Amazon Quick Supports FinOps Workflow Automation via CUDOS Dashboards

Limitations of CUDOS and the Rise of Amazon Quick

CUDOS, the core of Cloud Intelligence Dashboards (CID), is an open-source framework that visualizes AWS CUR data, providing cost visibility through a serverless architecture. However, in practice, efficiency was hindered by barriers to entry due to complex data structures, difficulties in cross-analysis, and manual reporting tasks repeated every month.

In October 2025, the existing QuickSight evolved into Amazon Quick Suite, adding generative AI capabilities. In particular, features such as Quick Chat, Quick Flows, and Quick Research allow users to intuitively explore CUDOS data and automate complex analyses through a natural language interface.

Natural Language-Based Analysis and Visualization

Users can select CUDOS data in Quick Chat and ask questions such as "RDS cost trends over the last 3 months" or "Analysis of accounts with cost spikes." Amazon Quick presents key insights, including RI/SP coverage and instance families, along with optimization recommendations. Additionally, analysis results can be converted into integrated visualizations, such as monthly trends or account-level comparisons, and shared instantly via Slack or Teams, speeding up decision-making within the organization.

Automation of Repetitive Tasks and In-Depth Research

Using Quick Flows, tasks such as monthly cost summaries or anomalous cost checks can be automated without coding. By generating flows in natural language and setting up scheduled triggers, reports are automatically generated at specified times and sent to Slack. This allows FinOps practitioners to move beyond simple data collection and focus on discovering optimization opportunities.

Quick Research generates in-depth reports with cited sources using only natural language questions, without the need for SQL or complex filters. It performs deep investigations, such as analyzing the causes of cost spikes for specific accounts or services, supporting the establishment of clear, data-driven action plans.