Administer Azure Analysis Services
This section provides comprehensive guidance on administering Azure Analysis Services, covering key tasks such as managing servers, monitoring performance, securing your data, and implementing best practices for efficient operation.
Key Administration Tasks
Server Management
Learn how to create, configure, and manage your Azure Analysis Services instances. This includes:
- Provisioning new Analysis Services servers.
- Configuring server properties, including performance tiers and scaling options.
- Managing resource utilization and capacity planning.
- Implementing auto-scaling rules to adapt to changing workloads.
Monitoring and Performance Tuning
Effective monitoring is crucial for maintaining the health and performance of your Analysis Services environment. Discover how to:
- Utilize Azure Monitor to track key metrics like CPU usage, memory, and query latency.
- Set up alerts for critical performance thresholds.
- Analyze query performance using DMVs (Dynamic Management Views).
- Identify and resolve performance bottlenecks.
- Implement caching strategies to improve query response times.
Security Management
Secure your sensitive data by implementing robust security measures. This includes:
- Configuring role-based access control (RBAC) for server and database access.
- Managing user permissions and authentication methods.
- Implementing row-level security and object-level security within models.
- Integrating with Azure Active Directory for centralized identity management.
Backup and Restore
Ensure business continuity with proper backup and restore procedures.
- Understand the automated backup policies for Azure Analysis Services.
- Learn how to perform manual backups and restores when necessary.
- Configure backup retention policies to meet compliance requirements.
Automation and Scripting
Leverage scripting and automation tools to streamline administrative tasks.
- Use Azure PowerShell cmdlets for managing Analysis Services.
- Explore REST APIs for programmatic management.
- Integrate with Azure DevOps or other CI/CD pipelines for deployment and management automation.
Best Practices
Follow recommended best practices for a stable and high-performing Analysis Services deployment:
- Choose the appropriate service tier for your workload.
- Optimize your data models for performance.
- Monitor query patterns and user activity.
- Keep your models and server configurations up-to-date.