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Sample Deliverable Preview

See What a FinOps Sprint Delivers

This is an illustrative example of a completed FinOps Sprint deliverable — representative of the findings, savings breakdown, and guardrails we establish during a typical 14-day engagement. Actual results vary based on your cloud provider, account structure, and current spend level.

Numbers in this sample are representative, not from a specific client. No client data is disclosed.

FinOps Sprint Report — Sample
Sample Organization — AWS Multi-Account Environment
14-day SprintAWS (3 accounts)
Savings Identified
32%
$5,800/mo

Executive Summary

The 14-day sprint analyzed three AWS accounts covering compute, storage, network resources, and commitment purchases. Five cost finding categories were identified and remediated during the sprint window, with guardrails installed to prevent regression.

Baseline Spend
$18,400/mo
Savings Identified
$5,800/mo
Optimized Run Rate
$12,600/mo
Sprint ROI
~14x
on $5,000 investment

Illustrative sample only. These numbers are representative of findings we commonly encounter for organizations spending $10k–$30k/month on AWS. Your engagement will be scoped and sized to your specific environment.

Cost Findings (Sample)

Five categories of cloud waste were identified and addressed during the sprint. Each finding includes the root cause, estimated monthly savings, and the remediation action taken.

HighCOMPUTE-001

Over-Provisioned EC2 Instances

Compute

Est. Savings
$2,100/mo
Finding

Fourteen EC2 instances running at under 15% average CPU utilization for 30+ consecutive days. Three production web servers were sized for peak-year traffic that never materialized.

Action Taken

Rightsize to the next smaller instance type for each workload. Schedule dev and test instances to shut down evenings and weekends using AWS Instance Scheduler.

Sprint window:Days 3–5
HighCOMMIT-001

Missing Savings Plans Coverage

Commitment Discounts

Est. Savings
$1,800/mo
Finding

Stable baseline workloads — application servers and database instances that have run continuously for 18 months — are entirely on-demand. No Savings Plans or Reserved Instances in place.

Action Taken

Purchase 1-year Compute Savings Plans sized to the committed baseline. Model with the AWS Cost Explorer Savings Plans recommendations before committing.

Sprint window:Days 6–7
MediumSTORAGE-001

Orphaned EBS Volumes and Snapshots

Storage

Est. Savings
$640/mo
Finding

31 EBS volumes totaling 4.2 TB are not attached to any running instance. 200+ automated snapshots older than 90 days remain in the account with no documented retention policy.

Action Taken

Delete unattached volumes after confirming no active mount references. Implement a snapshot lifecycle policy: 7-day daily, 4-week weekly, 3-month monthly. Remove snapshots outside that window.

Sprint window:Days 3–4
MediumORPHAN-001

Unused Elastic IPs, Load Balancers, and NAT Gateways

Network Resources

Est. Savings
$720/mo
Finding

Eight Elastic IP addresses with no associated instance. Two Application Load Balancers with zero target traffic for 60+ days. One NAT Gateway serving fewer than 500 MB/month — well below the break-even threshold for elimination.

Action Taken

Release unattached EIPs immediately (no data risk). Decommission the two idle ALBs after confirming no pending DNS references. Evaluate replacing the low-traffic NAT Gateway with a NAT instance.

Sprint window:Days 4–6
LowSTORAGE-002

S3 Storage Class Mismatches

Object Storage

Est. Savings
$540/mo
Finding

Approximately 18 TB of objects in S3 Standard that have not been accessed in over 90 days — including application logs, CI/CD artifacts, and archived media — have no lifecycle policy applied.

Action Taken

Apply S3 Intelligent-Tiering to buckets with unpredictable access patterns. For predictably cold data (logs, archives), create lifecycle rules transitioning objects to S3 Glacier Instant Retrieval after 90 days.

Sprint window:Days 5–7
A full engagement also produces a 90/180-day roadmap of additional opportunities outside the sprint window, prioritized by ROI and implementation complexity.

How the 14-Day Sprint Works

The sprint is structured to deliver tangible savings during the engagement, not just a list of recommendations. By the end of day 14 you have working guardrails, implemented changes, and a clear path forward.

Access and Baseline

Days 1–2

1
  • Read-only access configured (no production changes during discovery)
  • Cost and usage report (CUR) analysis to identify top cost drivers
  • Establish monthly spend baseline per service and per team

Savings Implementation

Days 3–7

2
  • Rightsizing and scheduling for identified idle resources
  • Orphaned resource cleanup (volumes, snapshots, EIPs, unused LBs)
  • Savings Plans / Reserved Instance analysis and commitment modeling

Guardrails and Controls

Days 8–12

3
  • Budget alerts at 80% and 100% of monthly targets, per account and per team
  • AWS Cost Anomaly Detection configured with alert thresholds
  • Tagging policy documented and Tag Editor remediation applied

Handoff and Roadmap

Days 13–14

4
  • Executive summary with realized savings and projected 12-month impact
  • 90/180-day optimization roadmap prioritized by ROI and implementation effort
  • Optional transition to monthly FinOps Management for sustained savings

Guardrails Installed

Savings without guardrails regress. By the end of the sprint, the following controls are operational so spend does not creep back.

Monthly budget alert at 80% and 100% threshold per account
AWS Cost Anomaly Detection with $500 alert sensitivity
Cost allocation tags enforced on all new resources via Service Control Policies
Weekly cost digest emailed to engineering lead and finance contact
Savings Plans utilization tracking configured in Cost Explorer
S3 lifecycle policies applied to three identified buckets

Your Sprint Deliverables

Every FinOps Sprint produces the same core set of outputs — scoped to your environment and spend level.

Prioritized savings plan (quick wins + structural fixes)
Implementation of agreed savings opportunities during the 14 days
Cost guardrails: budgets, anomaly alerts, and reporting baseline
Tagging and allocation recommendations (what to fix first for visibility)
Executive-ready summary (what changed, what it saves, what is next)
90 / 180-day roadmap for continued optimization

Best fit: $5k–$100k/month cloud spend on AWS, Azure, or GCP.

Ready to see your numbers?

Book a 30-minute call to confirm fit, discuss your cloud environment, and scope the sprint. If we are not the right fit, we will tell you directly.