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Created Service Type Note Context Reference
12/4/2018 Stream Analytics General Availability Today, we are announcing the general availability of Azure Stream Analytics (ASA) on IoT Edge, empowering developers to deploy near-real-time analytical intelligence closer to IoT devices, unlocking the full value of device-generated data. With this release, Azure Stream Analytics enables developers to build truly hybrid architectures for stream processing, where device-specific or site-specific analytics can run on containers on IoT Edge and complement large scale cross-devices analytics running in the cloud. Link Link Details
10/15/2018 Stream Analytics New Features New metric in Azure Stream Analytics tracks latency of your streaming pipeline Link Link Details
9/26/2018 Stream Analytics New Feature Azure Stream Analytics now supports high-performance and efficient write operations to Azure SQL Database and Azure SQL Data Warehouse to help customers achieve four to five times higher throughput than what was previously possible. To achieve fully parallel topologies, Stream Analytics will transition SQL writes from serial to parallel operations while simultaneously allowing for batch size customizations. Link Link Details
9/26/2018 Stream Analytics New Feature Visual Studio tooling for Azure Stream Analytics further enhances the local testing capability to help users test their queries against live data or event streams from cloud sources such as Azure Event Hubs or IoT Hub. This helps developers test their queries without having to stop and restart their jobs, so they're more efficient. Link Link Details
9/26/2018 Stream Analytics New Feature In Azure Stream Analytics, users can optionally specify the number of partitions of a stream when performing repartitioning. This will enable better performance tuning when the partition key can't be changed to upstream constraints, or there's a fixed number of partitions for output, or partitioned processing is needed to scale out to a larger processing load. Link Link Details
9/26/2018 Stream Analytics New Feature Developers who create Azure Stream Analytics modules for Azure IoT Edge can now write custom C# functions and invoke them right in the query through user-defined functions (UDFs). This enables scenarios like complex math calculations, importing custom machine learning models by using ML.NET, and programming custom data imputation logic. Link Link Details
9/26/2018 Stream Analytics New Feature Azure Stream Analytics users can now partition output to Azure Blob storage based on custom date and time formats. Link Link Details
9/26/2018 Stream Analytics New Feature This week at Microsoft Ignite 2018, we are excited to announce eight new features in Azure Stream Analytics (ASA). These new features include Support for query extensibility with C# custom code in ASA jobs running on Azure IoT Edge. Custom de-serializers in ASA jobs running on Azure IoT Edge. Live data Testing in Visual Studio. High throughput output to SQL. ML based Anomaly Detection on IoT Edge. Managed Identities for Azure Resources (formerly MSI) based authentication for egress to Azure Data Lake Storage Gen 1. Blob output partitioning by custom date/time formats. User defined custom re-partition count. Link Link Details
9/26/2018 Monitor Updated Feature Today, we released version 1.16 of the Azure Management Libraries for Java. Now you can programmatically manage Azure Monitor using Azure Management Libraries for Java, specifically, you can: Manage Diagnostic Settings Stream logs and metrics to Event Hub, Storage Account or Log Analytics Query Metrics Set up Metric Alerts Query Activity Logs Set up Activity Log Alerts Setup Auto Scale Perform Advanced Analytics Link Link Details
9/24/2018 Stream Analytics Preview Feature C# user-defined functions (UDF) support for Azure Stream Analytics on IoT Edge is now available in preview. Link Link Details

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