Monitoring Azure Analysis Services

Effective monitoring is crucial for ensuring the health, performance, and availability of your Azure Analysis Services (AAS) instances. This document outlines the key metrics, tools, and strategies for monitoring your AAS resources.

Key Monitoring Tools

Azure Monitor

Azure Monitor is the primary service for collecting, analyzing, and acting on telemetry from your Azure and on-premises environments. It provides a unified view of application performance and health.

Azure Advisor

Azure Advisor provides recommendations to optimize your Azure resources for performance, security, high availability, cost, and operations. It can offer insights related to AAS performance and configuration.

SQL Server Management Studio (SSMS)

While primarily for management, SSMS can be used to connect to your AAS instance and monitor active queries, sessions, and analyze query performance using Dynamic Management Views (DMVs).

Important Metrics to Monitor

Metric Name Description Example Thresholds (Guideline)
CPU Usage (%) Percentage of CPU utilized by the Analysis Services engine. High CPU can indicate performance bottlenecks. Consistently above 80%
Memory Usage (%) Percentage of available memory being used. Exceeding available memory can lead to performance degradation or instability. Consistently above 85%
Query Duration (Average/Max) Average or maximum time taken for queries to complete. High query durations indicate slow query performance. Average above 5 seconds, Max above 30 seconds (depends on query complexity)
Query Failures Number of queries that failed. Indicates underlying issues with the server or query logic. Any non-zero value, investigate immediately
Data Refresh Duration Time taken for tabular models to refresh. Long refresh times can impact data freshness. Significantly longer than historical averages or exceeding SLA
Active Connections Number of active client connections to the server. High connection counts might indicate inefficient connection management or load issues. Approaching server capacity limits or sudden spikes
Disk I/O Operations Rate of read/write operations to disk. Can indicate performance issues related to data storage. Unusual spikes or sustained high rates

Monitoring Strategies

1. Set Up Azure Monitor Alerts

Configure alerts for critical metrics such as high CPU/memory usage, excessive query durations, and query failures. This proactive approach allows you to address issues before they impact users.

2. Utilize Diagnostic Logs

Enable diagnostic logging for your AAS instance and send logs to Log Analytics. This provides a rich source of data for troubleshooting and performance analysis. Key log categories include:

3. Create Custom Dashboards

Build dashboards in the Azure portal that consolidate key metrics and log query results. This provides a single pane of glass for monitoring the health and performance of your AAS environment.

4. Monitor Query Performance

Regularly analyze query performance using SSMS or by querying diagnostic logs. Identify slow-running queries and optimize them by reviewing the query plan, data model, and partitioning strategies.

5. Track Data Refresh Operations

Monitor the success and duration of your data refreshes. Investigate any failures or significant increases in refresh time, as this can impact the freshness of your data.

Tip: Consider using Azure Application Insights in conjunction with your client applications to monitor query performance from the application's perspective, providing end-to-end visibility.

6. Performance Baselines

Establish baseline performance metrics during normal operating periods. This will help you identify deviations and anomalies that may indicate an issue.

Common Monitoring Scenarios

Scenario 1: Slow Query Performance

Scenario 2: High Resource Utilization

Scenario 3: Data Refresh Failures