Cost Optimization Strategies in AWS S3: How to Reduce Storage Costs Without Sacrificing Your Data

Discover how to optimize your AWS bill by using S3 storage classes and lifecycle policies. A real-world case of savings in large-scale backups.

Cloud storage is often perceived as a cheap and infinite resource. However, within the Cloud department at Aktios, we have observed a recurring trend: storage costs are silent. They grow month by month, gigabyte by gigabyte, until they become an alarming budget item that directly impacts companies’ operating margins.

Amazon S3 (Simple Storage Service) is one of the most robust and widely used AWS services, but its simplicity often leads to inefficient management. Many organizations treat S3 as a “junk drawer” where terabytes of information are dumped without a defined classification strategy.

In this technical article, we will explore how the different S3 storage classes (tiers) work, how to automate data movement using Lifecycle Policies, and we will analyze a real case in which a proper data architecture resulted in savings of more than 70% on the customer’s bill.

Understanding the Economics of Data: Not All Objects Are Worth the Same

To optimize costs, we must first understand that the value of data changes over time. A backup generated yesterday is critical and must be immediately accessible. That same backup, six months later, is probably only required for regulatory compliance and is rarely accessed.

AWS offers different storage classes designed for these life cycles. Choosing the right one is the foundation of cost savings.

1. S3 Standard: The Price of Immediacy

This is the default storage class. It offers high durability, availability, and performance with low latency.

• Ideal use: Hot data, static website content, cloud-native applications, and frequently accessed data.

• The problem: It is the most expensive option for long-term storage of data that is not accessed. Keeping years of historical data here is financially inefficient.

2. S3 Standard-Infrequent Access (S3 Standard-IA)

Designed for data that is not accessed often but still requires fast access when needed.

• Savings: Storage costs are approximately 40–50% lower than S3 Standard.

• Trade-off: AWS charges a small data retrieval fee (per-GB retrieval fee).

• Ideal use: Secondary backups, disaster recovery data, or historical data accessed monthly.

3. S3 Glacier y Glacier Deep Archive: Cold Storage

This is where the real savings for long-term retention data are achieved.

• S3 Glacier Flexible Retrieval: Very low costs (approximately 10% of the cost of Standard). Retrieval times range from minutes to hours.

• S3 Glacier Deep Archive: AWS’s lowest-cost option (approximately USD 0.00099/GB). Data retrieval can take 12–48 hours.

• Ideal use: Regulatory archiving (logs, invoices from previous years), “last-resort” backups, and legal retention for 5–10 years.

Technical note: Moving data to Glacier involves a trade-off. If you need to retrieve 50 TB at once from Deep Archive, retrieval costs and waiting time are critical factors to consider before archiving.

The Key Tool: S3 Lifecycle Policies

Savings are not achieved by manually moving data, but by automating data intelligence. S3 Lifecycle Policies are rules defined in JSON format or through the AWS console to instruct a bucket on how to behave.

A typical policy is structured around two actions:

1. Transition: Move objects to a cheaper storage class after a certain period (e.g., move to IA after 30 days).

2. Expiration: Delete objects that are no longer needed (e.g., delete logs after 365 days).

Success Case: Optimizing a 50 TB Backup Repository

From our experience in cost optimization projects (FinOps), we frequently encounter scenarios where the lack of data governance generates massive cost overruns.

Recently, we collaborated with a client in the industrial sector that used S3 as the primary repository for database and file system backups.

The initial scenario (The problem):

• Volume: 50 TB of data accumulated over 3 years.

• Class: All data stored in S3 Standard.

• Policy: None. Data was uploaded and never deleted or moved.

• Approximate cost: Around €1,150/month for storage alone (calculated based on the approximate Standard base price).

Aktios’ intervention:

After analyzing access patterns, we found that the client only restored backups from the last 7 days. Data older than one month had never been accessed, yet it was being paid for at a premium rate.

We implemented the following S3 Lifecycle Policy:

1. Day 0–30: Keep in S3 Standard (immediate and frequent access).

2. Day 31–90: Automatic transition to S3 Standard-IA (approximately 45% savings).

3. Day 90+: Transition to S3 Glacier Deep Archive (approximately 95% savings compared to Standard).

4. Day 365: Expiration (deletion) of non-critical files tagged with specific labels.

The result:

Thanks to the aggressive use of Deep Archive for the large volume of historical data (“cold data”), the storage bill for that specific bucket was drastically reduced.

The 50 TB, which previously cost more than €1,000/month, were reduced to a residual maintenance cost of less than €200/month once the policy stabilized, while keeping data security and durability fully intact.

Conclusion

Storage in AWS is flexible, but that flexibility requires governance. It is not just about storing data, but about understanding its useful life cycle. Implementing intelligent tiering not only reduces the monthly bill but also improves the security posture by forcing the organization to classify what is critical and what is expendable.

If your organization manages large volumes of data in S3 and your AWS bill continues to grow without a clear business justification, you are likely paying for performance (S3 Standard) that your older data does not need.

Would you like to analyze the state of your AWS infrastructure?

At Aktios, we can help you perform a cost audit and configure lifecycle policies that automate savings from day one.

Contact us