20

Jun

Column-Level Security is now supported in Azure SQL Data Warehouse

Today we’re announcing Column-Level Security (CLS) for Azure SQL Data Warehouse, an additional capability for managing security for sensitive data. Azure SQL Data Warehouse is a fast, flexible and secure cloud data warehouse tuned for running complex queries fast and across petabytes of data.

As you move data to the cloud, securing your data assets is critical to building trust with your customers and partners. With the introduction of CLS, you can adjust permissions to view sensitive data by limiting user access to specific columns in your tables without having to redesign your data warehouse. This simplifies the overall security implementation as the access restriction logic is located in the database tier itself rather than away from the data in another application. CLS eliminates the need to introduce views to filter out columns for access control management.

Some examples of how this is being used today:

A financial services firm allows only account managers to have access to customer social security numbers (SSN), phone numbers, and other personally identifiable information (PII). A health care provider allows only doctors and nurses to have access to sensitive medical records while not allowing members of the billing department to view this data.

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20

Jun

Column-Level Security is now supported in Azure SQL Data Warehouse

Today we’re announcing Column-Level Security (CLS) for Azure SQL Data Warehouse, an additional capability for managing security for sensitive data. Azure SQL Data Warehouse is a fast, flexible and secure cloud data warehouse tuned for running complex queries fast and across petabytes of data.

As you move data to the cloud, securing your data assets is critical to building trust with your customers and partners. With the introduction of CLS, you can adjust permissions to view sensitive data by limiting user access to specific columns in your tables without having to redesign your data warehouse. This simplifies the overall security implementation as the access restriction logic is located in the database tier itself rather than away from the data in another application. CLS eliminates the need to introduce views to filter out columns for access control management.

Some examples of how this is being used today:

A financial services firm allows only account managers to have access to customer social security numbers (SSN), phone numbers, and other personally identifiable information (PII). A health care provider allows only doctors and nurses to have access to sensitive medical records while not allowing members of the billing department to view this data.

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20

Jun

Disaster Recovery solution for Azure IaaS applications

On June 4th 2018, Corey Sanders announced the general availability of Disaster Recovery (DR) for Azure Virtual Machines (VMs) using Azure Site Recovery (ASR) in his blog post about why you should bet on Azure for your infrastructure needs today and in the future. Azure is the first public cloud to offer native Disaster Recovery solution for applications running on IaaS. With this offering, you can make your applications resilient to even region level failures by replicating VMs into another region. Along with Availability Sets and Availability Zones, Azure Site Recovery completes the resiliency continuum for applications running on Azure Virtual Machines.

Key benefits No infrastructure required: You do not need any additional software infrastructure (VMs or appliances) in your Azure subscription to enable this functionality. You avoid all the complexity and cost associated with deploying, monitoring, patching and maintaining any DR infrastructure.

“By using ‘Azure to Azure DR’, Microsoft’s Universal Store Team (UST), who develops and operates Microsoft’s core commerce Store and systems, was able to use its previously DR validated platform on-premises to perform the equivalent on Azure. Without ASR, the Universal Store team would have spent substantial resources deploying a new instance of the legacy

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20

Jun

Disaster Recovery solution for Azure IaaS applications

On June 4th 2018, Corey Sanders announced the general availability of Disaster Recovery (DR) for Azure Virtual Machines (VMs) using Azure Site Recovery (ASR) in his blog post about why you should bet on Azure for your infrastructure needs today and in the future. Azure is the first public cloud to offer native Disaster Recovery solution for applications running on IaaS. With this offering, you can make your applications resilient to even region level failures by replicating VMs into another region. Along with Availability Sets and Availability Zones, Azure Site Recovery completes the resiliency continuum for applications running on Azure Virtual Machines.

Key benefits No infrastructure required: You do not need any additional software infrastructure (VMs or appliances) in your Azure subscription to enable this functionality. You avoid all the complexity and cost associated with deploying, monitoring, patching and maintaining any DR infrastructure.

“By using ‘Azure to Azure DR’, Microsoft’s Universal Store Team (UST), who develops and operates Microsoft’s core commerce Store and systems, was able to use its previously DR validated platform on-premises to perform the equivalent on Azure. Without ASR, the Universal Store team would have spent substantial resources deploying a new instance of the legacy

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19

Jun

AI Lab: Learn to Code with the Cutting-Edge Microsoft AI Platform

This post is authored by Tara Shankar Jana, Senior Technical Product Marketing Manager at Microsoft.

Among our exciting announcements at //Build, one of the things I was thrilled to launch is the AI Lab – a collection of AI projects designed to help developers explore, experience, learn about and code with the latest Microsoft AI Platform technologies.

What is AI Lab?

AI Lab helps our large fast-growing community of developers get started on AI. It currently houses five projects that showcase the latest in custom vision, attnGAN (more below), Visual Studio tools for AI, Cognitive Search, machine reading comprehension and more. Each lab gives you access to the experimentation playground, source code on GitHub, a crisp developer-friendly video, and insights into the underlying business problem and solution. One of the projects we highlighted at //Build was the search and rescue challenge which gave the opportunity to developers worldwide to use AI School resources to build and deploy their first AI model for a problem involving aerial drones.

AI Lab is developed in partnership with Microsoft’s AI School and the Microsoft Research (MSR) AI organization.

AI Lab Experiments

We released the following experiments from Microsoft at //Build:

1. DrawingBot
At the

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19

Jun

Immutable storage for Azure Storage Blobs now in public preview

Financial Services organizations regulated by SEC, CFTC, FINRA, IIROC, FCA etc. are required to retain business-related communication in a Write-Once-Read-Many (WORM) or immutable state that makes it non-erasable and non-modifiable for a certain retention interval. The immutable storage requirement is not limited to financial organizations, but also applies to industries such as healthcare, insurance, media, public safety, and legal services.

Today, we are excited to announce the public preview of immutable storage for Azure Storage Blobs to address this requirement. The feature is available in all Azure public regions. Through configurable policies, users can keep Azure Blob storage data in an immutable state where Blobs can be created and read, but not modified or deleted.

Typical applications include: Regulatory compliance: Immutable storage for Azure Blobs is designed to help financial institutions and related industries address SEC 17a-4(f), CFTC 1.31©-(d), FINRA etc. A technical whitepaper with details on how the feature addresses these regulatory requirements will be available soon. The Azure Trust Center contains detailed information about our compliance certifications. Secure document retention: Users receive maximum data protection as the immutable storage feature for Azure Blobs service ensures that data cannot be modified or deleted by any user including those with

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19

Jun

Enabling Smart Manufacturing with Edge Computing

Smart Manufacturing envisions a future where factory equipment can make autonomous decisions based on what’s happening on the factory floor. Businesses can more easily integrate all steps of the manufacturing process including design, manufacturing, supply chain and operation. This facilitates greater flexibility and reactivity when participating in competitive markets. Enabling this vision requires a combination of related technologies such as IoT, AI/machine learning, and Edge Computing. In this article, we will introduce Edge Computing and discuss its role in enabling Smart Manufacturing.

What is Edge Computing?

Put simply, Edge Computing is about taking code that runs in the cloud and running it on local devices or close to it. Like in a gateway device or a PC sitting next to the device.

To understand Edge Computing it helps to think of an IoT solution as generally having three components:

Things like IoT devices, which generate sensor data. Insights you extract from this data. Actions you perform based on these insights to deliver some sort of value.

With Edge Computing, you move the insights and actions components from the cloud to the device. In other words, you bring some of the code used to process and extract insights from the data,

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19

Jun

Azure Data ingestion made easier with Azure Data Factory’s Copy Data Tool

Azure Data Factory (ADF) is the fully-managed data integration service for analytics workloads in Azure. Using ADF users can load the lake from 70+ data sources, on premises and in the cloud, use rich set of transform activities to prep, cleanse, process the data using Azure analytics engines, and finally land the curated data into a data warehouse for reporting and app consumption. With ADF you can iteratively develop, debug, and continuously integrate and deploy into dev, QA, and production environments, enabling you to achieve productivity during development phrase as well as operationalize and manage your Extract Transform Load /Extract Load Transform workflows holistically.

All analytics solutions start with loading data from diverse data source into data lake. As part of January 2018 release of ADF Visual Tool, we released Copy Data Tool which allows you to easily set up a pipeline to accomplish the data loading task in minutes, without having to understand or explicitly set up Linked Services and datasets for source and destination. We continuously listened to your feedback and today we are happy to announce the latest set of enhancements to the Copy Data Tool making it easier to ingest data at scale:

Support ingesting data

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19

Jun

Maven: Deploy Java Apps to Azure with Tomcat on Linux
Maven: Deploy Java Apps to Azure with Tomcat on Linux

We are pleased to announce a new feature in the Maven Plugin for Azure App Service. The plugin provides seamless integration of Azure services into Maven projects. With only one step, you can deploy your WAR file to Azure Web Apps on Linux with the built-in running stack of Java 8 and Tomcat 8.5 or 9.0. By leveraging Maven, the Azure App Service plugin is portable and can be integrated with your IDEs and CI/CD pipelines easily.

Web apps with Tomcat on Linux

A couple of months ago, we announced the preview release of built-in support for Java 8 and Tomcat 8.5/9.0 on Web Apps on Linux. This allows developers to get their Java apps up and running on Azure in a managed environment, benefitting from auto-scaling and high availability.

Getting started with Maven

After creating a new Azure Web App, choose Linux for OS and Tomcat as stack. Save the information of this new Web App to configurate the Maven plugin. Open the pom.xml file and add the following settings in the <configuration> section.

<!– Web App information –> <resourceGroup>your-resource-group</resourceGroup> <appName>your-app-name</appName> <!– Java Running Stack for Web App on Linux–> <linuxRuntime>tomcat 8.5-jre8</linuxRuntime> <!– Deployment Type –> <deploymentType>war</deploymentType>

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19

Jun

Introducing the redesigned Security Center Overview dashboard

Azure Security Center’s dashboard has been redesigned to provide cross-subscription, organizational level reports of the most important metrics that influence the organizational security posture, as well providing actionable insights to help organizations improve their overall security posture.

The redesigned dashboard also introduces two new concepts in Security Center:

Subscription Coverage: This metric presents the Security Center status of all subscriptions the user has (at least) read access to and helps identify subscriptions lack adequate security controls. NOTE: In order to gain visibility to all subscriptions under your AAD tenant, it is required to set either a Reader, Security Reader or Security Administrator role on the root Management Group. To learn more about the Azure Management Groups integration with Security Center, visit Integrate Security Center security policies with Azure Policy.

Policy Compliance: This metric conveys the organization’s adherence to the security policies assigned to its resources.
Actionable insights reside on the right-hand side of each of their respective areas and include the following:

Policy and compliance: Policy compliance over time, connecting Security Center to a SIEM solution and a guide to using security policies in Security Center

Resource security hygiene: Most prevalent recommendations and highest impact recommendations

Threat protection: Most

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