Migration & Modernization

How ExxonMobil reduced cloud costs with an AWS OLA

For energy companies like ExxonMobil, cloud costs rise as systems grow harder to manage and resources go underutilized. As the largest U.S. based oil and gas company by revenue, ExxonMobil operates a complex mix of on-premises and cloud workloads where infrastructure provisioned for reliability often costs more than it should. To address this, ExxonMobil conducted an AWS Optimization and Licensing Assessment (AWS OLA), a no-cost program that uses data-driven rightsizing recommendations to reduce costs without affecting performance. The assessment addressed compute and storage efficiency, licensing economics, and database modernization in a single engagement. In this post, we walk through how ExxonMobil used the AWS OLA to identify savings across compute, licensing, storage, and databases, and how you can apply the same approach to your organization.

The challenge

ExxonMobil’s environment reflects what many large energy operators face: a mix of on-premises and cloud workloads, legacy licensing agreements, and infrastructure sized for peak reliability that remains long after it’s needed. Several factors drove the need to act:

  • Computing instances running below optimal utilization
  • Microsoft Windows Server, Microsoft SQL Server, and Oracle licensing models misaligning with actual cloud usage
  • Availability Zone distribution creating inefficiencies in Amazon Elastic Compute Cloud (Amazon EC2) Dedicated Host packing and SQL Server core licensing
  • Limited visibility across accounts, making it hard to identify where inefficiencies exist
  • On-premises Exadata hardware approaching refresh cycles, creating pressure to act before costs escalate

The AWS OLA engagement

ExxonMobil’s engagement ran across three parallel workstreams, each targeting a distinct layer of the infrastructure.

Lift-and-shift assessment

AWS Professional Services and Evolve Cloud Services, an AWS OLA licensing partner, targeted on-premises servers not yet migrated to AWS. The AWS OLA mapped servers to appropriate Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Relational Database Service (Amazon RDS) types using rightsizing data for cost and performance optimization.

Post-migration optimization

For workloads already on AWS, a key finding involved Availability Zone separation. When SQL Server Enterprise workloads spread across multiple Availability Zones, Amazon EC2 Dedicated Hosts cannot pack efficiently enough to license by physical core. This drives up SQL Server core license counts. The AZ analysis showed that grouping workloads under a single Availability Zone reduces both SQL Server Enterprise and SQL Server Standard core counts, unlocking licensing savings.

Oracle modernization

ExxonMobil sought to avoid an Exadata hardware refresh and optimize costs ahead of its renewal cycle. The AWS OLA modeled two paths: Amazon Relational Database Service (Amazon RDS) with multi-tenant consolidation, and a hybrid Amazon RDS and Amazon EC2 approach with pluggable database (PDB) consolidation. Both options removed hardware dependency and provided flexibility across managed and self-managed platforms, with the hybrid approach delivering the greater cost reduction.

Validation and ownership

Following the AWS OLA engagement, ExxonMobil worked with its AWS account team to conduct a rightsizing initiative on existing AWS workloads, identifying annualized savings while maintaining performance across its portfolio.

ExxonMobil verified the results by analyzing AWS Cost and Usage Reports (AWS CUR) directly. The realized savings aligned closely with AWS Compute Optimizer projections, confirming the accuracy of the recommendations and giving the team confidence in the process. That independent validation allowed ExxonMobil to build its own impact summary for leadership, taking ownership of the results rather than relying on AWS-generated reporting alone.

The AWS account team provided Amazon Athena queries for cost tracking, methodology guidance, and implementation support throughout, with the intent of leaving ExxonMobil equipped to continue optimizing independently.

The following query tracks EC2 instance costs by account and month:

SELECT line_item_usage_account_id AS account_id, YEAR(line_item_usage_start_date) AS year, MONTH(line_item_usage_start_date) AS month, line_item_resource_id AS instance_id, product_instance_type, product_region, line_item_usage_type, line_item_line_item_type, SUM(line_item_unblended_cost) AS total_unblended_cost, SUM(line_item_usage_amount) AS total_usage_hoursFROM your_cur_database.your_cur_table --replace this with your table nameWHERE line_item_product_code = 'AmazonEC2' AND product_instance_type != '' AND line_item_resource_id LIKE 'i-%' AND line_item_line_item_type NOT IN ('Credit', 'Refund', 'Tax')GROUP BY line_item_usage_account_id, YEAR(line_item_usage_start_date), MONTH(line_item_usage_start_date), line_item_resource_id, product_instance_type, product_region, line_item_usage_type, line_item_line_item_typeHAVING SUM(line_item_unblended_cost) > 0ORDER BY year DESC, month DESC, total_unblended_cost DESC

Following the initial engagement, ExxonMobil identified additional opportunities and is planning a second round of rightsizing in 2026. That’s the pattern AWS OLA supports.

Applying this to your organization

ExxonMobil’s engagement offers a framework for energy enterprises managing aging infrastructure (both compute and storage), rising operational costs, and licensing complexity across cloud and on-premises environments. The AWS OLA framework, combining rightsizing, licensing analysis, and modernization modeling, applies to organizations of any scale running Windows Server, SQL Server, or Oracle workloads on-premises (e.g VMware), other cloud providers, or on existing AWS environments. Whether you manage hundreds or thousands of servers, or handle high volumes of attached and detached storage, the structured approach ExxonMobil employed demonstrates that optimization at scale is achievable with the right assessment, partnerships, and commitment to execution. Licensing is frequently overlooked in cloud cost conversations, yet it represents a significant and fixable portion of total cost of ownership. An AWS OLA surfaces that opportunity with the data needed to act on it.

Connect with your AWS team

Contact your AWS account team or visit Migration and Modernization Partners to learn more about how AWS and its partners can help transform and optimize your infrastructure.

Conclusion

ExxonMobil’s experience shows that a structured, data-driven approach to cloud optimization can deliver real savings across compute, storage, licensing, and database workloads. By combining AWS OLA insights with internal validation and a commitment to ongoing rightsizing, ExxonMobil turned a one-time assessment into a repeatable optimization practice. If your organization is managing complex infrastructure across cloud and on-premises environments, here’s how to begin:

Evaluate your current state

Request an AWS Optimization and Licensing Assessment to understand your savings potential and licensing optimization opportunities.

Enable your data foundation

Turn on AWS Compute Optimizer across your accounts. Review your AWS Cost and Usage Reports (AWS CUR) to understand current spending patterns.

Identify your starting point

Select pilot workloads before expanding scope. Document your existing Windows Server, SQL Server, and Oracle licensing agreements so AWS OLA can factor your license position into its recommendations.

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