Which two Azure services can be used to provision Spark clusters?

Azure offers two primary services for provisioning and managing Apache Spark clusters. Azure Databricks is a premium, managed analytics platform optimized for the Microsoft Azure cloud services platform, built around Apache Spark. It provides a collaborative environment with notebooks, automated cluster management, and enterprise-grade security. Azure HDInsight is a managed, full-spectrum, open-source analytics service that allows you to create clusters using various open-source frameworks, including Apache Spark, Hadoop, and Kafka. Both services enable users to deploy and manage Spark clusters for large-scale data processing and analytics.

B. Azure Log Analytics: This service is part of Azure Monitor and is used for collecting, correlating, and analyzing log and performance data from various sources, not for provisioning data processing clusters.

C. Azure Time Series Insights: This is a fully managed analytics, storage, and visualization service for IoT-scale time-series data. It does not provision general-purpose Spark clusters.

1. Microsoft Learn: "What is Azure Databricks?". This document states, "Azure Databricks is a data analytics platform optimized for the Microsoft Azure cloud services platform. Azure Databricks offers three environments for developing data intensive applications: Databricks SQL, Databricks Data Science & Engineering, and Databricks Machine Learning. Databricks Data Science & Engineering (sometimes called simply “Workspace”) provides an interactive workspace that enables collaboration between data engineers, data scientists, and machine learning engineers. For a big data pipeline, the data (raw or structured) is ingested into Azure through Azure Data Factory in batches, or streamed near real-time using Apache Kafka, Event Hub, or IoT Hub. This data lands in a data lake for long term persisted storage, in Azure Blob Storage or Azure Data Lake Storage. As part of your analytics workflow, use Azure Databricks to read data from multiple data sources and turn it into breakthrough insights using Spark."

2. Microsoft Learn: "What is Apache Spark in Azure HDInsight?". This document explicitly states, "Apache Spark is a parallel processing framework that supports in-memory processing to boost the performance of big-data analytic applications. Apache Spark in Azure HDInsight is the Microsoft implementation of Apache Spark in the cloud. HDInsight makes it easier to create and configure a Spark cluster in Azure."

3. Microsoft Learn: "DP-900: Describe the capabilities of Azure HDInsight". This module details the cluster types available in HDInsight, explicitly listing Spark as one of them. It states, "Azure HDInsight is a cloud distribution of Hadoop components... You can use HDInsight to create clusters of virtual machines for the following open-source frameworks: ... Apache Spark: A parallel processing framework that supports in-memory processing to boost the performance of big-data analysis applications."