Automated AWS Resource Tag Compliance Validation Using Amazon Quick Flows
Durai Krishnan, Abhi Patlolla, Arun Chellappa Ganesan, Siraj Gadne
Amazon Web Services
Use Case and Problem
Maintaining consistent and accurate AWS resource tagging is a persistent challenge for organizations managing multi-account environments. As cloud footprints grow, manual tag audits become impractical — resources get tagged incorrectly, tags drift from approved values, and compliance gaps widen silently.
Each AWS account is assigned specific valid cost allocation tag values (e.g., application IDs, cost center codes, or project identifiers) that map resources to business units and cost centers. These tags are critical for accurate chargeback, showback, and financial reporting. Common issues include:
• Misassigned tags — a resource is tagged with a value that belongs to a different account
• Invalid tag values — typos or deprecated codes that don’t exist in the master mapping
• Missing tags — resources with no cost allocation tags at all
This article shows how to use Amazon Quick Flows to automate cost allocation tag compliance validation — comparing live resource tagging data from a CUDOS dashboard against a master tag-to-account mapping, classifying resources by compliance status, generating an actionable report, and delivering it to stakeholders on a recurring schedule — all without writing a single line of code.
How to Solve the Problem
This solution uses three core components working together:
| Component | Role |
|---|---|
| CUDOS Dashboard | Provides live resource tagging data — no manual exports needed |
| Amazon Quick Space | Central hub for the master mapping file and the linked CUDOS dashboard |
| Amazon Quick Flow | Orchestrates validation logic: retrieval → comparison → classification → reporting → delivery |
How It Works
Figure 1: End-to-end flow architecture
Prerequisites
• Amazon Quick access (Quick Pro or Enterprise edition)
• Email integration configured in Amazon Quick (e.g., Outlook)
• Access to your organization’s CUDOS dashboard in Quick for live resource tagging data
• A master tag-to-account mapping spreadsheet (or equivalent source of truth)
Step 1: Prepare the Master Data File
Export your valid tag-to-account mappings from your authoritative source (finance system, governance spreadsheet, CMDB, etc.). The CSV should contain at minimum these columns:
| Column | Description | Example |
|---|---|---|
| account_id | 12-digit AWS account ID | 123456789012 |
| valid_tag_value | Approved cost allocation tag value for this account | APP-0046 |
| business_unit | Business unit the account belongs to | Engineering |
Save this as master_data.csv. Each row represents a valid (account, tag value) combination. Adapt the column names and tag format to match your organization’s naming conventions.
Step 2: Create the Quick Space
1. Open Amazon Quick → Spaces (left sidebar)
2. Click Create Space and name it descriptively (e.g., “Tagging Validation - Data”)
3. Upload master_data.csv to the space (Add resource → Upload file)
4. Link the CUDOS dashboard: Add resource → Browse Quick assets → Dashboard tab → select CUDOS → Add
Important: The user running the flow must have direct access to the CUDOS dashboard. Space sharing does not automatically grant dashboard access.
Step 3: Create the Quick Flow
Navigate to Flows in the left sidebar, click Create Flow, and provide a prompt that defines the validation logic. The flow should perform these steps:
1. Retrieve Master Data: Read master_data.csv from the Quick Space. Retrieve ALL rows.
2. Retrieve Current Tags: Query the linked CUDOS dashboard for resource identifier, account ID, tag value, and account name.
3. Validate and Classify: Compare every resource against the master data. Classify into: Compliant, Invalid Tag for Account, Invalid Tag Value, or Missing Tag.
4. Generate Report: Create a compliance report with executive summary, category breakdown, business unit breakdown, detailed findings, and compliance score.
5. Email Report: Send the report via email with a subject line including the current date.
Compliance Classification Rules
| Category | Criteria |
|---|---|
 Compliant |
Resource has a tag AND the (account_id, tag_value) combination exists in master data |
 Invalid Tag for Account |
Tag value exists in master data but is not valid for this specific account |
| Invalid Tag Value |
Tag value does not exist anywhere in the master data |
 Missing Tag |
Resource has no cost allocation tag value |
Step 4: Configure and Test
• Click on each Quick Data step and verify it points to your Space
• Run the flow manually with your email address as input
• Check your inbox for the compliance report
• Spot-check a few resources against the master spreadsheet for accuracy
Tip: If the validation step misses resources, edit its prompt and add: “Process ALL rows. Do not skip any. Do not summarize.”
Step 5: Set Up a Recurring Schedule
In Run mode, click the scheduling icon (clock), then Create schedule. Configure a weekly run (e.g., Monday at 8:00 AM) with your team distribution list as the default email. Enable “Run with no confirmation” for fully automated operation.
Troubleshooting
| Issue | Resolution |
|---|---|
| Quick Data returns no data found | Verify the Space name matches exactly |
| Dashboard not visible in Space browser | Ensure you have Quick access — Space sharing doesn’t grant it |
| Validation misses resources | Edit the validation prompt: add Process ALL rows, do not skip any |
| Email not received | Check email integration in Quick settings |
| Report is truncated | Add: Summarize compliant, list all non-compliant individually |
Conclusion
Using Amazon Quick Flows, you can transform a manual, error-prone tagging audit into an automated, recurring compliance check that runs on schedule and delivers actionable results. The entire solution requires no code — just a well-structured prompt, a master data file, and a linked CUDOS dashboard.
About the Authors
Durai Krishnan is a Senior Customer Solution Manager at Amazon Web Services (AWS) with 26 years of rich background in consulting and leadership. Durai specializes in guiding customers through their cloud journey, focusing on migration, modernization, and cost optimization strategies.
Abhi Patlolla is a Sr. Solutions Architect based out of the NYC region, helping users in their cloud transformation, AI/ML, and data initiatives.
Arun Chellappa Ganesan is a Senior Customer Solutions Manager with Amazon Web Services. Arun drives customer success through accelerated GenAI adoption, business value realization, and organizational change management across GenAI and Agentic AI transformation initiatives.
Siraj Gadne is a Customer Solutions Leader at Amazon Web Services. He is passionate about helping customers maximize the benefits of cloud adoption through migration, modernization, and transformation.