Using AWS Tools to Support FinOps in the Cloud

Digital Team
6 days ago
3 min read

Understanding AWS’s approach to cloud cost management

As cloud environments grow in complexity, organisations are seeking new ways to gain visibility into costs and improve financial accountability. One approach gaining traction is FinOps—a framework for managing cloud spending that brings together engineering, finance and operations.

This article explores how AWS tools and services can support a FinOps strategy. It outlines what AWS currently offers, from cost tracking tools to emerging AI-based solutions, and suggests how these capabilities may help organisations make more informed decisions, improve cost efficiency, and build collaborative workflows.

1. Exploring AI-driven FinOps with Amazon Bedrock and Nova

Amazon Bedrock allows organisations to create AI agents using AWS foundation models such as Amazon Nova. These models are designed to perform a range of tasks, including summarisation, cost forecasting and complex analysis. Nova comes in several formats (e.g., Micro, Lite, Pro) and is tailored for business and enterprise use.

Organisations interested in advanced, AI-supported FinOps workflows may consider using these tools to:

Summarise detailed billing data
Project future spending based on historical patterns
Suggest optimisation steps using custom logic

Nova’s pricing and performance are positioned to support larger-scale FinOps efforts, but organisations should assess whether its capabilities align with their internal needs and security policies.

2. Multi-agent architecture for FinOps use cases

AWS has introduced multi-agent support in Bedrock, enabling different AI agents to collaborate on tasks. A typical FinOps setup could involve:

A supervisor agent to manage user queries
A cost analysis agent that connects with AWS Cost Explorer
A cost optimisation agent that accesses AWS Trusted Advisor

This model allows for task-specific processing. For example, if a user asks about last month’s spending and savings opportunities, the query can be divided between agents and answered with a combination of historical data and real-time insights.

3. Implementing access control and secure interfaces

Organisations adopting FinOps on AWS may consider using Amazon Cognito to manage access. This service supports role-based access control, ensuring only approved users interact with cost data or optimisation agents. For teams building internal dashboards, AWS Amplify can be used to deploy secure front-end interfaces.

4. Automating actions with Lambda and cost tools

Automation is another feature supported by AWS. Lambda functions can be linked to Bedrock agents to perform tasks such as:

Querying cost trends
Maintaining date and time context
Providing spending forecasts via Cost Explorer
Retrieving optimisation recommendations from Trusted Advisor

These components may help teams reduce manual work and improve response times when handling FinOps queries.

5. Tools for visibility and analysis

AWS Cost Explorer and AWS Budgets allow users to track spending, compare across services, and make projections. These tools support real-time monitoring and trend analysis, potentially reducing the risk of overspending or delayed action.

AWS users can consider these tools if they are looking for:

Daily or monthly cost summaries
Alerts for unusual usage patterns
Comparisons between planned and actual spend

6. Tagging to support accountability and cost allocation

Tagging is a core FinOps practice. AWS supports native tagging capabilities that help identify who is using cloud resources and for what purpose. By applying tags consistently at the point of resource creation, teams can:

Track usage by department or service line
Identify underutilised infrastructure
Enable cost-sharing through showback or chargeback models

Monitoring tag compliance is also possible using AWS automation tools.

7. Deploying a FinOps prototype with CloudFormation

To speed up experimentation or deployment, AWS provides a CloudFormation template that sets up key resources:

Bedrock agents
Lambda functions
Cognito pools
IAM roles

Organisations can use this template to test FinOps workflows in a controlled environment before wider rollout. Adjustments may be needed depending on region, security requirements, or scale.

8. User experience and workflow integration

Once deployed, the system can provide a conversational interface for FinOps queries. For example, users may ask:

"What were my top spending services in March?"
"Where are savings opportunities based on Trusted Advisor data?"

Results can be returned in real-time, giving finance and engineering teams actionable insights. AWS recommends integrating these tools with standard workflows, and they can be adapted based on internal processes.

AWS tools as potential FinOps enablers

AWS offers a growing number of services that may assist with FinOps adoption. These include well-established tools like Cost Explorer and Budgets, as well as more recent innovations such as Bedrock and Nova for AI-powered workflows.

While not every organisation will need all components, teams looking to improve cost visibility, automate financial operations, or experiment with AI in cloud finance may find value in exploring these options.

As always, careful testing, security review, and internal alignment are recommended before deploying FinOps tools at scale.

Want more tips like this? Subscribe to GJC articles for insights on FinOps practices, AWS cloud strategy, and digital optimisation trends.

See: https://www.georgejamesconsulting.com/