Amazon Web Service exec on competing with Google and Microsoft

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

It’s been a busy past couple of weeks in the IaaS cloud with Google Cloud Platform and Microsoft each holding major user events and announcing significant advancements, which continues to put pressure on the company many consider to be the market leader: Amazon Web Services.

matt wood aws

Matt Wood

AWS is gearing up for its own international tour of summits this spring and summer, culminating with its re:Invent annual user conference in December. Network World caught up with AWS’s General Manager for Product Strategy Matt Wood – who has a PhD in Bioinformatics - to discuss the increasing competition in the IaaS market and how customers are using some of AWS’s newest features.

NWW: The big IaaS cloud providers – Amazon, Microsoft, Google and IBM – have been talking a lot recently about machine learning, real-time data processing (like Amazon’s Kenesis), and event-driven computing platforms (like Amazon Lambda). Sometimes I wonder if these services are significantly ahead of where customers are in using this technology though. Are these technologies the next big thing for the cloud?

Matt Wood: Well our approach isn’t just to build cool products. Our approach is very much more focused on real material customer feedback.

I tend to look at it in three buckets. There is the ‘you want to know what happened in the past’ bucket. Customers want to ask increasingly complicated questions about increasingly complicated data that has been aggregated from an increasingly disparate set of sources. For customers who want to do this, we have Amazon Redshift, the canonical data warehouse that you can get data into and then run queries against it. (Event-driven computing platform) Lambda is really good at ETL-style workloads, in which you can collect data coming in real-time and then load that data into Amazon Redshift. Lambda’s also good for running data warehousing queries. Plus, we have tools like Amazon QuickSight, which allow you to both visually query that data and share the results of those queries. That’s one bucket: What happened in the past, given all this aggregate information?

Then there’s the ‘what’s happening right now’ view. This is all about real-time streaming data analytics. Lambda plays a really key role here, in terms of accepting a stream from Kenesis and Lambda will respond on the other end. You can just put a real-time data stream into Kenesis and Lambda can handle it.

This is really helpful because Lambda scales, and you only pay for the functions as they run, so it responds to peaks and ebbs and flows in streaming data, and you only pay for it as you use it. Lambda can take that information and process it in a multitude of different ways from a real-time stream. This is really important for IoT, where you want to add as much smarts to existing devices as possible. You can’t run around and install a bunch of over the air updates to these devices because they could be in remote, disparate locations or because they may not have power or network connection.

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