How to Detect Problems Before They Occur with Azure Anomaly Detector

Add anomaly detection capabilities to your applications for improved operational efficiency and user experience.

Anomaly detection is a key aspect of building reliable and transformative business solutions that have the capacity to take on intricate challenges. With Azure anomaly detection, you can boost your business’s reliability by detecting problems that could jeopardize your strategic efforts. In this post, we’ll look into anomaly detection deployment through Azure Cognitive Services.

What is Azure Anomaly Detection?

Azure Anomaly Detection helps you embed time-series detection capabilities into your applications to enable users to identify and report problems. The Anomaly Detector takes the time series data and chooses the best possible algorithm for high accuracy. The algorithm detects dips, spikes, trend changes, and deviations from normal cyclic patterns through multivariate and univariate APIs. You can customize the Anomaly Detection Service as per your unique business needs. And, you can deploy the service on both the Edge and the Cloud.

Why invest in Azure Anomaly Detection Service?

Apps and other online services can quickly become obsolete if they don’t upgrade or offer quick debugging. Your business can not only lose customers but discourage potential customers from trying your service. With Azure Anomaly Detection Service, you can amp up your applications for quick system anomaly detection, so your developers can find timely solutions.

Anomaly Detection use cases

The service is packed with powerful features that include:

- AI-powered inference engine that processes time-series data to automatically choose the best algorithm for your application.

- AI-powered automatic detection eradicates the need for training data, so you can focus on fixing problems for quick solutions.

- Customizable settings let you change settings based on the risk profile of your company, so you can pay more attention to potential anomalies and work towards eradicating them.

Azure Anomaly Detection offers anomaly detection capabilities for every industry. From hospitals to retail, every organization (small or large) can benefit from anomaly detection to get to the problems faster before they wreak havoc.

Setting up Anomaly Detection with Azure Services

Step 1: Get the following prerequisites:

- Get Azure Synapse Analytics Workspace and have Azure Data Lake Storage Gen2 configured as the default storage.

- Get a Spark pool in Azure Synapse Workspace.

Configure the cognitive services in Azure Synapse.

Step 2: Sign in to your Azure Portal and set up a Spark Table

For this, download the Notebook file. The file contains the code to generate the table.

Next, upload the downloaded file to the Azure Synapse workspace.

Step 3: Next, open the Notebook file and choose Run All.

See the screenshot below.

Step 4: Locate the anamoly_detector_testing_data in the default Spark database.

Step 5: Right-click on the Spark Table and select Machine Learning > Predict with a model, as shown below.

Next, you’ll see a configuration panel. Here, select Anomaly Detector.

Step 6: Configure the Anomaly Detector

Enter the following details into the Anomaly Detector configuration window, as shown in the screenshot below.

Step 7: Run the Notebook

Select ‘Run All’ to perform anomaly detection. See the screenshot below.

Conclusion

If done correctly, the above-mentioned steps will help you enrich data in Azure Synapse with Cognitive Services. You’ll be able to use an Azure Anomaly Detector to find wide-ranging anomalies for quick problem detection and solution. With timely anomaly detection, you can eliminate potential problems that could seriously jeopardize your business.

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Krishna Sriram

Principal Cloud Solutions Architect, EdgeSoft Corp

@cloudgeek

I am a Certified Azure Solutions Architect Expert with 17+ years of IT experience working with all types of Infrastructure, Applications, Network, Security etc.,