Azure DevOps

When we launched Azure Spring Cloud with VMware in 2019, we set out to solve common challenges developers, IT operators, and DevOps teams face when running Spring Boot applications at scale.

Enterprises are increasingly defined by the applications they use and build to run their core business processes, including the customer experiences they provide.

As Mark mentioned when he authored the Advancing Reliability blog series, building and operating a global cloud infrastructure at the scale of Azure is a complex task with hundreds of ever-evolving service components, spanning more than 160 datacenters and across more than 60 regions.

In part one of our two-part series, we will peek behind the Azure.com web page to show you how we think about running a major brand website on a global scale.

In part two of our two-part series we share our blueprint, so you can learn from our experience building a website on global scale and move forward with your own website transformation.

Thank you for your response to our cloud continuity blogs; many of you have told us that this information is helpful. We’re committed to providing further posts when we have additional information.

Vernon Turner is the Founder and Chief Strategist at Causeway Connections, an information and communications technology research firm.

At Microsoft, we know DevOps adoption can be challenging. This is why we are excited to share our own journey, with learnings from teams across Microsoft who have transformed the way they work through DevOps adoption.

We are highlighting key Azure Infrastructure enhancements that further power our customers’ digital transformation journey.

News and updates from Azure Bastion, Azure Cognitive Services, Power Platform, and more.

Last month, Microsoft released Azure Blockchain Service making it easy for anyone to quickly setup and manage a blockchain network and providing a foundation for developers to build a new class of multi-party blockchain applications in the cloud.

At Microsoft Build 2019 we announced MLOps capabilities in Azure Machine Learning service. MLOps, also known as DevOps for machine learning, is the practice of collaboration and communication between data scientists and DevOps professionals to help manage the production of the machine learning (ML) lifecycle.