Amazon Web Service exec on competing with Google and Microsoft

Plus, would AWS ever offer a private cloud? Do customers outgrow the cloud?

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But Lambda allows you to continually improve the logic and respond to changes in that data using pretty detailed rules across the content of the messages. Data streams and IoT are making a lot of use of data in real time, and tools like Kenesis and Lambda are great at managing all that data.

And then a third bucket is: You want to know ‘what will happens in the future?’ That’s where Amazon Machine Learning plays a role. It allows you to provide very low-latency, high-load, real-time predictions on models you’ve already trained. Lambda can be integrated to execute those predictions based on the Machine Learning API, then send that data back to your apps.

Google’s cloud has been making a big deal recently about its machine learning, big data and cognitive computing functionality. The company recently developed a program that beat highly-ranked players at the ancient game of Go, for example. What would you say to people who see Google as a more savvy big data, machine learning company compared to Amazon and AWS?

If you look at one of the very early screenshots of the gateway page from around 1996, there were just books available but a million titles. But even in 1996 you would have seen a feature called ‘Eyes and Editors’ which was an early foray into using machine learning to help customers navigate a large and growing catalog of products on Amazon retail. That was very early on and of course since then we’ve been using machine learning and artificial intelligence across the company.

Everything from recommendations – people who read this also read this; people who bought this also bought this – to helping guide customers through the very broad catalog that we have and using it for fulfillment. We do a lot of work with fraud detection and prevention; we sponsor two professorships in machine learning at the University of Washington. In addition to all of that, we took all of that internal knowledge and technology and exposed it to customers through AWS with Amazon Machine Learning.

I’m pretty comfortable with the credentials we’ve built up in Machine Learning. We apply those relentlessly across the company for the benefit of customers in helping search, identify and discover, and then helping developers apply those exact same algorithms to the data sets they already have on AWS, allowing them to build out both batch and real-time predictions for their applications. I think our credentials are pretty well established.

One of Amazon’s chief competitors, Microsoft, emphasizes its capabilities in hybrid cloud computing as a strategic advantage compared to AWS. Microsoft has plans to offer a product named Azure Stack, which gives customers an infrastructure stack to run in their own data centers that mirrors the Azure public cloud. Correct me if I’m wrong but AWS doesn’t really have something like that. Is the lack of an on-premises AWS cloud holding the company back from a portion of the market that wants something like that?

I wouldn’t say it’s holding us back. We’re a pretty fast growing business and we’re still growing pretty quickly. We probably have on AWS the most successful and largest collection of real enterprise hybrid applications and use cases of hybrid serving as a migration platform to going all in on AWS.

You can look at a company like Johnson & Johnson running 120 apps, which they expect to triple this year, seamlessly integrated across AWS and on-premises; they call it a ‘borderless’ data center where the apps can run between one and the other. We have folks like Comcast who built their new entertainment platform called X1 as a hybrid application that runs on premises and on AWS; it uses the scale of AWS plus their own internal data centers.

Samsung has hybrid applications, which are deployed across their data center plus the cloud; Hitachi is doing integrated resource management across their hybrid cloud of AWS and on-prem. These are not lightweight, un-thoughtful companies; these are large organizations who are running real, core, mission-critical workloads in a hybrid model across AWS and their data centers.

But in terms of an on-premises appliance that would mirror Amazon’s cloud, Amazon doesn’t have anything like that now. Do you ever get requests for that from customers? I know Amazon always talks about doing what customers are asking for.

That’s right. We don’t have anything like that today, but never say never. We’re going to continue to make investments to allow customers to use their on-premises infrastructure and use AWS. It’s a model that we see both as a way of utilizing existing investment, but also as an early stepping stone to much deeper, more thoughtful migration to AWS.

Customers use a combination of Amazon native tools and their on premises management tools. They use the bridges that we’ve built over the past three or four years, such as ones for identity federation, directory services, integrated networking with Direct Connect; we have plugins for vCenter and Systems Center; we have AWS Config and CloudTrail and even a service like CodeDeploy, which you can run on your own premises. We have things like Storage Gateway, which allows you to build out a gateway internally and then take data internally from your on premises environment and back it up to the cloud either for disaster recovery or for data replication. So there’s a pretty broad set of tools available to customers for building hybrid applications.

When you start looking at migrating data, we have things like a physical storage appliance, which we will send you in the form of our Snowball device that you can load data into, and then send it back to us and we’ll upload it to the cloud. We’re seeing huge uptick in our database migration tool, which allows you to select an on-prem database and then select a new database on AWS, click a couple of buttons, and we’ll manage the migration of that data over from places like Oracle and SQL Server on to open source platforms like MySQL, or increasingly into Amazon Aurora. We’ve already seen over 1,000 databases move since we made the announcement of database migration services, and it went into GA just last month. 

Do companies ever out-grow the cloud? Recently, I spoke with officials at Dropbox, who believe that they can run some of their applications more efficiently in a custom-built internal infrastructure stack compared to using the public cloud. The CTO of Bank of America told me they have found no economic reason to move to the cloud. Especially with open source initiatives like the Open Compute Project, is there a point where it’s more efficient to run some workloads on-premises compared to in the cloud?

Our stated mission and belief continues to be that in the fullness of time, most companies will not run their own data centers. We’ve seen that to be the case for startups that are going through enormous growth. Folks like Airbnb, Instacart and Tinder start on the cloud but then they remain on the platform as they go through that growth and stabilize. We’ve seen large-scale enterprises who have made the choice to make really key, strategic migrations to AWS.

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