How to apply data masking while exposing data through an API?

With Talos, you can mask the data for the API endpoint by defining user groups on their segments and dimensions.

1. To create the user groups, define the user groups in config.yaml, as shown below:

   name: employee
   description: A talos app
   version: 0.0.1
   logLevel: DEBUG
   auth:
       heimdallUrl: https://liberal-donkey.dataos.app/heimdall
       userGroups: 
       - name : intern
         description: intern group
         includes: # Users to include in this group
           - users:id:iamgroot
         excludes: # Users to exclude from this group
           - users:id:blackwidow
       - name : datadev
         description: data dev group
         includes: # Users to include in this group
           - roles:id:data-dev
   
   metrics:
     type: summary
     percentiles: [ 0.5, 0.75, 0.95, 0.98, 0.99, 0.999 ]
   rateLimit:
     enabled: true
     options:
       interval:
         min: 1
       max: 100
       delayAfter: 4
   cors:
     enabled: true
     options:
       origin: 'https://google.com'
       allowMethods: 'GET'  
   cachePath: tmp       
   sources:
     - name: pg 
       type: pg
       connection:
         host: pg-db
         port: 5432
         user: postgres
         password: '12345'
         database: employee
   

2. Customize your SQL query in the department.sql example according to the user group as shown below:

   SELECT
       -- dynamic data masking
       id,
       department,
       last_name,
       company_role,
       -- column level security
       {% if context.user.userGroup == 'datadev' %}
           annual_salary
       {% else %}
           NULL AS annual_salary
       {% endif %}
   FROM departments
   

3. Update department.yaml to activate the user groups as shown below:

   urlPath: /departments
   description: Get a list of departments
   source: pg
   allow:
     - intern
     - datadev
   filters:
     - description: Allow only certain department
       userGroups:
         - reader
         - default
     - description: Indian Content Only
       userGroups:
         - asian
         - indian
   depends:
     - table: departments
       columns:
         - IT
         - Finance
   

4. Descriptions for filters explain how various user groups will access content. This improves the API documentation by offering clear guidance for users interacting with the API.

5. External dependencies, such as tables and columns, have been included to clarify what the API relies on. This adds context to the API documentation, helping users better understand the data sources involved.

Now you are ready to expose your data via APIs securly.