
k9-ownership-byod-setup
โ 139by datadog-labs ยท part of datadog-labs/agent-skills
Generate a BYOD ownership preferences reference table for a customer. Walks through preference types, generates CSV, and provides upload instructions (UI, API, cloud storage, or Terraform). Use when asked about BYOD setup, preferences reference table, k9_ownership_preferences, or ownership customization.
This is the playbook your agent receives when the skill activates โ you don't need to read it to use the skill, but it's here to audit before installing.
BYOD Preferences Reference Table Setup
Help customers create and upload a k9_ownership_preferences reference table to customize how the Ownership Agent determines resource owners.
Read first
references/schema.mdโ full schema, column details, validation rules, and per-type examplesassets/example.csvโ complete working CSV with all three preference types
Overview
The Ownership Agent infers owners for cloud resources with security findings. Ownership preferences let customers customize this by providing rules in a Datadog reference table. The agent reads them automatically.
With preferences you can:
- Map tags to owners: Resources with specific tag values belong to a particular team or person
- Exclude accounts: Prevent bot accounts or shared infrastructure from appearing as owners
- Provide custom guidance: Give the AI engine organization-specific context
Reference Table Details
- Table name:
k9_ownership_preferences(exact name, must match) - Effect delay: Changes take effect within 24 hours of upload
- Schema: 12 columns, all STRING โ see
references/schema.mdfor details
Workflow
Step 1: Determine Needs
Ask the customer:
- Tag mappings: "Do you have tags on your cloud resources that indicate ownership? (e.g.,
cost-center,team,project)" - Exclusions: "Are there bot accounts, service accounts, or shared accounts that should never appear as owners?"
- Prompt text: "Any organization-specific context that would help determine ownership? (e.g., naming conventions, team structure)"
Step 2: Generate CSV
Read references/schema.md for the full column spec and assets/example.csv for a working template. Build a CSV with all 12 column headers. Each row gets a unique sequential id and fills columns relevant to its preference_type, leaving the rest empty.
Step 3: Upload Instructions
Option A โ CSV Upload (UI):
- Go to Integrations > Reference Tables in Datadog
- Click New Reference Table
- Upload the CSV
- Set table name to
k9_ownership_preferences - Choose primary key:
preference_type, tag_key, tag_value, handle - Save
Manual uploads support files up to 4 MB.
Option B โ Cloud Storage Sync (S3, Azure Blob, GCS): Best for automated, recurring updates. Store your CSV in a cloud storage bucket and Datadog periodically imports it.
- Upload CSV to S3 / Azure Blob / GCS
- In Datadog, go to Integrations > Reference Tables
- Click New Reference Table, select Cloud Storage as source
- Provide storage path and credentials
- Set table name to
k9_ownership_preferences - Datadog re-imports the file periodically
Cloud storage uploads support files up to 200 MB.
Option C โ Terraform:
Use the datadog_reference_table resource in the Datadog Terraform provider to manage the table as infrastructure-as-code.
Option D โ API: You can manage reference tables programmatically through the Reference Tables API. See the API documentation for available endpoints. Replace the API domain with your Datadog site URL if applicable.
Step 4: Verify
Changes take effect within 24 hours. To verify:
- Identify a resource that matches one of your tag mappings
- After 24 hours, check the ownership suggestion for that resource in the Datadog UI
- The suggested owner should reflect your configured mapping
Key Behaviors
- Case-insensitive matching: Tag keys, tag values, handles, exclusion types, and resource types are all matched case-insensitively
- AND-logic exclusions: All non-empty exclusion fields must match. Empty fields act as wildcards
- Tag mappings complement, not override: Direct ownership indicators (like
team:orservice:tags) take precedence. Tag mappings augment, not replace - Graceful degradation: If the table doesn't exist or is empty, ownership detection works normally without preferences
- Empty table clears preferences: Deleting all rows or deleting the table causes cached preferences to expire and be left empty
- All-or-nothing validation: Any validation failure rejects the entire preference set for that cycle
npx skills add https://github.com/datadog-labs/agent-skills --skill k9-ownership-byod-setupRun this in your project โ your agent picks the skill up automatically.
Troubleshooting
| Problem | Likely cause | Fix |
|---|---|---|
| Preferences not taking effect after 24h | Table name is wrong | Must be exactly k9_ownership_preferences |
| Preferences not taking effect after 24h | Missing column headers | All 12 columns must exist as CSV headers |
| Preferences not taking effect after 24h | Feature not enabled for org | Contact support to enable ownership preferences |
| All preferences rejected | Invalid characters | See references/schema.md Allowed Characters. No angle brackets, curly braces, or pipes |
| All preferences rejected | Missing required field | Check required fields for each preference type in references/schema.md |
| All preferences rejected | Duplicate or conflicting rows | See Duplicate Detection in references/schema.md |
| All preferences rejected | Size limit exceeded | 50 tag mappings, 20 exclusions, 3 prompt texts. 1024 bytes/field, 4096/prompt |
| Tag mapping not matching | Spelling mismatch | Matching is case-insensitive but verify exact tag key/value on resource |
| Exclusion not applying | Scoping too narrow | All non-empty fields must match (AND). Leave filters empty for broad exclusions |
| Preferences cleared unexpectedly | Table emptied or deleted | Both cause cached preferences to expire. Upload a valid CSV to restore |
Licensed under MITโ you can use, modify, and redistribute it under that license's terms.
View the full license file on GitHub โ