Create a solution that uses Azure Metrics Advisor, part of Azure Applied AI Services

Azure Metrics Advisor, as part of Microsoft’s Azure Applied AI Services, is a comprehensive solution for anomaly detection and diagnosis in time series data. The platform enables businesses to monitor data in real-time, identify potential issues early, and fix them before they become problematic. This service is particularly crucial in scenarios that require real-time insights like finance, e-commerce, IoT devices, and business analytics.

In the scope of the AI-102 Designing and Implementing a Microsoft Azure AI Solution exam, candidates are expected to have an understanding of how to implement Azure Metrics Advisor to solve problems.

1. Implementing Azure Metrics Advisor

To implement Azure Metrics Advisor, you need to have a valid Azure subscription. If you don’t have one, you can create it through the Azure portal.

The first step in implementing Azure Metrics Advisor is to create a Metrics Advisor resource. Follow these steps:

1. Navigate to the Azure portal, Select “Create a resource”, search for “Metrics Advisor”, and then select “Create” to create a new resource.
2. In “Create Metrics Advisor”, provide the subscription, resource group, name, region, and pricing tier details, then click “Review + Create.”

Once resource creation is successful, navigate to it, and select “Get Started” next to “Quickstarts” to get your API and subscription keys.

2. Connecting your data source

After you have created a Metrics Advisor resource, the next step is to connect your data source. Azure Metrics Advisor supports a variety of data sources including Azure Blob Storage, Azure Data Explorer, Azure Cosmos DB, Azure Table Storage, Azure Event Hubs, InfluxDB, MySQL, PostgreSQL, and SQL Server.

Here’s a basic outline of how to connect a data source:

1. Navigate to your Metrics Advisor resource in the Azure portal, then select “Data Feeds.”
2. Click “+ New Data Feed”, choose a data source from the list, and input the required connection details.

3. Configure Anomaly Detection

Set up anomaly detection rules to help identify unusual data behavior. Azure Metrics Advisor takes a two-level approach: a time series level, which is sensitive and ideal for individual anomaly detection, and a scope level, which is less sensitive, for generalized trends.

1. Navigate to “Anomaly Detection Configuration”, click “Add detection configuration”.

4. Diagnosis and Alerting

Once an anomaly is discovered, Azure Metrics Advisor can provide a diagnosis and create an alert to inform the corresponding stakeholders. To set up alert configuration:

1. Navigate to “Alert Configuration” and click “New Alert Configuration”. Set the anomaly severity level, the detection configurations, and who to alert.

In conclusion, Azure Metrics Advisor, part of Microsoft’s Azure Applied AI Services, provides valuable tools for anomaly detection and diagnosis in time-series data. With this service, you can effectively monitor data, detect anomalies in real-time and efficiently diagnose the root cause to avoid potential negative impacts. This understanding and implementation skill is vital in the AI-102 exam context and beyond for developing and implementing AI solutions in real-world business scenarios.

Practice Test

Azure Metrics Advisor is a part of Azure Applied AI Services.

• 1) True
• 2) False

Answer: True

Explanation: Azure Metrics Advisor is indeed part of Azure Applied AI Services. It provides an AI-based service to understand and explore telemetry from applications and devices.

Azure Metrics Advisor is used for anomaly detection and root-cause analysis.

• 1) True
• 2) False

Answer: True

Explanation: Azure Metrics Advisor is used to analyze multivariate, streaming time series data to detect anomalies, and find their root-cause with the help of an AI-based system.

Azure Metrics Advisor does not support integration with Azure Monitor logs.

• 1) True
• 2) False

Answer: False

Explanation: Azure Metrics Advisor provides integration with Azure Monitor logs.

In Azure Metrics Advisor, what strategy is used for anomaly detection?

• 1) Supervised learning
• 2) Reinforcement learning
• 3) Unsupervised learning
• 4) None of the above

Answer: Unsupervised learning

Explanation: Azure Metrics Advisor utilizes unsupervised machine learning techniques for anomaly detection.

Azure AI Metrics Advisor does not offer an API for developers to build onto their apps.

• 1) True
• 2) False

Answer: False

Explanation: Azure Metrics Advisor provides a RESTful API and client libraries in several languages for developers to integrate these services into their applications.

What Azure service does Azure Metrics Advisor use to store data?

• 1) Azure Storage
• 2) Azure Data Lake
• 3) Azure Cosmos DB
• 4) All of the above

Answer: All of the above

Explanation: Azure Metrics Advisor can use all these Azure services to store data for further analysis.

Azure Metrics Advisor can analyze telemetry from only applications.

• 1) True
• 2) False

Answer: False

Explanation: Azure Metrics Advisor can analyze telemetry from both applications and devices.

Azure Metrics Advisor supports only anomaly detection and doesn’t support anomaly analysis.

• 1) True
• 2) False

Answer: False

Explanation: Azure Metrics Advisor supports both anomaly detection and anomaly analysis.

Azure Metrics Advisor doesn’t help with getting insights on time series data monitoring, preventive maintenance, and trend analysis.

• 1) True
• 2) False

Answer: False

Explanation: Azure Metrics Advisor indeed helps with these aspects.

Azure Metrics Advisor is capable of alerting once an anomaly is detected.

• 1) True
• 2) False

Answer: True

Explanation: Azure Metrics Advisor can generate alerts once an anomaly is detected.

Azure Metrics Advisor is not a fully managed service by Azure.

• 1) True
• 2) False

Answer: False

Explanation: Azure Metrics Advisor is a fully managed service on Azure.

Azure Metrics Advisor doesn’t support ingestion from other sources outside Azure.

• 1) True
• 2) False

Answer: False

Explanation: Azure Metrics Advisor supports ingestion from multiple sources, including outside of Azure.

Is the data analysed by Azure Metrics Advisor limited to time series data?

• 1) True
• 2) False

Answer: True

Explanation: Azure Metrics Advisor is designed specifically to manage and analyze time series data.

Azure Metric Advisors provides insights in real-time.

• 1) True
• 2) False

Answer: True

Explanation: Azure Metrics Advisor provides real-time insights. It can detect and determine the potential impact of anomalies as soon as the data is ingested.

Azure Metrics Advisor can automatically suggest likely root-cause of anomalies.

• 1) True
• 2) False

Answer: True

Explanation: Azure Metrics Advisor has a built-in root cause analysis feature that suggests the probable root cause of an anomaly.

Interview Questions

What is Azure Metrics Advisor?

Azure Metrics Advisor is a part of Azure Applied AI Services, it is used for multidimensional anomaly detection and root cause analysis with built-in machine learning capabilities. It helps you monitor the health of your business, your products, and your growth.

What are the main capabilities of Azure Metrics Advisor?

Azure Metrics Advisor provides capabilities like multi-dimensional anomaly detection, incident troubleshooting, adaptive alerting, and intelligent diagnosis. It can analyze multi-dimensional data from various sources and discover anomalies with built-in machine learning models.

How can Azure Metrics Advisor help in root cause analysis?

Azure Metrics Advisor has a built-in root cause analysis feature that helps users to understand the contributing factors behind identified anomalies. This helps in early detection and resolution of problems.

What diagnosis capabilities does Azure Metrics Advisor provide?

Azure Metrics Advisor provides intelligent diagnosis with root-cause analysis and contributing factor discovery. This helps businesses to quickly identify and react to any anomalies and prevent future incidents.

Does Azure Metrics Advisor support custom Anomaly detection models?

Yes, Azure Metrics Advisor allows you to configure custom anomaly detection models based on your specific requirements and parameters.

Which data sources are supported by the Azure Metrics Advisor?

Azure Metrics Advisor supports several data sources, including Azure Data Explorer, Azure Cosmos DB, Azure Data Lake Storage, Azure Blob Storage, Apache Kafka, MySQL, PostgreSQL, and SQL Server.

How does Azure Metrics Advisor handle incident management?

Azure Metrics Advisor provides incident management by setting up anomaly alert configurations. It notifies about the anomalies and issues via webhooks, emails or it can integrate alerts into existing workflows like using Microsoft Teams for incident management.

How can Azure Metrics Advisor improve your business?

Azure Metrics Advisor helps businesses to monitor their metrics and KPIs, identify anomalies, diagnose anomalies, and uncover potential issues before they become critical. This leads to proactive decision making, improved operational efficiency, and uptime.

What pricing models are available for Azure Metrics Advisor?

Azure Metrics Advisor uses a consumption-based pricing model. Customers are charged based on the volume of data ingested for anomaly detection and the number of time series monitored.

Is there a limit on the number of data feeds that can be created with Azure Metrics Advisor?

Yes, Azure Metrics Advisor enforces limits on various resources, like the number of data feeds that can be created. The actual limit depends on the type of Azure subscription and can be increased upon request.

What does the ‘Incident’ refer to in Azure Metrics Advisor?

An Incident in Azure Metrics Advisor refers to a time period during which the anomaly rate of a data feed is unusually high, often indicating unusual business behavior.

What is an Anomaly Alert in Azure Metrics Advisor?

An anomaly alert in Azure Metrics Advisor is a notification triggered when the system detects an incident or a series of anomalies according to pre-set conditions.

How does the Azure Metrics Advisor define an anomaly?

In Azure Metrics Advisor, an anomaly is defined as data that deviates significantly from the expected data pattern. This definition is based on the sophisticated machine learning models within the Metrics Advisor.

Can Azure Metrics Advisor integrate with other Azure services?

Yes, Azure Metrics Advisor can be integrated with other Azure services like Azure Notification Hubs for Anomaly alerts delivery, Azure Data Lake Storage for data ingestion, and Azure Logic Apps for advanced workflow scenarios.

Can you monitor all your cloud and on-premise applications with Azure Metrics Advisor?

Yes, Azure Metrics Advisor allows monitoring of all your applications across multi-cloud and on-premise environments, as long as data feeds can be provided for analysis.