Dr. Matt Wood, AWS, at AWS Re:Invent 2013 2013 with John Furrier and Dave Vellante
It was an action packed week at re:Invent 2013. From making the cloud more transparent to challenging VMware to introducing a stream processing service for the masses, Amazon didn't stop for a breather -- and neither did we. The man behind it all, AWS data science GM Dr. Matt Wood, hopped into theCUBE on Day 3 of the event to share his insider's perspective on the latest wave of cloud and Big Data innovation.
Wood kicks off the interview with a rundown of his company's newest products. He starts with CloudTrail, the free API logging service that sparked a flurry of partner announcements, and goes on to discuss the business continuity features that Amazon introduced with the addition of PostgreSQL support to its Relational Database Service.
These enhancements were all unveiled during Day 1. On Day 2, the cloud titan made an even bigger splash with the launch of two new instance types: I2, for IOPS-intensive workloads such as NoSQL databases, and C3 instances for high-performance apps. After briefly touching on the benefits of each, Wood brings up Amazon Kinesis, the managed service that delivers real time insights on a budget.
Up until 3-5 years ago, the high cost of collecting large volumes of rapidly changing information was the main barrier to stream processing, he reflects. But as sensory innovations made data aggregation economically viable for the enterprise, the bottleneck moved to the data center. In comes Kinesis. The platform "allows an entirely new class of applications to be built and developed without the complexity of having to manage either batch processing, which typically can't keep up at scale, or very very high throughput data streams," Wood explains.
"Kinesis will store the data for 24 hours in a very reliable fashion and in an entirely managed environment, so customers don't have to worry about provisioning the storage and the servers and all the rest of it. They just set the amount of throughput that their application needs and start streaming data straight away," he says.
Kinesis can be used for window analysis to uncover data patterns in specific time frames, Wood continues. It also enables developers to integrate multiple data streams into their applications and dashboards, giving end-users access to actionable information as it comes in.
Watch the interview for more exclusive insight into Amazon's ambitious push toward the intersection of cloud computing and Big Data.
@thecube
#AWSreinvent
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Dr. Matt Wood, AWS | AWS Re:Invent 2013
Dr. Matt Wood, AWS, at AWS Re:Invent 2013 2013 with John Furrier and Dave Vellante
It was an action packed week at re:Invent 2013. From making the cloud more transparent to challenging VMware to introducing a stream processing service for the masses, Amazon didn't stop for a breather -- and neither did we. The man behind it all, AWS data science GM Dr. Matt Wood, hopped into theCUBE on Day 3 of the event to share his insider's perspective on the latest wave of cloud and Big Data innovation.
Wood kicks off the interview with a rundown of his company's newest products. He starts with CloudTrail, the free API logging service that sparked a flurry of partner announcements, and goes on to discuss the business continuity features that Amazon introduced with the addition of PostgreSQL support to its Relational Database Service.
These enhancements were all unveiled during Day 1. On Day 2, the cloud titan made an even bigger splash with the launch of two new instance types: I2, for IOPS-intensive workloads such as NoSQL databases, and C3 instances for high-performance apps. After briefly touching on the benefits of each, Wood brings up Amazon Kinesis, the managed service that delivers real time insights on a budget.
Up until 3-5 years ago, the high cost of collecting large volumes of rapidly changing information was the main barrier to stream processing, he reflects. But as sensory innovations made data aggregation economically viable for the enterprise, the bottleneck moved to the data center. In comes Kinesis. The platform "allows an entirely new class of applications to be built and developed without the complexity of having to manage either batch processing, which typically can't keep up at scale, or very very high throughput data streams," Wood explains.
"Kinesis will store the data for 24 hours in a very reliable fashion and in an entirely managed environment, so customers don't have to worry about provisioning the storage and the servers and all the rest of it. They just set the amount of throughput that their application needs and start streaming data straight away," he says.
Kinesis can be used for window analysis to uncover data patterns in specific time frames, Wood continues. It also enables developers to integrate multiple data streams into their applications and dashboards, giving end-users access to actionable information as it comes in.
Watch the interview for more exclusive insight into Amazon's ambitious push toward the intersection of cloud computing and Big Data.
@thecube
#AWSreinvent
