Amazon Web Services had a busy week rolling out an onslaught of new services, but perhaps the most important news out of re:Invent 2018 was the big reveal of Amazon Outposts, an on-premises server and storage offering with VMware, in addition to 13 new machine-learning and two blockchain services. Terry Wise, global vice president of channels and alliances, sees a huge opportunity for AWS partners in all of these arenas.
CRN USA caught up with Wise during re:Invent to talk about these new offerings and the value that partners can add. Here are excerpts from the conversation.
What are your thoughts on Amazon Outposts, and what do you expect customer demand to be like?
We expect a lot of customers will want to run VMware because that’s what they've been running on-premise, and their virtualised apps on-prem are already running on VMware. Candidly, when we've been talking to customers, there's a lot of demand for this offering because of that on-premise VMware environment.
Is there going to be a play for partners to set up and manage Outposts?
It will definitely be more of a managed service, but I think of it more as on the application side of things. There's not going to be a huge business for setting up the hardware—we are going to take care of that piece and the logistics behind it.
I think there is a huge partner play because partners don’t actually have to convince customers to go to cloud. They can say, ‘Let's start building cloud apps on AWS and we are going to do it on-premise so you're going to be able to get moving faster.’ There's going to be a huge SI [systems integrator] play, and it's also an extension of the MSP model. MSPs that are managing in the cloud can extend it on-prem. There's just more opportunity all around.
A lot of partners are used to that on-premise environment, so now they can say [to customers], ‘If you want to use Amazon cloud, we can get you on today in your on-premise environment, and we can worry about all the security and compliance stuff in parallel, but we can get you moving now.’ So, I think it’s a great on-ramp and a great way for partners to engage greenfield accounts.
Will there ever be a decoupled hardware offering for partners to sell with a software platform, a hypervisor or a virtualisation platform?
Never say never, but [Outposts] is an integrated system. Over the years, people have really requested this. I wouldn’t even think of it as hardware and software. I see it as an extension of our services.
How important is it for partners that Amazon's latest machine-learning services don't require machine-learning experience or expertise?
Everybody is talking about [machine learning], but no one is really doing it. I think it's an even bigger deal for partners. The more packaged machine learning is and the more they can drive business outcomes, the higher the value is that partners can provide to their customers. Think about a partner using Amazon Forecast who is building a new forecasting tool using machine learning for an insurance company—that's pretty cool and something that's repeatable across that industry.
What's the difference between the two new blockchain services?
Blockchain, I think, is very interesting. The Important thing out of those two announcements [Amazon Quantum Ledger Database and Amazon Blockchain] are the two flavors. Quantum Ledger is really more of that closed blockchain coupled with a centralised ledger, and then there's [Amazon Blockchain,] which is more of a distributed use of a blockchain service.
When we talk to enterprises, they really like the centralised ledger model, and then in some of the newer markets, the decentralized ledger is really interesting. With tools like these, businesses can start taking their first steps with blockchain.
How will Amazon's new storage solutions help empower partners to not only store data, but help customers take advantage of the data they have generated?
We are seeing the whole data and analytics story coming together. A lot of businesses have to keep their data, and they're probably not going to keep it on-premise because it's ridiculously expensive, and even in cloud at the scale we're talking about, it's costly and it's not accessed a lot. Now, with machine learning and solutions like [Glacier Deep Archive for long-term data retention] they can actually store a lot of data much more effectively, and that really feeds the whole machine-learning piece—it all really does come together and it's going to drive a lot of action.