Configuration of Azure Stream Analytics

Azure Stream Analytics (ASA) is a fully managed, cost-effective real-time event processing engine. Stream Analytics makes it easy to set up real-time analytic computations on data streaming from devices, sensors, websites, social media, applications, infrastructure systems, and more.

The service can be hosted with a few clicks in the Azure portal; users can author a Stream Analytics job specifying the input source of the streaming data, the output sink for the results of your job, and a data transformation expressed in a SQL-like language. The jobs can be monitored and you can adjust the scale/speed of the job in the Azure portal to scale from a few kilobytes to a gigabyte or more of events processed per second.

Let's review how to configure Azure Stream Analytics step by step:

1. Log in to the Azure portal using your Azure credentials, click on New, and search for Stream Analytics job:

Creating new Stream Analytics job

1. Click on Create to create an Azure Stream Analytics instance:

Creation of the Azure Stream Analytics deployment

1. Provide a Job Name and Resource group name for the Azure Stream Analytics job deployment:

Deploying the Azure Stream Analytics in new resource group

1. After a few minutes, the deployment will be complete:

Service available for deployment

1. Review the following in the deployment—audit trail of the creation:

Audit Trail

1. Scale-out horizontally by adding more capacity using a simple UI:

Scale up on demand using simple UI

1. Build in the Query interface to run queries:

Run SQL like Queries to ingest and process streaming data 

1. Run Queries using a SQL-like interface, with the ability to accept late-arriving events with simple GUI-based configuration:

Configure late-arriving events

In this section, we created an Azure Stream Analytics instance and reviewed a couple of features. In the next sections, we will look into the advantages, security, and total cost of ownership.