How We Helped a SaaS Client Cut Their AWS Bill by 60% in 30 Days

Aug 9
3 min read

At Ananta Cloud, we often work with fast-growing startups and mid-size tech companies that have one thing in common: they’re moving fast—and their AWS bill shows it.

Recently, a SaaS client came to us concerned about their ballooning cloud costs. Their traffic had grown modestly, but their AWS bill had spiked to over $3,400/month. It was clear they weren’t scaling efficiently.

In under 30 days, we helped them cut that bill down to $1,380/month—a 60% reduction with zero impact on performance or reliability.

Here’s exactly how we did it—and how you can apply the same strategies to your own AWS environment.

Step 1: Audit and Analyze

We kicked off with a detailed audit using:

AWS Cost Explorer
Trusted Advisor
CloudWatch metrics
Compute Optimizer

We uncovered several key issues:

Over-provisioned EC2 and RDS instances
Everything running on on-demand pricing
Dozens of unused EBS volumes, AMIs, and Elastic IPs
Unoptimized S3 storage with no lifecycle rules
CloudWatch logs accumulating indefinitely

In short, cloud sprawl had taken over.

Step 2: Implement Savings Plans and Reserved Instances

The client was using on-demand pricing across the board—convenient, but expensive.

What We Did:

Purchased a 1-year Compute Savings Plan covering core EC2 usage
Reserved instances for stable RDS workloads

Monthly Savings: ~$700

Tip: Use Compute Savings Plans for flexibility and easier coverage across instance types and regions.

Right-Size Compute and Database Resources

Most workloads were dramatically over-provisioned. Using CloudWatch metrics and Compute Optimizer, we tailored instance sizes to actual usage.

What We Did:

Replaced m5.large EC2 instances with t3.medium in dev and staging
Reduced RDS instance size and disabled multi-AZ in non-critical environments
Added Auto Scaling for production services

Monthly Savings: ~$400

Tip: Monitor CPU, memory, and IOPS to identify what’s actually needed.

Step 4: Eliminate Zombie Resources

Orphaned cloud assets are one of the biggest hidden costs in AWS.

What We Did:

Deleted unused EBS volumes, Elastic IPs, and load balancers
Cleaned up stale AMIs
Set retention policies for CloudWatch logs
Applied tagging strategy to improve future visibility

Monthly Savings: ~$250

Tip: Schedule monthly cost hygiene reviews to avoid silent bloat.

Optimize S3 Storage

The client’s S3 usage had no lifecycle policies—backups and logs were sitting in Standard storage indefinitely.

What We Did:

Moved infrequently accessed data to S3 Intelligent-Tiering
Archived older backups to Glacier Deep Archive
Applied data lifecycle rules for logs and media assets

Monthly Savings: ~$150

Tip: S3 tiers can reduce costs significantly—especially if you’re storing large, rarely accessed files.

The Results

Metric	Before	After
Monthly AWS Bill	~$3,400	~$1,380
Time to Optimize	—	< 30 days
Performance	—	No impact
Uptime	—	100%

We reduced their AWS bill by 60%, while improving cost visibility, governance, and cloud hygiene.

Bonus Tactics for Continuous Savings

To make the cost savings stick, we are also:

Enabled budgets and cost alerts
Set up automated tagging and resource tracking
Trained the client’s dev team on cost-aware deployment practices

Cloud cost optimization is not a one-time fix—it’s a continuous process.

Final Thoughts

At Ananta Cloud, we help teams go from “just make it work” to “make it work efficiently.” AWS offers powerful tools, but without strategy, waste is inevitable.

If your cloud costs are growing faster than your user base, it’s time to take control.