterns, commitments and workloads that cannot tolerate disruption.
/ 01
In a handful of predictable places: virtual machines sized for a peak that rarely happens, non-production environments running around the clock, unattached disks and public IPs left after deletions, oversized databases, snapshots kept long past their purpose, and premium storage holding data nobody reads.
| Leak | How we find it | Typical fix |
|---|---|---|
| Oversized VMs | 30+ days of CPU and memory data, Azure Advisor | Resize or move to a better-fitting VM series |
| Always-on dev and test | Tags and usage hours | Auto-shutdown schedules |
| Orphaned disks and IPs | Resource Graph queries | Snapshot if needed, then delete |
| Steady workloads on pay-as-you-go | Usage history | Reservations or a savings plan |
| Hot storage for cold data | Access patterns | Lifecycle rules to cool or archive tiers |
| Log ingestion | Per-table ingestion volume | Filter, shorten retention, cheaper log tiers |
/ 02
Usually for the same few reasons: EC2 and RDS instances sized for a peak that rarely comes, non-production environments running around the clock, NAT gateway and cross-zone data transfer charges, CloudWatch logs kept forever, and old EBS snapshots and unattached volumes. Cost Explorer grouped by service and usage type normally shows which one it is within minutes.
| AWS cost driver | Typical fix |
|---|---|
| Oversized EC2 and RDS instances | Right-size using Compute Optimizer and 30 days of metrics |
| Always-on dev and test | Instance scheduling outside working hours |
| NAT gateway and data transfer | VPC endpoints, and keeping traffic in one availability zone where safe |
| CloudWatch logs with no expiry | Set retention per log group |
| Old snapshots and unattached EBS volumes | Lifecycle policies, then delete what isn't needed |
| Steady workloads on on-demand pricing | Savings Plans or Reserved Instances after right-sizing |
/ 03
We look at at least a month of CPU, memory, disk and network data before changing anything, resize a non-production copy first where one exists, and schedule production changes in a maintenance window with a rollback plan. A VM resize usually needs a restart, so we treat it as a change, not a tweak.
/ 04
Reserved instances give the deepest discount but tie you to a specific VM family and region for one or three years. Azure savings plans give a smaller discount but apply across VM sizes and regions, as long as you commit to an hourly spend. For stable, predictable workloads, reservations usually win. For an estate that's still changing, a savings plan is the safer commitment.
Commit after right-sizing, not before. Buying a reservation for an oversized VM locks the waste in for years.
/ 05
Autoscaling adds capacity when load rises and removes it when load falls, so you stop paying for peak capacity all day. Virtual machine scale sets, App Service autoscale rules and serverless options like Azure Functions all do this. Which one fits depends on how the application is built.
Not every application can scale out. Older apps that keep state on the server need work before they can run on several instances, and we'll say so plainly instead of promising savings the architecture can't deliver.
/ 06
With budgets and alerts per subscription or resource group, a tagging standard so every resource has an owner and a cost centre, Azure Policy to block expensive SKUs or untagged deployments, and a monthly cost review that looks at the trend rather than just the total.
/ 07
As a fixed-scope engagement, agreed in writing before work starts. The scope depends on the number of subscriptions, the size of the estate, and whether you want us to make the changes or only recommend them. Ongoing cost management can then be added to a managed cloud agreement.
A VM resize needs a restart, so that machine is briefly unavailable. We schedule it in an agreed maintenance window and, for anything critical, test the new size on a copy first.
Read access through a named account, using the Reader and Cost Management Reader roles, is enough for the review. Any changes use separately approved, time-limited permissions.
It depends entirely on how the estate has been run, so we don't quote a number up front. The review report lists each finding with its estimated monthly saving, so you can decide what's worth doing.
Yes. Azure and AWS are covered in detail on this page, and Google Cloud follows the same approach with its own tools, such as committed use discounts and Recommender. The principles of right-sizing first and committing second apply on every platform.
Yes. We plan resource sizing, ownership tags, budgets and policies when creating an environment. This gives the team a basis for reviewing usage and costs as workloads change.
/ Next step
Azure or AWS estate, billing period, usage patterns, commitments and workloads that cannot tolerate disruption.