NetApp ActiveIQ API - Use Cases Overview¶

This document provides an overview of the use cases for NetApp ActiveIQ automation, now organized into specialized categories for better navigation and implementation guidance.

📁 Use Cases Organization¶

The use cases have been reorganized into two main categories:

🌐 NetApp API Use Cases¶

Standard Storage Operations - Core NetApp ActiveIQ API functionality:

• Storage provisioning and management (NFS file shares, LUN expansion)

• Resource management (decommissioning, cleanup procedures)

• Performance monitoring and analytics

• Tagging & annotation workflows (event annotation, SVM tagging, volume name tags)

• Metadata management (generic metadata attachment, search by metadata)

• Infrastructure operations and maintenance

🔧 MCP Tools Use Cases¶

Model Context Protocol Integration - Advanced DevOps workflows with MCP enhancement:

• Backup & Recovery with MCP-enhanced context and AI-assisted recovery

• Capacity Planning with AI forecasting and automated scaling

• Event Management with intelligent correlation and automated workflows

• Performance Analysis with AI-powered insights and predictive analytics

• SVM Management with automated provisioning and AI optimization

• Volume Operations with intelligent monitoring and automated optimization

Authentication¶

All NetApp ActiveIQ API requests require HTTP Basic Authentication. Each automation script must:

1. Obtain valid credentials (username/password) with appropriate permissions
2. Include the Authorization header in every API request
3. Handle authentication failures gracefully

Quick Reference - Use Cases by Category¶

1. Provisioning a New NFS File Share¶

Objective: Automate the creation of new NFS file shares for clients.

Key Steps:

• Discover available clusters and SVMs
• Select appropriate aggregates with sufficient space
• Create the file share with proper export policies
• Monitor the creation job until completion

Common Errors: Authentication failures, insufficient space, invalid export policies, job failures.

2. Decommissioning a File Share¶

Objective: Safely remove file shares that are no longer needed.

Key Steps:

• Locate the target file share
• Verify no active connections (optional)
• Delete the file share
• Monitor the deletion job

Common Errors: File share not found, permission issues, active connections, deletion constraints.

3. Expanding a LUN¶

Objective: Increase the size of existing LUNs to meet growing storage requirements.

Key Steps:

• Locate the target LUN
• Validate the new size requirements
• Expand the LUN
• Monitor the expansion job
• (Optional) Provide guidance for host-side expansion

Common Errors: LUN not found, insufficient space, invalid size parameters, LUN state issues.

4. Monitoring Cluster Performance¶

Objective: Continuously monitor cluster performance metrics for proactive management.

Key Steps:

• Identify target clusters
• Retrieve performance metrics for specified time intervals
• Process and analyze the metrics data
• Generate alerts or reports as needed

Common Errors: Cluster not found, invalid time intervals, metrics unavailable, rate limiting.

5. Annotating an Event¶

Objective: Add metadata annotations to events for enhanced tracking, categorization, and automation workflows.

Key Steps:

• Search for events using specific criteria (severity, state, resource type)
• Select events that require annotation
• Add structured annotations using key-value pairs
• Verify the annotation was applied successfully

Common Errors: Event not found, invalid annotation format, permission issues, concurrent modification conflicts.

6. Tagging a Volume with name_tag¶

Objective: Use name_tag to create consistently named volumes during LUN creation for better organization and searchability.

Key Steps:

• Discover available SVMs for LUN creation
• Create a LUN with a specific volume.name_tag parameter
• Monitor the LUN creation job until completion
• Verify the volume was created with the expected name derived from the tag

Common Errors: Invalid name_tag format, volume name conflicts, insufficient space, SVM not found, job failures.

7. Tagging an SVM via Event Annotation¶

Objective: Add custom metadata tags to SVMs by creating associated events with annotations, enabling SVM categorization and management.

Key Steps:

• Locate the target SVM using discovery endpoints
• Create a new event associated with the SVM
• Add structured annotations to the event (e.g., group, owner, project metadata)
• Monitor the event creation job until completion
• Verify the annotation was applied successfully

Common Errors: SVM not found, invalid event payload, job failures, annotation format issues.

8. Attaching Metadata to any Object¶

Objective: Provide a universal mechanism for attaching custom metadata to any object within ActiveIQ Unified Manager using the console's event annotation capabilities.

Key Steps:

• User selects an object in the ActiveIQ console
• User initiates an "Add Annotation" action
• Console creates an event associated with the object and adds the metadata as an annotation
• User can view all annotations for an object in the console

Common Errors: Object not found, invalid metadata format, permission denied, job failures.

9. Searching for Objects by Metadata¶

Objective: Enable powerful search capabilities to find objects based on their attached metadata tags, supporting both API-based automation and console-based user interfaces.

Key Steps:

• Search events using annotation filters (e.g., owner:team_a, environment:production)
• Parse event results to extract unique resource keys
• Retrieve full object details for each matching resource
• Present categorized search results grouped by object type
• Support advanced search patterns for compliance, cost tracking, and resource management

Common Errors: No matching results, invalid search syntax, deleted resources, pagination handling.

NetApp ActiveIQ Administrative Philosophy¶

NetApp ActiveIQ Unified Manager follows an event-driven administrative approach that provides comprehensive metadata management capabilities through its built-in event system. This philosophy aligns with enterprise requirements for:

Audit and Compliance¶

• Complete Audit Trail: All metadata changes are recorded as events with timestamps and user attribution
• Regulatory Compliance: Events provide the documentation trail required for SOX, GDPR, and other compliance frameworks
• Change Management: Integration with ITSM systems through event-based workflows

Enterprise Integration¶

• RBAC Integration: Leverages existing role-based access control for metadata management
• Workflow Automation: Events can trigger automated responses and notifications
• Reporting and Analytics: Metadata can be aggregated and analyzed through the event system

Operational Excellence¶

• Centralized Management: All metadata is managed through the same interface used for monitoring and administration
• Consistency: Standardized approach ensures uniform metadata handling across all object types
• Scalability: Event-based system scales with enterprise growth and complexity

Tagging and Labeling Approaches¶

NetApp ActiveIQ API provides multiple approaches for adding labels/tags to objects:

Event Annotations¶

• Purpose: Add metadata to events for categorization, workflow integration, and reporting
• Format: Free-form string (recommended: key-value pairs like priority:high,team:storage)
• API Endpoint: PATCH /management-server/events/{key}
• Use Cases:
• ITSM integration (ticket numbers, workflow IDs)
• Priority classification and routing
• Team assignment and responsibility tracking
• Compliance and audit metadata

Volume Name Tags¶

• Purpose: Create consistent volume naming during LUN creation
• Format: String that becomes part of the volume name (e.g., sample_volume → NSLM_sample_volume)
• API Endpoint: POST /storage-provider/luns with volume.name_tag parameter
• Use Cases:
• Standardized naming conventions
• Environment identification (dev, test, prod)
• Application or project grouping
• Cost center or department tracking

Comparison¶

General Error Handling Strategies¶

Network and Connectivity¶

• Timeout Errors: Implement exponential backoff retry logic
• Connection Errors: Verify network connectivity and API endpoint availability
• Rate Limiting (429): Implement request throttling and backoff strategies

Authentication and Authorization¶

• 401 Unauthorized: Verify credentials and re-authenticate if necessary
• 403 Forbidden: Check user permissions and role assignments

Resource Management¶

• 404 Not Found: Implement resource discovery and validation logic
• 400 Bad Request: Parse error messages and provide user-friendly feedback
• 409 Conflict: Handle resource state conflicts gracefully

Asynchronous Operations¶

• Job Monitoring: Implement polling logic with appropriate intervals
• Job Failures: Retrieve detailed error information from failed jobs
• Timeout Handling: Set reasonable timeouts for long-running operations

Best Practices¶

Security¶

• Store credentials securely (environment variables, secure vaults)
• Use service accounts with minimal required permissions
• Implement proper credential rotation

Reliability¶

• Implement idempotent operations where possible
• Use circuit breaker patterns for external dependencies
• Log all operations for troubleshooting and audit purposes

Performance¶

• Cache frequently accessed data (clusters, SVMs, etc.)
• Implement connection pooling for high-frequency operations
• Use appropriate request batching where supported

Monitoring¶

• Track API response times and error rates
• Monitor job completion rates and failure patterns
• Implement health checks for the automation system

Implementation Tools¶

The automation scripts can be implemented using various technologies:

• Python: Using requests library for HTTP operations
• PowerShell: Using Invoke-RestMethod cmdlets
• Bash/curl: For simple operations and testing
• Go: For high-performance, concurrent operations
• Terraform: For infrastructure-as-code approaches

Integration Patterns¶

These use cases can be integrated into larger automation workflows:

• CI/CD Pipelines: Provision storage as part of application deployment
• Monitoring Systems: Integrate performance monitoring with alerting platforms
• ITSM Tools: Trigger storage operations from service request workflows
• Infrastructure as Code: Define storage resources in declarative formats

Next Steps¶

For each use case, consider:

1. Implementation: Develop the automation scripts using your preferred technology
2. Testing: Validate the scripts in a test environment
3. Monitoring: Implement logging and alerting for the automation
4. Documentation: Create operational runbooks and troubleshooting guides
5. Integration: Connect the automation to your existing workflows and systems