Earlier this year in July, we announced the public preview for Virtual Network Service Endpoints and Firewall rules for both Azure Event Hubs and Azure Service Bus. Today, we’re excited to announce that we are making these capabilities generally available to our customers.
In today’s high-productivity environment, processing large amounts of data each millisecond is becoming a common business requirement. This is why an internal Microsoft project named for “a trillion events per day” is now available under open-source as Trill.
Azure Functions is a serverless compute service that enables you to run code on-demand without having to explicitly provision or manage infrastructure. Using Azure Functions, you can run a script or piece of code in response to a variety of events.
Although it’s not a typical use case for Azure Functions, a single Azure function is all it took to fully implement an end-to-end, real-time, mission-critical data pipeline for a fraud detection scenario. And it was done with a serverless architecture.
Today we are sharing an update to the Azure HDInsight integration with Azure Data Lake Storage Gen 2. This integration will enable HDInsight customers to drive analytics from the data stored in Azure Data Lake Storage Gen 2 using popular open source frameworks such as Apache Spark, Hive, MapReduce, Kafka, Storm, and HBase in a secure manner.
HDInsight covers a wide variety of big data technologies, and we have received many requests for a detailed guide. Whether you want to just get started with HDInsight, or become a Big Data expert, this post has you covered with all the latest resources.
Since we announced the limited public preview of Azure Data Lake Storage (ADLS) Gen2 in June, the response has been resounding. Customers participating in the ADLS Gen2 preview have directly benefitted from the scale, performance, security, manageability, and cost-effectiveness inherent in the ADLS Gen2 offering.
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.
We recently published a blog on a fraud detection solution delivered to a banking customer. The solution required complete processing of a streaming pipeline for telemetry data in real-time using a serverless architecture. This blog describes the evaluation process and the decision to use Microsoft Azure Functions.
We are pleased to reveal the release of Spark Interactive Console in Azure Toolkit for IntelliJ. This new component intends to facilitate your Spark job authoring, and enable you to run code interactively in a shell-like environment within IntelliJ.