Manage Azure Analysis Services

This document provides comprehensive guidance on managing your Azure Analysis Services resources, covering tasks such as scaling, monitoring, security configuration, and basic administration.

Scaling Your Azure Analysis Services Environment

Azure Analysis Services allows you to scale your resources to meet the demands of your analytical workloads. You can scale both compute and memory resources to optimize performance and cost.

Scaling Vertically (Changing Service Tier)

Vertical scaling involves changing the pricing tier of your Analysis Services server. Higher tiers offer more resources (CPU, RAM) and better query performance. This is typically done through the Azure portal.

1. Navigate to your Azure Analysis Services resource in the Azure portal.
2. Under "Settings", click on "Scale".
3. Select the desired service tier (e.g., Developer, Basic, Standard S1, Standard S2, etc.).
4. Click "Apply" to save the changes. The server will be restarted during the scaling operation.

Scaling Horizontally (Read Scale-Out)

For read-intensive workloads, Azure Analysis Services offers read scale-out capabilities. This allows you to create read-replica servers that can handle query requests, distributing the load and improving responsiveness. This feature is available in Standard pricing tiers.

• Enable read scale-out in the server's configuration.
• Create additional read-replica servers.
• Configure your client applications or load balancers to distribute read queries across the primary and read-replica servers.

Monitoring and Performance Tuning

Effective monitoring is crucial for understanding the health and performance of your Analysis Services. Azure provides integrated monitoring tools.

Key Metrics to Monitor

• CPU Usage: High CPU can indicate a need for scaling or query optimization.
• Memory Usage: Exceeding available memory can lead to performance degradation.
• Query Latency: Slow query responses can impact user experience.
• Cache Hit Ratio: A low hit ratio might suggest inefficient caching strategies or a need for more memory.
• Active Connections: High numbers of connections can strain server resources.

Using Azure Monitor

Azure Monitor provides a comprehensive platform for collecting, analyzing, and acting on telemetry from your Azure resources. You can set up alerts for critical metrics.

For detailed performance tuning, consider:

• Optimizing DAX queries.
• Improving tabular model design.
• Using query partitioning.
• Leveraging partitions for data management.

Security Management

Securing your Azure Analysis Services environment is paramount. This involves managing access control and network security.

Role-Based Access Control (RBAC)

Use Azure RBAC to grant permissions to users and groups for managing the Analysis Services server itself (e.g., Contributor, Reader roles).

Database Roles

Within your Analysis Services tabular models, define database roles to control access to data and operations at the model level (e.g., Administrator, Read, ReadAll).

-- Example of creating a database role using Tabular Editor or SSMS
CREATE ROLE [MyReadRole]
ADD MEMBER [YourAzureADGroup];
ALTER ROLE [MyReadRole] ADD PERMISSION READ;
GO
            

Network Security

Configure firewalls and virtual networks to restrict access to your Analysis Services server. Consider using private endpoints for secure connectivity.

Backup and Restore

Regular backups are essential for disaster recovery and data protection. Azure Analysis Services automatically backs up your databases.

• Automatic Backups: By default, Azure performs daily backups.
• Manual Backups: You can initiate manual backups through the Azure portal or using PowerShell/REST API.
• Restore Operations: Restore databases from backups to the same or a different server.

Administrative Tasks

Perform routine administrative tasks such as restarting the server, managing models, and configuring server properties.

• Restarting the Server: Useful for applying configuration changes or resolving transient issues.
• Deploying Models: Deploy updated tabular models from Visual Studio or other development tools.
• Managing Data Sources: Update connection strings and credentials for data sources.