Inflammatix

HealthCare Diagnostic Platform Achieves 64.8% Savings with AWS Cost Optimization for RDS & S3

74.8% Annual S3 Savings

Reduced storage spend by moving file versions to Intelligent-Tiering and Glacier Instant Retrieval.

46.6% Annual RDS Savings

Lowered database costs through instance upgrades, reservations, and scheduling.

677% ROI

Combined infrastructure optimization resulting in $31,080 in annual savings.

AWS Optimization Architecture

Healthcare Diagnostics Platform Cost Reduction Strategy

S3 Storage

Large Buckets

Intelligent-Tiering

Auto optimization

74.8%

Savings

RDS Right-Sizing

r5.large

Graviton

r6g.large upgrade

Efficient

Compute

STEADY WORKLOADS

On-Demand

4 Reserved

1-year commitment

Up to 72%

predictable usage

Dev/Test

24/7 Running

Scheduled

~15 hrs/day

No idle

Cost

Total cost reduction

64.8%

Combined Optimizations

Storage tiering & archival
Right-sized compute instances
Reserved capacity commitments
Automated resource scheduling

Industry

Healthcare & Life Sciences

Biotechnology Research

Provided Services

AWS Cost Optimization

RDS Optimization & Modernization

S3 Storage Optimization

Tech Stack

Amazon S3
Amazon RDS
AWS Instance Scheduler / EventBridge Scheduler Reserved Instances (RI)

Project Duration

1 week

[ client/ ]

HealthCare Diagnostic Equipment; Data analytics platform with growing storage and database spend.

Our client is a healthcare diagnostic equipment provider operating a data analytics platform that processes and stores large volumes of medical data.

As the platform grew, so did infrastructure costs—especially for AWS S3 storage and RDS database workloads.
MEV created two software solutions that made visualization and analysis fast and easy and sales message delivery effective.

Let’s Optimize Your AWS Spend

Our team has delivered AWS cost reductions of 30%–89% across healthcare, SaaS, and data analytics platforms – often with immediate ROI.

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[ challenges/ ]

The Core Challenges Solved

The client requested AWS cost optimization support. Monthly AWS costs were trending up due to:

C1:

High S3 storage usage with mixed access patterns

C2:

Under-optimized RDS instance types and utilization

C3:

Always-on clusters that didn’t match business hours

C4:

No reservations in place for steady workloads

[ how we did it/ ]

Solution & Implementation

The client requested AWS cost optimization support. Monthly AWS costs were trending up due to:

S1:

S3 optimization – 74.8% annual cost reduction

Moved largest buckets’ current file versions to Intelligent-Tiering to auto-optimize for access patterns.
Shifted old file versions in the biggest buckets to Glacier Instant Retrieval for cold-ish data.

S2:

RDS optimization – 46.6% cost reduction

Upgraded all r5.large RDS to r6g.large (Graviton).
Purchased 4 Reserved Instances (for subspace & acs clusters) to lock in lower rates.
Implemented start/stop schedules for 2 instances in the idbms cluster (weekdays, ~15 hrs/day).

AWS Cost Optimization - Key Approaches

Cutting infrastructure spend can be done in different ways—even small steps matter. A few proven approaches include:

01:

Right-Sizing Instances - match compute resources to real workload needs, avoiding over-provisioning.

02:

Leveraging Reserved & Spot Instances - lock in lower rates for predictable workloads or tap into deeply discounted spare capacity.

03:

Storage Tiering & Lifecycle Policies - use S3 Intelligent-Tiering, Glacier, and automated lifecycle rules to move data to cheaper storage classes.

04:

Scheduling Non-Critical Resources - automatically shut down dev, test, or analytics environments outside working hours.

05:

Monitoring & Continuous Optimization - use AWS Cost Explorer, CloudWatch, and third-party tools to track usage and adjust over time.

With the right combination of these tactics, companies can cut infrastructure costs significantly without compromising performance.

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