Cloud Cost Optimization Services that lower your cloud bill
Lower your AWS, Azure or Google Cloud bill without slowing anything down. Start with a 72-hour cost analysis, a fixed-price sprint where we ship the savings, or ongoing management that keeps costs from creeping back.
Four ways to start
Fixed prices, fixed scope. Compare them below.
What Cloud Cost Optimization Involves
Cloud cost optimization is the work of lowering an AWS, Azure, or Google Cloud bill without making the workloads on it slower or less reliable. It has two parts. First a cost analysis: where the money goes, what is idle or oversized, and how much steady usage still runs at on-demand rates. Then the changes themselves: right-sizing, commitments, storage tiering, Kubernetes tuning, data transfer fixes, cleanup, and tagging so the savings hold.
PlatOps sells that work in four shapes, from a 72-hour report to an ongoing FinOps practice. This page explains what each one includes, what we look at in each cloud, and how to choose.
Audit, Sprint, or Ongoing FinOps?
The four offers overlap on purpose: each one starts with a cost analysis. They differ in who makes the changes, how long we stay, and what else is in scope.
| Attribute | Cloud Cost Audit | Cloud Bill Sprint | Cloud & DevOps Audit Sprint | FinOps Management |
|---|---|---|---|---|
| What it is | A one-time cloud cost analysis with a ranked list of savings | A fixed-scope sprint that finds savings and implements the top ones | A broader infrastructure audit: cost, security posture, and DevOps single points of failure | A recurring FinOps practice run by us |
| Length | 72 hours, plus a walkthrough call | 14 days | 30 days | Ongoing; 6-month minimum recommended |
| Price | $5,000 up to $50K/mo spend; $10,000 for $50K–$250K/mo; custom above | $5,000 fixed | $5,000 fixed | $2,500/mo up to $50K/mo spend; $5,000/mo up to $200K/mo; custom above |
| Clouds | AWS, Azure, GCP | AWS, Azure, GCP | AWS | AWS, Azure, GCP |
| Who makes the changes | Your team; the $10,000 and custom tiers include 1–3 days of implementation support | We implement the top agreed savings, with your approval | We ship three agreed quick wins (cost or security) | We implement and keep them in place |
| Guardrails | Recommendations only | Budgets, anomaly alerts, and a reporting baseline set up | Budgets, anomaly alerts, and tagging recommendations | Anomaly detection, budget tracking, and monthly reporting |
| What you keep | Report with executive summary, inventory, right-sizing and commitment plans, 90-day action plan | Savings plan, implemented changes, guardrails, 14/30/90/180-day roadmap | Audit report, security snapshot, single-point-of-failure map, 30/60/90-day roadmap | Regular optimization reviews, commitment portfolio management, and (from Professional) chargeback reporting |
| Pick it when | You have engineers to do the work and need the list, or a business case | You have no FinOps role and want savings shipped, not documented | Cost is one of several worries and one engineer carries the whole AWS estate | Spend changes month to month, several teams deploy, or you hold commitments |
Which one fits
You need a number before anyone approves work
Cloud Cost AuditYou want the bill lower this month and have nobody to do it
Cloud Bill SprintYou run on AWS and also worry about security gaps or a single DevOps engineer
Cloud & DevOps Audit SprintYou optimized once and the bill crept back
FinOps ManagementThe usual path is one of the first three, then FinOps Management once the backlog of savings is cleared. Below roughly $5,000 a month in cloud spend, a paid engagement may not pay for itself; budgets and alerts are often enough.
The Optimization Work
These seven levers are where cloud savings come from. Each has a trade-off, and we check it before changing anything.
Right-sizing compute and databases
Compare provisioned CPU and memory against observed utilization over a representative period, then move instances, database tiers, and container requests down a size or to a current generation.
Savings Plans, Reserved Instances, and CUDs
Measure the steady baseline of compute and database usage, then cover it with AWS Savings Plans or Reserved Instances, Azure Reservations or savings plan for compute, or GCP committed use discounts.
Storage tiering and lifecycle
Move cold objects to cheaper storage classes, add lifecycle rules, migrate old volume types, and delete snapshots and backups past their retention requirement.
Kubernetes cost
Fix pod requests and limits, right-size node pools, tune the cluster autoscaler, add namespace quotas, and run interruptible workloads on Spot or preemptible nodes. Costs are allocated per namespace or team.
Data transfer and networking
Trace NAT gateway processing, cross-zone and cross-region traffic, and internet egress back to the services that cause them, then fix with VPC endpoints, zone-aware routing, caching, or a CDN.
Idle and orphaned resources
Find unattached disks, unused IP addresses, idle load balancers, forgotten test environments, and dev or staging resources running nights and weekends, then remove or schedule them.
Tagging, allocation, and showback
Define a small tagging standard (owner, environment, product, cost center), enforce it on new resources, and build showback reports so each team sees its own spend.
What We Look At in Each Cloud
The levers are the same everywhere; the services, discount programs, and native tools are not.
AWS
- Cost and Usage Report data, grouped by account, service, and tag
- Compute Optimizer findings for EC2, Auto Scaling groups, EBS, Lambda, and RDS
- Savings Plan and Reserved Instance coverage and utilization
- Graviton candidates and previous-generation instance types
- gp2 volumes that can move to gp3; unattached EBS volumes and old snapshots
- S3 storage classes, Intelligent-Tiering, and lifecycle rules
- NAT gateway processing, cross-AZ transfer, and public IPv4 addresses
- RDS sizing, and Multi-AZ on non-production databases
- CloudWatch Logs retention and ingestion volume
Azure
- Cost Management exports, grouped by subscription, resource group, and tag
- Azure Advisor cost recommendations, checked against real utilization
- Reservations and Azure savings plan for compute coverage
- Azure Hybrid Benefit for Windows Server and SQL Server licenses you already own
- VM sizes, B-series fit, and auto-shutdown on dev and test VMs
- Unattached managed disks and old snapshots
- Blob Storage access tiers and lifecycle management policies
- App Service plans and Azure SQL tiers sized above their load
- Log Analytics ingestion and retention
Google Cloud
- Billing export to BigQuery, grouped by project, service, and label
- Recommender findings for idle VMs and machine type right-sizing
- Committed use discount coverage, resource-based and spend-based
- Custom machine types where predefined shapes waste memory or CPU
- Idle persistent disks, old snapshots, and unused static IPs
- Cloud Storage classes, Autoclass, and lifecycle rules
- Inter-region and internet egress, and network service tier
- Cloud SQL instance sizing and high-availability settings on non-production
- GKE node pools, Autopilot fit, and Cloud Logging volume
What a Cloud Cost Analysis Gives You
Every engagement opens with the same cost assessment. In the audit it is the product; in the sprints and FinOps Management it is the work plan.
Spend baseline
Current monthly spend split by account or subscription, service, environment, and team, with the trend across the billing history you share.
Top cost drivers
The handful of line items that make up most of the bill, and what is behind each one in plain terms.
Waste inventory
Every idle, orphaned, or oversized resource we found, with its monthly cost and the owner we think it belongs to.
Right-sizing list
Instance-by-instance recommendations with the utilization data behind each, plus a risk rating for the change.
Commitment model
Current coverage and utilization of Savings Plans, reservations, or CUDs, and the commitment we would buy, with term and break-even.
Prioritized plan
Findings ranked by monthly saving and effort: quick wins, changes that need testing, and architecture work, each with a suggested owner.
Running a Cost Analysis Yourself
You can do a first pass in-house. This is the order we work in, and it finds the large items first. For the specific findings that come up most often, see five AWS cost mistakes SMBs make.
- 1Export the billing data: AWS Cost and Usage Report, Azure Cost Management export, or the GCP billing export to BigQuery.
- 2Group spend by account, service, and environment. If tags are missing, note which spend you cannot attribute.
- 3List the top ten line items. They usually explain most of the bill, so start there.
- 4Pull CPU and memory utilization for the biggest compute and database resources and look for anything sized well above its peak.
- 5Check commitment coverage: how much steady usage still runs at on-demand rates, and whether existing commitments are fully used.
- 6Look for orphans: unattached disks, old snapshots, idle load balancers, unused IPs, and environments nobody owns.
- 7Read the data transfer lines. NAT gateway, cross-zone, and egress charges are easy to miss and often fixable.
- 8Rank every finding by monthly saving and by risk, then fix the low-risk items first.
Typical Timeline
How the first month runs. An audit stops after day 3; the sprints run to day 14 or 30.
- Day 0
Scoping call
We confirm spend, clouds, and goals, recommend one of the options above, and send a read-only access policy.
- Days 1–3
Cost analysis
Billing and utilization data is analyzed and findings are validated by an engineer. The Cloud Cost Audit report is delivered on day 3.
- Days 3–14
Quick wins
In a sprint, low-risk changes ship first: cleanup, scheduling, and right-sizing, each approved by you before it runs.
- Days 14–30
Commitments and guardrails
Commitments are sized against the new, lower baseline. Budgets and anomaly alerts are switched on.
- Month 2 onward
Ongoing FinOps
With FinOps Management, reviews run monthly, bi-weekly, or weekly depending on tier, and commitments are adjusted as usage changes.
Frequently Asked Questions
What is the difference between a cloud cost audit and ongoing FinOps?
A cloud cost audit is a point-in-time analysis: you get a ranked list of savings and decide who implements them. Ongoing FinOps, which we run as FinOps Management, implements the changes and keeps watching, because new resources, new teams, and expiring commitments push the bill back up. The audit tells you what to fix today; FinOps keeps it fixed.
Should we start with an audit, a sprint, or FinOps Management?
Start with the Cloud Cost Audit if you have engineers to do the work and need the list or a business case. Start with the Cloud Bill Sprint if you want savings implemented in 14 days. Pick the Cloud & DevOps Audit Sprint if you run on AWS and security or a single DevOps engineer worries you as much as cost. Go straight to FinOps Management if you already optimized once and costs crept back.
Will cost optimization affect performance?
It should not, and we design changes so it does not. Right-sizing is based on peak utilization, not averages. Changes run in non-production first where possible, are approved by you, and have a rollback plan. Commitments and cleanup do not touch running workloads at all. If a change carries performance risk, the recommendation says so.
Do you need access to production?
Not for the analysis. We work from read-only billing and utilization access, using an IAM policy or role we provide. For implementation, you choose: we hand your team change sets to apply, we make approved changes ourselves, or we implement over screen-share for sensitive environments.
How much will we save?
It depends on where you start. Environments that have never been optimized typically fall in the 20–30% range we quote for this service, in line with the 29% of cloud spend Flexera’s 2026 survey finds wasted; accounts that already use commitments and clean up regularly see less. The audit or sprint gives you a dollar figure for your own account before you commit to anything ongoing.
Do Savings Plans, reservations, or CUDs lock us in?
Yes, for one or three years, which is why we buy them after right-sizing and only for the steady baseline. While your architecture is still changing we favor the flexible types: AWS Compute Savings Plans, Azure savings plan for compute, and GCP spend-based committed use discounts.
Is cost optimization worth it on a small cloud bill?
Below roughly $5,000 a month in cloud spend, the savings may not cover a paid engagement. In that case we usually suggest setting up budgets and alerts and focusing on operational stability first.
Which tools do you use?
The native ones first: AWS Cost Explorer and Compute Optimizer, Azure Cost Management and Advisor, and GCP billing exports and Recommender. For Kubernetes we use Kubecost. We work with tools you already pay for, such as CloudHealth or Datadog, rather than adding new ones.
Related Services and Tools
FinOps Management
Ongoing cost control with monthly reviews and commitment management.
Kubernetes Services
Cluster design and operations, including right-sized node pools.
Managed Cloud
Day-to-day cloud management with cost optimization built in.
ROI Calculator
Compare in-house IT and staffing costs against a managed service.
Not sure which option fits?
Tell us your clouds and monthly spend on a call. We will recommend one, or tell you none is worth it yet.
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