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Durable Functions now supports a new stateful entities pattern, enabling you to build stateful Azure Functions that map to an actor.
IoT Central is introducing new capabilities that are designed to simplify IoT Central for developers and enable integration to a customer’s existing enterprise and line of business solutions by enabling more seamless integration to a customer’s existing enterprise and line of business solutions.
With a wire-protocol compatible API for etcd on top of Azure Cosmos DB, developers will automatically get highly reliable, globally distributed and highly available Kubernetes and K8 tools with no code changes or management required.
Today we’re announcing IoT Plug and Play, which is based on an open modeling language that allows developers to connect IoT devices to the cloud without having to write any code.
Now you can manage your AWS spend along your Azure spend in Azure Cost Management
Red Hat Enterprise Linux images are now available as both BYOS and PAYG offers.
Azure Shared Image Gallery makes it easier to manage, share and distribute custom virtual machine (VM) images in Azure. Shared Image Gallery is now generally available in all public cloud regions.
Azure Bot Service, built on Microsoft Bot Framework, makes it easier to develop bots and intelligent agents. New enhancements include: Adaptive dialogs enable developers to create more sophisticated, dynamic conversations.
Language Understanding service makes it easier to build language models by extending roles to all entity types, dynamic lists, and providing a new analytics dashboard.
QnA Maker now can handle multi-turn conversation and is even more simple to deploy without code
Logic Apps provides the ability to send and receive RosettaNet based messages through RosettaNet connector, which supports the operations to decode or receive and encode or send messages.
Azure Container Instances (ACI) now supports Windows Server 2019 based containers in public preview
Features include: Model Interpretability - Machine learning interpretability allows data scientists to explain machine learning models globally on all data, or locally on a specific data point using the state-of-art technologies in an easy-to-use and scalable fashion. Machine Learning interpretability incorporates technologies developed by Microsoft and proven third-party libraries (for example, SHAP and LIME).
The native integrations of GitHub Enterprise with Visual Studio and Azure DevOps make it easier and faster for your development teams to adopt Git.
At Build, Azure Data Explorer will preview the capability for enterprises to query data from ADLS Gen 2 without ingesting data
Spark connector for Azure Data Explorer and ability to run inline Python and R as part of the query.
Features include: Open Datasets - Open Datasets are a collection of datasets from the public domain to accelerate the development of machine learning models built in Azure. Open Datasets integrates with Machine Leaning Studio or can be accessed from python notebooks in Azure Machine Learning Service.
GitHub identities are now supported as sign in option to log in to Azure. An existing Microsoft account is no longer needed to sign in to Azure.
By using built-in support for Apache Spark and Jupyter notebooks, Azure Cosmos DB helps reduce time to insights by ingesting and serving data and running analytics against the local database replica in an Azure region.
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