AWS FinOps CID/ CUDOS framework augmented with Gen AI capability | Rajesh Natesan | TCS Cloud Unit

Amazon Q overview:

Amazon Q in QuickSight allows to build advanced generative AI capabilities, build visualization dashboards, and complex calculations. question the datasets beyond the data presented in the dashboard, create data stories using natural language.

Amazon Q is powered by Amazon Bedrock to support Generative BI capabilities in Amazon QuickSight:

• AI-accelerated assisted dashboard authoring
• AI answers to questions of data on demand
• AI-assisted story telling

In this blog, I have integrated Amazon Q in QuickSight capabilities to demonstrate FinOps use cases.

Prerequisites:

• Existing AWS FinOps Cloud Intelligence Dashboards, CUDOS Datasets can be integrated with Q capabilities
• In case you are not using AWS native FinOps framework, I strongly recommend you configure AWS CID, CUDOS and other advanced dashboards.
• Enable Amazon QuickSight Admin or Author Pro access role, Admin Pro access will allow users to create dashboards and Q & A against the dataset through natural language. Reader Pro access will have access to only Q&A capabilities.
• In the following blog, AWS CUDOS, CID and Compute Optimizer dashboards are established, and Cost Explorer data sets are exported to QuickSight

Amazon Q in QuickSight integration with AWS FinOps enablement

In the following FinOps use cases, we will see how Amazon Q in QuickSight capabilities can be leveraged for FinOps use cases to increase the FinOps engineers’ productivity and experience.

1.       Data Stories

Data Stories offer narrative-driven analytics, transforming data into compelling, interactive stories. This feature enables users to create engaging visualizations, embed insights, and share actionable intelligence. Data Stories enhance communication, drive informed decision-making, and provide a seamless experience for both creators and consumers of data-driven content.

Use case 1: FinOps Optimization data stories and report creation using Amazon Q Gen AI Capability:

• For FinOps cost optimization, AWS QuickSight Data Stories can be leveraged to create compelling, narrative-driven analytics that transform complex cost data into actionable insights.
• Users can build interactive stories that highlight spending patterns, cost drivers, and optimization opportunities.
• These stories can be shared across the organization to foster a culture of cost consciousness and drive informed decision-making.
• By embedding visualizations and key insights, FinOps teams can communicate the impact of cost-saving strategies more effectively.

Creation of FinOps Optimization data stories:

Depiction below shows on how to navigate, select the datasets and establish data stories for this use case.

QuickSight > Data Stories > New Data Story

Build Stort > Description of FinOps data story > Add (Visuals, FinOps Dashboard) > Build

FinOps data story created by Q, then you can share the story with team.

View the story on the Stories main page and access later.

2.Scenarios

Empower users with tailored, interactive analytics experiences. This feature offers dynamic, context-aware insights, automating complex data workflows. Scenarios drive informed decision-making, streamline analytics processes, and provide a seamless, intuitive interface for both technical and non-technical users, revolutionizing data-driven strategies across organizations.

Use case 2: FinOps cost and usage insights and scenarios using Q Gen AI capability:

• In a FinOps cost optimization use case, AWS QuickSight Scenarios can be instrumental by providing customized, interactive analytics tailored to cost management.
• Users can create specific scenarios to analyze spending patterns, identify cost drivers, and forecast future expenses. This feature allows for dynamic, context-aware insights into resource utilization and cost efficiency.
• By automating complex data workflows related to cost data, QuickSight Scenarios enable FinOps teams to generate personalized dashboards and reports that highlight areas for optimization.

QuickSight > Scenarios > New Scenario > Select Data > Start Analysis

In this case I was looking for optimization and modernization, recommendation for implementation with Cloud Formation Template recommendations. Scenarios Feature has helped me to find out optimisation and modernisation opportunities, also narrow down to specific EC2 optimisation with Cloud Formation Template implementation approach.

3.Analyses

AWS QuickSight Analyses provide robust, interactive visualizations and dashboards that enable users to explore and interpret data with ease. This feature offers advanced analytics capabilities, including calculated fields, filters, and drill-down options. Users can create custom visualizations, apply machine learning insights, and share analyses across the organization. QuickSight Analyses facilitate data-driven decision-making, enhance collaboration, and ensure that stakeholders have access to real-time, actionable intelligence. The intuitive interface supports both technical and non-technical users, driving engagement and insights across diverse teams.

Use case 3: FinOps cost visibility dashboards using Q Gen AI capability

• AWS QuickSight Analyses can be leveraged to create comprehensive FinOps dashboards and reports by providing interactive, real-time visualizations of cost data.
• Users can build custom dashboards that track spending patterns, resource utilization, and cost optimization metrics. Advanced analytics capabilities allow for the application of filters, calculated fields, and machine learning insights to identify cost-saving opportunities.
• QuickSight Analyses enable stakeholders to drill down into data, explore trends, and make informed decisions. This feature supports collaboration, ensuring that FinOps teams and executives have access to up-to-date, actionable intelligence for effective cost management and financial optimization.

QuickSight > Analysis > New Analysis > Select DataSet ( “Summary View” of Cloud Spend - will be used for dashboard creation)

create new Analysis window, here we will enable Q Build Visual capability to create interactive dashboards with help of Amazon Q feature.

1. Build Visuals> Enter the analysis you want to perform Build > Add to Analysis

• In this use case, Entered the following in text window “create Top Spending Products in my account “ then Q created the visuals from the selected dataset (Summary View).
• Add the analysis to the dashboard, then publish the dashboard

4.Topics

AWS QuickSight Topics Q&A feature offers a natural language interface for users to query and explore data effortlessly. This capability allows users to ask questions in plain language, receiving intuitive, data-driven answers and visualizations. Topics enable the creation of curated datasets with predefined business contexts, enhancing the accuracy and relevance of responses. This feature supports ad-hoc analysis, fosters data literacy, and empowers users to uncover insights without requiring deep technical knowledge. QuickSight Topics Q&A drives engagement, simplifies complex data queries, and ensures that stakeholders can quickly access the information they need.

Use case 4: FinOps Q&A feature to ask questions on the usage and optimization insights using Q capability

• AWS QuickSight Topics Q&A can be leveraged for FinOps by enabling users to ask natural language questions about cost data, resource utilization, and financial metrics. This feature allows FinOps teams to quickly uncover insights, identify cost-saving opportunities, and make data-driven decisions without requiring deep technical expertise.
• Topics can be curated to include relevant financial datasets, ensuring accurate and context-aware responses. The Q&A interface supports ad-hoc analysis, fosters collaboration, and enhances data literacy across the organization.
• By simplifying complex queries, QuickSight Topics Q&A empowers stakeholders to access critical financial information effortlessly, driving efficient cost management and optimization strategies.

QuickSight > Topics > New Topics > Topic Name > Select Data Set

• FinOps Chat Q &A is ready, ask questions pertaining to the dataset has been selected, you can add additional data sets as required. This FinOps Q & A capability will help developers to query their specific usage insights and take an action on it.

Conclusion:

Amazon Q in QuickSight emerges as a powerful tool for offering a suite of features that transform complex cost data into actionable insights. Through Data Stories, users can create interactive narratives that highlight spending patterns, cost drivers, and optimisation opportunities, fostering a culture of cost consciousness across the organisation. Additionally, QuickSight Topics Q&A allows users to ask natural language questions about cost data, simplifying complex queries and driving data-driven decision-making. Overall, Amazon Q in QuickSight enhances financial data literacy, promotes collaboration, and supports informed decision-making in cost management.