The rise of cloud technology has enabled digital transformation efforts for enterprises, SMBs, and governments, said Scott Guthrie, an executive vice president of Microsoft’s cloud and enterprise group, at Microsoft Ignite in Orlando on Monday.

“While the vast majority of organizations have moved to a cloud-first technology strategy, most are still early on realizing this strategy due to a number of aspects from complexity of existing systems, to incomplete cloud capabilities, to emerging privacy regulations,” Guthrie said in a media release.

At the conference, Guthrie laid out the four areas in which the company is advancing Azure to remove cloud barriers for enterprises:

1. Enabling IT and developer productivity

Companies moving increasingly large, complex applications to the cloud require a comprehensive set of tools to build, deploy, and run them efficiently, Guthrie said. On Monday, Microsoft announced the Azure Data Box, which enables fast and secure data migration to Azure. Businesses can order the Data Box from the Azure portal, load it with up to 100TB of data, and ship it back to Microsoft, which will ingest it into Azure.

SEE: Securing Windows policy (Tech Pro Research)

2. Providing a consistent hybrid cloud

Azure Stack allows organizations to build and deploy apps using the same APIs, tools, and experiences they would have in the Azure cloud, to enable consistent development across cloud and on-premises. At Ignite, Guthrie announced that Azure Stack integrated systems are now shipping and available for purchase from OEM partners including Dell EMC, HPE, and Lenovo.

“Now developers can build one application and have it run in Azure or locally on Azure Stack, opening up new uses cases such as edge and disconnected solutions and meeting literally every regulatory requirement,” Guthrie wrote in the release.

Microsoft also announced the general availability of SQL Server 2017–the first version of SQL Server to run on Windows Server, Linux, and Docker. SQL Server 2017 enables in-database advanced machine learning, with support for scalable Python and R-based analytics–which allows you to train advanced models more easily with data inside SQL server, without having to move data.

“The bottom line is that SQL Server 2017 delivers industry leading mission critical performance and security with everything built-in, including AI, now on the platform of your choice,” Guthrie said in the release. “These are just some of the reasons that dV01 moved onto SQL Server 2017 on Linux and is experiencing unmatched performance and value.”

Microsoft also announced the new, fully-automated Azure Database Migration Service and SQL DB Managed Instance, allowing customers to easily lift and shift their on-premises SQL server databases to an Azure SQL database with near-zero downtime.

SQL Data Warehouse will deliver a new, optimized for compute performance tier, significantly improving the performance of analytics in the cloud, with workloads running up to 2x. This tier also scales up to 30,000 compute Data Warehouse Units. The preview will be available in the fall.

Further, Azure Hybrid Benefit for SQL Server will allow customers to maximize existing license investments with rates discounted up to 50%.

SEE: Azure data platform analysis: Enterprise use cases and services (Tech Pro Research)

3. Unlocking AI solutions

Microsoft announced that it will bring Azure Cosmos DB database server to its serverless offering, Azure Functions, for event-based, serverless systems. “This new combination of Azure Cosmos DB and Azure Functions enables developers to use event-driven serverless computing at near-infinite global scale,” Guthrie said in the release. UK retailer ASOS is currently using this approach to offer customers real-time personalization and recommendations, he added.

Finally, Microsoft previewed new Azure Machine Learning updates that offer AI developers and data scientists a new set of tools to develop and manage machine learning and AI models in the cloud, on-premises, or on the edge. A new Machine Learning Workbench is designed to improve AI productivity of these professionals, and brings DevOps to AI development with comprehensive model management and agile experimentation using open tools.

“AI developers and data scientists can now use Azure Machine Learning to develop, deploy, and manage machine learning and AI models on any type of data, on any scale, in Azure and on-premises,” Guthrie said in the release.

4. Ensuring trust through security, privacy and cost controls

Microsoft is adding in new security and privacy protections for Azure, including Azure confidential computing, which enables encryption of data while in use, and an Azure DDoS protection service, which monitors the public IP addresses of resources with Azure, learns an application’s normal traffic patterns, and automatically mitigates a DDoS attack when detected.

The tech giant will also expand the integrated Azure Security Center capabilities to include monitoring and protecting on-premises systems, to allow for full hybrid cloud security management and threat detection.

The new Azure Cost Management Services, featuring a Cloudyn integration, will help users manage and optimize cloud spending in a single, unified view, across multi-cloud environments. The service will be free for all Azure customers and partners, Guthrie said.

“Today’s announcements, and the entire Azure team’s work over the past year is focused on ensuring Azure is the cloud that can meet the most rigorous and mission critical requirements of governments and enterprise customers, with the cost efficiency and productivity necessary for every start up and small business,” Guthrie said in the release.