Cloud Cost Optimization
Reduce your AWS and Azure cloud spend by 20–35% through rightsizing, reserved planning, and continuous cost governance.
TL;DR: CloudTechForce helps businesses reduce cloud spending by 20–35% through instance rightsizing, reserved capacity planning, idle resource elimination, storage optimization, and ongoing cost governance — supported by real-time dashboards and monthly reports.
What's Included in Cloud Cost Optimization
Cost Analysis
Detailed breakdown of spending by service, team, and project with waste identification.
Rightsizing
Match instance types to actual workload requirements — often saves 15–25% on compute alone.
Reserved Planning
Strategic reserved instance and savings plan purchasing for 30–72% discounts.
Ongoing Governance
Automated alerts, budget controls, and monthly optimization reports to prevent cost drift.
More than a quarter of your cloud bill is paying for nothing
Idle instances, oversized VMs, and forgotten storage quietly drain budget every month while your invoice keeps climbing. That waste compounds across every account and region until cost control becomes the single hardest part of running cloud.
Cloud Cost Optimization rightsizes resources, plans reserved capacity, clears waste, and adds governance to cut your spend 20-30%.
Book a free assessment27%
of public cloud spend organizations estimate is wasted
[src] Flexera State of the Cloud 2024
#1
managing cloud spend ranks as the top cloud challenge for organizations
[src] Flexera State of the Cloud 2024
Speak to a Cloud Cost Optimization Expert
Tell us about your IT environment and we'll prepare a custom proposal — usually within 1 business day.
✓ No obligation, no pressure
✓ Response within 1 business day
✓ Includes a free gap analysis
Frequently Asked Questions
Common questions about our cloud cost optimization.
Most businesses are overspending by 20–35%. Common waste includes oversized instances, idle resources, on-demand pricing instead of reserved plans, and unoptimized storage.
Matching instance sizes to actual utilization. For example, moving a web server from a high-memory to general-purpose instance when usage is only 15%.
No. We analyze peak loads before recommending changes, implement in staged rollouts with monitoring, and can quickly revert any change showing negative impact.
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