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Policy Cover
Datazone’s policy system provides flexible, fine-grained access control through role-based permissions. Policies define what actions users can perform on resources, supporting both flat and hierarchical resource patterns with explicit allow/deny rules.

Key Features

  • Role-based: Policies are bound to roles, not individual users
  • Hierarchical: Support for project-scoped resources (e.g., project:<id>:dataset:*)
  • Explicit deny: Deny statements override allow statements
  • Extra constraints: Resource-specific restrictions (row-level security, column filtering, path prefixes)
  • Wildcard support: Use * for flexible matching across resources and actions
  • Branch-aware: Optional branch specification for version control
Policy Diagram

Policy Structure

Each policy consists of one or more statements that define access rules:

Fields

Resource Patterns

Resources follow a hierarchical pattern that supports various levels of specificity:

Flat Resources

Hierarchical Resources

Hierarchical patterns enable project-scoped permissions:

Supported Resource Types

  • dataset - Data tables in the lakehouse
  • project - Project containers
  • view - Virtual views over datasets
  • schedule - Automated execution schedules
  • extract - Data ingestion jobs
  • compute - Compute resources
  • api_key - API authentication keys
  • user - User accounts
  • role - User roles
  • notebook - Interactive analysis notebooks
  • pipeline - Data transformation pipelines
  • endpoint - REST API endpoints
  • intelligent_app - Dashboard applications
  • variable - Environment variables
  • agent - AI agents
  • action - Executable actions
  • organisation - Organisation-level administration
  • orion - Orion logs
  • source - Data source connections
  • notification - Notification channels and settings
  • tag - Resource tags

Actions

Actions follow the <resource>:<action> format and define what operations can be performed:

Action Patterns

  • dataset:read - Read access to datasets
  • dataset:write - Modify datasets
  • dataset:delete - Delete datasets
  • dataset:execute - Execute operations on datasets
  • dataset:manage - Full management access
  • dataset:create - Create new datasets
  • dataset:* - All dataset actions
  • *:read - Read access to all resources
  • *:* - All actions on all resources

Common Actions

Exceptional Actions

Some resources support custom actions beyond the standard CRUD operations:
  • project:read_repository - Read access to project code repository
  • project:write_repository - Write access to project code repository (push commits, merge pull requests)
  • project:pr_create - Permission to open a pull request targeting a branch
  • project:deploy - Permission to deploy a project
  • endpoint:invoke - Permission to call an API endpoint
  • agent:ask - Permission to ask (query) an AI agent

Manage Permissions and Settings Access

Some parts of the application — mainly the Settings area — are gated by the manage action rather than by read. A user who holds <resource>:manage sees that resource’s menu in Settings and can view its entries. manage grants visibility only. It does not imply creating, editing, or deleting — grant <resource>:create, <resource>:write, or <resource>:delete alongside it for those operations. Previously these areas were visible only to users with organisation:manage. Now each resource can be delegated independently, so you can grant access to a single Settings menu without handing over organisation-wide administration.

Resources that support manage

Example: access to API keys and sources

This policy reveals the API Keys and Source menus in Settings without granting any other organisation administration:
The user can open both menus and see their contents. All other Settings menus stay hidden. Because API keys belong to the user who owns them, api_key:manage is enough to create and revoke their own keys. Sources are shared organisation resources, so this policy does not let them create or delete a source.

Example: adding source create permission

To let the same role also create sources, add source:create on the resource type:
Deleting or editing existing sources requires source:delete and source:write on the instances (for example source:*).
organisation:manage still implies access to every Settings menu. Use the per-resource manage actions when you want to delegate one area only.

Row-Level and Column-Level Security

Datazone supports fine-grained data access control through row-level and column-level restrictions using the extra_constraints field. This enables you to restrict what data users can see within a dataset or view, beyond just granting or denying access to the entire resource.

Extra Constraints Structure

For datasets and views, you can specify columnar constraints:

Fields

Row-Level Restrictions

Row-level restrictions apply SQL conditions to filter which rows a user can access:
When a user queries this dataset, these conditions are automatically appended to the WHERE clause:

Column-Level Restrictions

Column-level restrictions specify which columns users can access (allowlist):
Only the specified columns will be accessible in query results. All other columns will be filtered out automatically.

Combined Restrictions

You can use both row and column restrictions together:
Important Restrictions for Row/Column-Level Security:When using extra_constraints with row_level_restrictions or column_level_restrictions:
  1. Must target a specific resource: Use dataset:<object_id> or view:<object_id>, not wildcards like dataset:*
  2. Read-only actions: Only dataset:read or view:read actions are allowed
  3. Single action: Statement must contain exactly one action
  4. Single resource: Statement must target exactly one dataset or view
Invalid examples:
  • "resource": "dataset:*" (wildcard not allowed)
  • "actions": ["dataset:read", "dataset:write"] (multiple actions)
  • "actions": ["dataset:*"] (wildcard action not allowed)
  • "actions": ["dataset:write"] (write action not allowed)
Valid example:
  • "resource": "dataset:507f1f77bcf86cd799439011" with "actions": ["dataset:read"]

Policy Examples

Read-Only Access

Grant read access to all resources:

Dataset Admin

Full control over all datasets:

Project Admin

Full control over a specific project and all its resources:
This allows the user to:
  • Manage the project itself (project:*)
  • Create and manage all child resources (datasets, notebooks, pipelines, etc.)

Restricted Access with Deny

Allow read access to all datasets except one specific dataset:
Deny statements always override allow statements, regardless of order.

Project-Scoped Dataset Access

Grant access to datasets within a specific project only:

Branch Protection

Repository permissions can be scoped to a branch with the branch field. Combined with the separation between project:write_repository (pushing commits and merging pull requests) and project:pr_create (opening a pull request), this lets you protect a branch such as main while keeping the rest of the project fully editable.
How this evaluates: The result is a familiar protected-branch workflow: contributors work on feature branches and open pull requests into main, but nobody with this policy can push or merge into main directly. Grant merge rights to a separate reviewer role that is not denied project:write_repository on main.
project:pr_create is checked against the base branch of the pull request — the branch being merged into. To block pull requests into main entirely, add project:pr_create to the deny statement’s actions.

Data Analyst Role

Typical permissions for a data analyst:

Built-in Policies

Datazone provides several built-in policies for common use cases:

Admin Policy

Full access to all resources:

Best Practices

Policy Design

  1. Start restrictive: Begin with minimal permissions and add as needed
  2. Use hierarchical patterns: Organize permissions by project for better management
  3. Leverage deny sparingly: Use deny for exceptions to broad allow rules
  4. Document policies: Add clear descriptions to explain policy intent

Role Assignment

  1. Bind to roles only: Policies are assigned to roles, not individual users
  2. Create role hierarchies: Use multiple roles for different permission levels (Viewer, Editor, Admin)
  3. Audit regularly: Review policy assignments periodically

Performance

  1. Cache aware: Policies are cached; changes may take a few seconds to propagate
  2. Granular resources: Use specific resource IDs when possible to reduce evaluation complexity
  3. Minimize deny statements: They require checking all policies

Security

  1. Principle of least privilege: Grant only necessary permissions
  2. Explicit denies: Use deny statements to override broad allows for sensitive resources
  3. Extra constraints: Apply row-level and column-level security for sensitive data
  4. Path restrictions: Use path_prefix constraints to sandbox project access

Validation Rules

Policies are validated automatically to ensure correctness:

Action Format

  • Must follow <resource>:<action> pattern
  • Both parts must be lowercase with underscores
  • Wildcards allowed: *:*, dataset:*, *:read
Valid:
  • dataset:read
  • project:*
  • *:*
Invalid:
  • dataset (missing action)
  • Dataset:Read (uppercase)
  • read (missing resource)

Resource Pattern

  • Must be valid resource type or wildcard
  • ObjectIds must be valid MongoDB ObjectIds
  • Hierarchical patterns must follow parent:<id>:child format
Valid:
  • dataset:*
  • project:507f1f77bcf86cd799439011
  • project:507f1f77bcf86cd799439011:dataset:*
Invalid:
  • dataset:invalid-id
  • project::dataset:*

Action-Resource Matching

Actions must match the resource type they’re applied to:
Exception: Wildcard actions (*:*) can be used on any resource.

Troubleshooting

Permission Denied Errors

If you encounter permission denied errors:
  1. Check user roles: Verify the user has the appropriate role assigned
  2. Review policy statements: Ensure the policy includes the required action and resource
  3. Look for deny statements: Check if an explicit deny is overriding an allow
  4. Verify resource IDs: Ensure you’re using the correct resource identifier
  5. Check cache: Wait a few seconds for policy changes to propagate

Hierarchical Permissions Not Working

If project-scoped permissions aren’t working:
  1. Verify pattern format: Use project:<id>:* not project:*:<id>
  2. Check parent context: Ensure the resource creation includes project reference
  3. Review cache: Hierarchical relationships are cached; wait 5 minutes or invalidate cache
  4. Validate ObjectIds: All IDs must be valid MongoDB ObjectIds

Performance Issues

If policy evaluation is slow:
  1. Reduce policy complexity: Simplify nested hierarchies
  2. Use specific resources: Prefer dataset:<id> over broad wildcards when possible
  3. Monitor cache health: Ensure Redis is functioning properly
  4. Check database queries: Hierarchical policies should use cache, not database

Roles

Learn about role management and user assignment

Authentication

Understand authentication and token management

API Keys

Generate and manage API keys for programmatic access

Projects

Organize resources within projects