Migrating hundreds of SQL Server instances and thousands of databases to Azure SQL Database, our Platform as a Service (PaaS) offering, is a considerable task, and to streamline the process as much as possible, you need to feel confident about your relative readiness for migration. Being able to identify low-hanging fruit including the servers and databases that are fully ready or that require minimal effort to prepare for migration eases and accelerates your efforts. We are pleased to share that Azure database target readiness recommendations have been enabled.
With just 1 click, Event Hubs customers can easily visualize incoming streaming data and start writing Stream Analytics query from the Event Hubs portal. Once the query is ready, they will be able to operationalize it in few clicks and start deriving real time insights.
With the new MATCH_RECOGNIZE function, you can easily define event patterns using regular expressions and aggregate methods to verify and extract values from the match. This enables to easily express and run Complex Event Processing (CEP) on your streams of data.
Developers can now use aggregates such as SUM, COUNT, AVG, MIN and MAX directly with the OVER clause, without having to define a window. This enables users to easily express queries such as “Is the latest temperature greater than the maximum temperature reported in the last 24 hours?”.
Azure Stream Analytics supports managed identity authentication with egress to Azure Blob Storage. The identity is a managed application registered in Azure Active Directory that represents a given Stream Analytics job, and can be used to authenticate to a targeted resource. Managed identities eliminate the limitations of user-based authentication methods, like needing to reauthenticate due to password changes or user token expirations that occur every 90 days.
Announcing the public preview for new functionality that will enable customers to manage the same data using either the Blob APIs or ADLS Gen2 APIs. Multi-protocol data access for Azure Data Lake Storage Gen2 will bring features like snapshots, soft delete, data tiering, and logging that are standard in the Blob world to the filesystem world of ADLS Gen2.
The Azure Resource Graph is now generally available. Azure Resource Graph provides you efficient and performant resource exploration with the ability to query at scale across a given set of subscriptions so that you can effectively govern your environment.
Stream Analytics now offers native support for Apache Parquet format when writing to Blob storage. Apache Parquet is a columnar storage format tailored for bulk processing and query processing in the big data ecosystems.