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my job. Their attitude was one of frustration—they were making all this money and now this little squeaky thing called the cloud came along and they didn’t want to bother with it.

      To break out of this impasse, I met with everyone on the STB leadership team individually, taking their pulse, asking questions and listening. Together we had to see that our North Star would be a cloud-first strategy. Our products and technologies would optimize for the cloud, not just for private servers that resided on an organization’s own premises. Though we would be cloud-first, our server strength would enable us to differentiate ourselves as the company that delivered a hybrid solution to customers who wanted both private, on-premise servers and access to the public cloud.

      This new framework helped reshape the argument, breaking down the resistance to going all-in on the cloud. I began to notice a new openness to innovation and a search for creative ways to meet the needs of our commercial customers.

      Unfortunately, Red Dog, which had become Windows Azure, was still struggling. They were trying to leapfrog with a new approach to cloud computing, but the market was clearly giving them feedback that they first needed to meet their current needs. Mark Russinovich, who was an early member of the Red Dog team and the current CTO of Azure, had a clear road map in mind to evolve Azure. We needed to infuse more resources into the team to execute on that road map.

      It was time to move Azure into the mainstream of STB rather than have it be a side project. People, the human element of any enterprise, are ultimately the greatest asset, and so I set about assembling the right team, starting with Scott Guthrie, a very accomplished Microsoft engineer. He had spearheaded a number of successful company technologies focused on developers. I tapped him to lead engineering for Azure on its way to becoming Microsoft’s cloud platform—our answer to Amazon Web Services.

      Over time, many others from both inside and outside the company joined our effort. Jason Zander, another key leader who built .Net and Visual Studio, joined to lead the core Azure infrastructure. We recruited the highly regarded Big Data researcher Raghu Ramakrishnan from Yahoo and James Phillips who had cofounded the database company Couchbase. We relied heavily on the expertise of Joy Chik and Brad Anderson to advance our device management solutions for the mobile world. Under their leadership we made our first major steps in providing business customers the technology they need to secure and manage Windows, iOS, and Android devices. Julia Liuson took over our Visual Studio developer tools, evolving it to be the tool of choice for any developer regardless of platform or app.

      Complementing these world-class engineers was world-class business planning and modeling. Takeshi Numoto moved from the Office team to join STB. Takeshi had been an important member of the team that had strategized and executed the transformation of Office products to a cloud-based, subscription model. And in his role as business lead for STB, he set about building the new commercial model that was based on creating meters to measure consumption of cloud services and inventing new ways to package our products for customers.

      One of the early decisions I made was to differentiate Azure with our data and AI capabilities. Raghu and team designed and built the data platform that could help store and process exabyte-scale data. Microsoft was developing machine learning and AI capability as part of our products such as Bing, Xbox Kinect, and Skype Translator. I wanted us to make this capability available to third-party developers as part of Azure.

      A key hire for Azure was Joseph Sirosh, who I recruited from Amazon. Joseph had been passionately working in ML for all his professional career, and he brought that passion to his new role at Microsoft. Now our cloud not only could store and compute massive amounts of data, it could also analyze and learn from the data.

      The practical value of ML is immense and incredibly varied. Take a Microsoft customer like ThyssenKrupp, a manufacturer in the elevator and escalator business. Using Azure and Azure ML, they can now predict in advance when an elevator or escalator will need maintenance, virtually eliminating outages and creating new value for its customers. Similarly, an insurer like MetLife can spin up our cloud with ML overnight to run enormous actuarial tables and have answers to its most crucial financial questions in the morning, making it possible for the company to adapt quickly to dramatic shifts in the insurance landscape—an unexpected flu epidemic, a more-violent-than-normal hurricane season.

      Whether you are in Ethiopia or Evanston, Ohio, or if you hold a doctorate in data science or not, everyone should have that capability to learn from the data. With Azure, Microsoft would democratize machine learning just as it had done with personal computing back in the 1980s.

      To me, meeting with customers and learning from both their articulated and unarticulated needs is key to any product innovation agenda. In my meetings with customers I would usually bring other leaders and engineers along so that we could learn together. On one trip to the Bay Area, we met with several startups. It became clear that we needed to support the Linux operating system, and we had already taken some rudimentary steps toward that with Azure. But as Scott Guthrie and our team walked out of those meetings that day, it was certain that we needed to make first-class support for Linux in Azure. We made that decision by the time we got to the parking lot.

      This may sound like a purely technical dilemma, but it also posed a profound cultural challenge. Dogma at Microsoft had long held that the open-source software from Linux was the enemy. We couldn’t afford to cling to that attitude any longer. We had to meet the customers where they were and, more importantly, we needed to ensure that we viewed our opportunity not through a rearview mirror, but with a more future-oriented perspective. We changed the name of the product from Windows Azure to Microsoft Azure to make it clear that our cloud was not just about Windows.

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