Manage Azure Analysis Services Server

This document provides comprehensive guidance on managing your Azure Analysis Services server instance. You'll learn how to monitor performance, scale your resources, secure your data, and perform essential administrative tasks.

Server Management Overview

Azure Analysis Services provides a fully managed PaaS (Platform as a Service) offering that simplifies the deployment and management of enterprise-grade big data model solutions. Management tasks can be performed through the Azure portal, Azure Resource Manager (ARM) templates, PowerShell, or programmatically using the Azure Analysis Services REST API.

Using the Azure Portal

The Azure portal is the primary interface for managing your Analysis Services resources. From the portal, you can:

• Create and delete server instances.
• Configure server properties such as scale, region, and administrator accounts.
• Monitor resource utilization and performance metrics.
• Manage firewall rules and network access.
• View activity logs and diagnostic settings.

Navigate to your Analysis Services server resource in the Azure portal to access these management capabilities.

Using Azure PowerShell

Azure PowerShell provides a powerful command-line interface for automating management tasks. You can use the Az.AnalysisServices module to:

• Provision new servers.
• Update existing server configurations.
• Start, stop, and restart servers.
• Manage server administrators and firewall rules.

# Example: Restart an Azure Analysis Services server
            Restart-AzAnalysisServicesServer -ResourceGroupName "MyResourceGroup" -Name "MyAnalysisServicesServer"

Using the REST API

For programmatic management and integration with custom applications, Azure Analysis Services exposes a REST API. This API allows you to perform all management operations that are available through the Azure portal and PowerShell.

Key operations include:

• Server provisioning and lifecycle management.
• Configuration updates.
• Monitoring and diagnostics.

Scaling Your Server

Scaling your Azure Analysis Services server allows you to adjust its compute and memory resources to meet changing performance demands. You can scale up (increase resources for higher performance) or scale down (decrease resources to save costs).

Scaling is performed by changing the pricing tier or the number of capacity units (when applicable). This operation is often a rolling update and may involve a brief service interruption.

To scale your server:

1. In the Azure portal, navigate to your Analysis Services server.
2. Under Settings, select Scale.
3. Choose a new pricing tier or adjust the capacity units.
4. Click Apply.

Monitoring Performance

Effective monitoring is crucial for ensuring your Analysis Services solution performs optimally. Azure Analysis Services provides several tools and metrics for this purpose.

Azure Monitor

Azure Monitor is your central hub for monitoring Azure resources. You can collect, analyze, and act on telemetry from your Analysis Services server.

• Metrics: Track key performance indicators like CPU utilization, memory usage, query throughput, and active connections.
• Logs: Collect diagnostic logs for in-depth troubleshooting.
• Alerts: Configure alerts to notify you when certain metrics exceed predefined thresholds.

Common metrics to monitor include:

• CPU%: Indicates processor load.
• Memory%: Indicates memory utilization.
• QueryRuns: Number of queries executed.
• ActiveConnections: Number of active client connections.

Query Performance

Monitor query execution times to identify performance bottlenecks. Slow queries can impact user experience and increase resource consumption.

Use tools like:

• SQL Server Management Studio (SSMS) to run DMV queries (Dynamic Management Views) that provide insights into query performance.
• Azure Monitor logs with Query Store enabled (if applicable for your version/setup) for historical query analysis.

-- Example DMV query to find slow queries
            SELECT *
            FROM $System.QueryStatus
            WHERE Duration > 1000 -- Queries longer than 1 second
            ORDER BY Duration DESC;

Backup and Restore

Regular backups are essential for data protection and disaster recovery. Azure Analysis Services supports automated and manual backup operations.

Automated Backups

You can configure automated backups through the Azure portal. These backups are stored in a specified Azure Blob Storage account.

1. In your Analysis Services server settings, select Backups.
2. Configure the backup frequency, retention period, and Azure storage account details.

Manual Backups

You can also initiate manual backups on demand via PowerShell or the REST API.

# Example: Manual backup using PowerShell
            Backup-AzAnalysisServicesServer -ResourceGroupName "MyResourceGroup" -Name "MyAnalysisServicesServer" -BackupFile "https://mystorage.blob.core.windows.net/backups/MyDatabaseBackup.zip"

Restoring Data

Restoring a database from a backup can be done through the Azure portal, PowerShell, or the REST API. Ensure you have the correct backup file path.

Server Security

Securing your Analysis Services server is paramount. This involves controlling access to the server and the data it contains.

Access Control

• Server Administrators: Assign users or groups from your Microsoft Entra ID tenant as server administrators. These users have full control over the server.
• Database Roles: Within your Analysis Services models, define roles to grant specific permissions to users or groups for accessing tabular or multidimensional data.

Use the Access control (IAM) blade in the Azure portal for server-level permissions and tools like SQL Server Management Studio (SSMS) or Visual Studio for managing database roles.

Firewall and Network Security

Configure firewall rules to restrict network access to your Analysis Services server. You can allow access only from specific IP addresses or virtual networks.

1. In your Analysis Services server settings, select Firewall.
2. Enable the firewall and specify allowed IP addresses or virtual network subnets.