Azure Data Explorer

Azure Data Explorer is a fully managed data analytics service that can handle large volumes of diverse data from any data source, such as websites, applications, IoT devices, and more. Azure Data Explorer makes it simple to ingest this data and enables you to do complex ad hoc queries on the data in seconds. It scales quickly to terabytes of data, in minutes, allowing rapid iterations of data exploration to discover relevant insights. It is already integrated with Apache Spark work via the Data Source and Data Sink Connector and is used to power solutions for near real-time data processing, data archiving, machine learning etc.

Getting started with Azure Data Explorer using the Go SDK covered how to use the Azure Data Explorer Go SDK to ingest and query data from azure data explorer to ingest and query data. In this blog you will the Azure Go SDK to manage Azure Data Explorer clusters and databases.

Azure Data Explorer (also known as Kusto) is a fast and scalable data exploration service for analyzing large volumes of diverse data from any data source, such as websites, applications, IoT devices, and more. This data can then be used for diagnostics, monitoring, reporting, machine learning, and additional analytics capabilities.

With the help of an example, this blog post will walk you through how to use the Azure Data explorer Go SDK to ingest data from a Azure Blob storage container and query it programmatically using the SDK. After a quick overview of how to setup Azure Data Explorer cluster (and a database), we will explore the code to understand what’s going on (and how) and finally test the application using a simple CLI interface