四月 2024
.Net Standard user-defined functions for Azure Stream Analytics will be retired on 30 September 2024.
目標淘汰日期: 十月 01, 2024
.Net Standard user-defined functions for Azure Stream Analytics will be retired on 30 September 2024. After that date, it won’t be possible to use the feature. Please transition to JavaScript user-defined functions for Azure Stream Analytics.
三月 2024
Custom .net deserializer for Azure Stream Analytics will be retired on 30 September 2024
目標淘汰日期: 十月 01, 2024
Custom .net deserializer for Azure Stream Analytics will be retired on 30 September 2024. After that date, it won't be possible to use the feature. Please transition to a JSON, AVRO, or CSV built-in deserializer by that date.
一月 2024
Azure Stream Analytics No-code Editor: new features and improvements in Jan 2024
Enhancements and new features have been introduced to the Stream Analytics no-code editor, accessible through both the Azure Event Hubs portal and the Azure Stream Analytics portal. These updates aim to deliver a more intuitive and user-friendly experience for users.
十一月 2023
Public Preview: Kafka Input and Output with Azure Stream Analytics
目標可用性: Q4 2023
You can connect directly to Kafka to ingest from Kafka clusters or output data to Kafka clusters in your Azure Stream Analytics (ASA) job.
Public Preview Preview: Protocol Buffers (Protobuf) with Azure Stream Analytics
目標可用性: Q4 2023
You can ingest events in protobuf format into Azure Stream Analytics using a built-in deserializer.
七月 2023
Public preview: Stream Analytics No-Code Editor available in Azure Stream Analytics Portal
The no-code editor is now available in Azure Stream Analytics portal to enable building your Stream Analytics jobs effortlessly, no coding required.
五月 2023
Setting Up a CI/CD Pipeline with GitHub Actions for Stream Analytics Jobs
Are you using GitHub for managing your Stream Analytics project and looking to leverage GitHub's powerful CI/CD pipeline? Follow this comprehensive guide and learn to set up a CI/CD pipeline with GitHub Actions for your Stream Analytics jobs.
Generally Available: Exactly Once Delivery to ADLS Gen2 Output
Azure Stream Analytics supports for end-to-end exactly once semantics when writing to Azure Data Lake Storage Gen2.
Private Preview: Kafka Input and Output with Azure Stream Analytics
目標可用性: Q2 2023
You can connect directly to Kafka to ingest from Kafka clusters or output data to Kafka clusters in your Azure Stream Analytics (ASA) job.
Generally Available: Exactly Once Delivery to Event Hub Output
Stream Analytics now supports end-to-end exactly once semantics when writing to Event Hub output.
Public Preview: Azure Stream Analytics Schema Registry Integration
Azure Stream Analytics can now fetch schema from the Schema Registry and deserialize data from Event Hub inputs for Avro format.
四月 2023
使用受控私人端點將 Azure 串流分析連線到 Azure 資料總管。
目標可用性: Q2 2023
您可以使用受控私人端點,將 Azure 串流分析作業連線到 Azure 資料總管/Kusto 叢集
Use Stream Analytics to process exported data from Application Insights
目標可用性: Q2 2023
Use Stream Analytics to process exported data from Application Insights
二月 2023
General availability: Stream Analytics no-code editor updates in Feb 2023
New features are now available in Stream Analytics no-code editor GA including Power BI output support, and data preview optimization. Power BI output feature enables you to build real-time dashboard in minutes and low-cost.
一月 2023
Public preview: Capture Event Hubs data with Stream Analytics no-code editor in Delta Lake format
Stream Analytics no-code editor now supports capturing Event Hubs data into ADLS gen2 with Delta Lake format.
十二月 2022
正式運作:2022 年 12 月的串流分析無程式碼編輯器更新
串流分析無程式碼編輯器 GA 現已推出新功能,包含支援多個參數內建函數、在 ADLS Gen2 輸出接收器中支援 Delta Lake 格式。
Public preview: Processor diagram in Physical Job Diagram for Stream Analytics job troubleshooting
The processor diagram in physical job diagram provides you further insights within the streaming nodes of your stream analytics jobs.
十月 2022
General availability: Stream Analytics no-code editor in Event Hubs
Stream Analytics no-code editor enables you to develop a Stream Analytics job in minutes with drag and drop experience. Now, it is generally available with several new capabilities added.
公開預覽:Azure Data Lake Storage Gen2 的正好一次傳遞
串流分析現在可在寫入 Azure Data Lake Storage Gen2 時支援端對端的正好一次語意。
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