Adi Krishnan and Ryan Waite, AWS, at AWS Summit 2014 with John Furrier and Jeff Frick
@thecube
#AWSSummit
While the cloud allows most organizations easy access to nearly unlimited compute power, it also creates significant complexity and scaling challenges. Approaching these issues with the same IT strategy of years past will fail. Simply put, companies need to first and foremost be open to the idea of change--from team hierarchies to cloud deployments to automation tools.
With an open mind-set, only then can you change your practices to embrace DevOps principles and align development and operations on the same end goal. At this year's AWS Summit, Amazon's foothold into the enterprise, as developers, IT, marketing and other departments utilize its cloud offerings for a myriad of projects.
DevOps is really about change, both cultural and tooling change, and the industry winner will need to appeal to developers, and succeed in automation for proper integration of its cloud solutions. SiliconANGLE's editor-in-chief John Furrier thinks that AWS is "still not ready for prime time," but Amazon is clearly disrupting an entire industry with its AWS solutions, and making the right moves.
Amazon's take on DevOps from the Amazon Kinesis team
.
John Furrier and Jeff Frick, theCUBE co-hosts, interviewed Aditya Krishnan, AWS Sr. Product Manager for Kinesis, and Ryan Waite, General Manager of Data Services at Amazon Web Services, at AWS Summit 2014 in San Francisco to talk about how Amazon helps solve DevOps problems by providing a fully managed service that takes care of all the heavy lifting for developers, providing easy data ingestion and storage, high data durability and the ability to scale seamlessly from kilobytes to terabytes an hour.
Furrier describes Amazon Kinesis as the full real-time processing of large data streaming service, facilitating the development of applications dealing with real-time data. He added that Amazon has added extra features to Kinesis, which is helping developers to scale data up and down as needed. Furrier inquired about the new developments going on around Kinesis world.
Waite said Kinesis can store and process terabytes of data an hour from hundreds of thousands of sources. Data is replicated across multiple availability zones to ensure high durability and availability.
Waite added that in terms of use and usefulness, Kinesis can collect and process hundreds of terabytes of data per hour from hundreds of thousands of sources. This means that developers will be able to write applications that process information in real-time from sources (such as website click-streams or sensors for the Internet of Things) that handle social media, operational logs, metering data or any other data.
Furrier stated that the "use of data is shifting new development paradigm. But no one really come out yet on a development kit or developer framework for data."
He then asked of Amazon's approach of data framework for developer?
Krishnan said, "most big data processing has been done through batch-oriented approaches such as those used by Hadoop, or through database technologies such as data warehouses. To build applications that rely on this fast-moving data, many companies have developed their own systems or stitched together open source tools, but these are often complex to build, difficult to operate, inelastic and hard to scale and can be unreliable or lose data. Amazon Kinesis helps solve these problems by providing easy data ingestion and storage, high data durability and the ability to scale seamlessly."
Commenting on the composite application development across team in implementing DevOps, Furrier asked if is this DevOps 2.0. "What's next after DevOps? What Amazon's take on next DevOps model?"
"DevOps is a great model, it really worked for number of startup companies. Amazon's ability to take data from Kinesis and pump that right into Elastic MapReduce makes it easy for people to use their existing applications with the new system like Kinesis," said Waite. "That kind of composing of applications accelerate DevOps and Amazon is continue to do so more and more kind of work," he added.
Furrier asked what kind of challenges and issues Amazon faced adopting this model in terms of use and usefulness. Waite said initially Kinesis used to collect and process hundreds of terabytes of data in around 100 milliseconds. But that is high SLA time for customers. As data streams in, the team reduces the data upload to 30 to 40 millisecond.
With Amazon Kinesis, customers can quickly and easily add real-time analytics and other functionality to their applications, turning today's explosive data growth into an opportunity to build competitive advantage and innovate for their customers, he added.
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Adi Krishnan & Ryan Waite | AWS Summit 2014
Adi Krishnan and Ryan Waite, AWS, at AWS Summit 2014 with John Furrier and Jeff Frick
@thecube
#AWSSummit
While the cloud allows most organizations easy access to nearly unlimited compute power, it also creates significant complexity and scaling challenges. Approaching these issues with the same IT strategy of years past will fail. Simply put, companies need to first and foremost be open to the idea of change--from team hierarchies to cloud deployments to automation tools.
With an open mind-set, only then can you change your practices to embrace DevOps principles and align development and operations on the same end goal. At this year's AWS Summit, Amazon's foothold into the enterprise, as developers, IT, marketing and other departments utilize its cloud offerings for a myriad of projects.
DevOps is really about change, both cultural and tooling change, and the industry winner will need to appeal to developers, and succeed in automation for proper integration of its cloud solutions. SiliconANGLE's editor-in-chief John Furrier thinks that AWS is "still not ready for prime time," but Amazon is clearly disrupting an entire industry with its AWS solutions, and making the right moves.
Amazon's take on DevOps from the Amazon Kinesis team
.
John Furrier and Jeff Frick, theCUBE co-hosts, interviewed Aditya Krishnan, AWS Sr. Product Manager for Kinesis, and Ryan Waite, General Manager of Data Services at Amazon Web Services, at AWS Summit 2014 in San Francisco to talk about how Amazon helps solve DevOps problems by providing a fully managed service that takes care of all the heavy lifting for developers, providing easy data ingestion and storage, high data durability and the ability to scale seamlessly from kilobytes to terabytes an hour.
Furrier describes Amazon Kinesis as the full real-time processing of large data streaming service, facilitating the development of applications dealing with real-time data. He added that Amazon has added extra features to Kinesis, which is helping developers to scale data up and down as needed. Furrier inquired about the new developments going on around Kinesis world.
Waite said Kinesis can store and process terabytes of data an hour from hundreds of thousands of sources. Data is replicated across multiple availability zones to ensure high durability and availability.
Waite added that in terms of use and usefulness, Kinesis can collect and process hundreds of terabytes of data per hour from hundreds of thousands of sources. This means that developers will be able to write applications that process information in real-time from sources (such as website click-streams or sensors for the Internet of Things) that handle social media, operational logs, metering data or any other data.
Furrier stated that the "use of data is shifting new development paradigm. But no one really come out yet on a development kit or developer framework for data."
He then asked of Amazon's approach of data framework for developer?
Krishnan said, "most big data processing has been done through batch-oriented approaches such as those used by Hadoop, or through database technologies such as data warehouses. To build applications that rely on this fast-moving data, many companies have developed their own systems or stitched together open source tools, but these are often complex to build, difficult to operate, inelastic and hard to scale and can be unreliable or lose data. Amazon Kinesis helps solve these problems by providing easy data ingestion and storage, high data durability and the ability to scale seamlessly."
Commenting on the composite application development across team in implementing DevOps, Furrier asked if is this DevOps 2.0. "What's next after DevOps? What Amazon's take on next DevOps model?"
"DevOps is a great model, it really worked for number of startup companies. Amazon's ability to take data from Kinesis and pump that right into Elastic MapReduce makes it easy for people to use their existing applications with the new system like Kinesis," said Waite. "That kind of composing of applications accelerate DevOps and Amazon is continue to do so more and more kind of work," he added.
Furrier asked what kind of challenges and issues Amazon faced adopting this model in terms of use and usefulness. Waite said initially Kinesis used to collect and process hundreds of terabytes of data in around 100 milliseconds. But that is high SLA time for customers. As data streams in, the team reduces the data upload to 30 to 40 millisecond.
With Amazon Kinesis, customers can quickly and easily add real-time analytics and other functionality to their applications, turning today's explosive data growth into an opportunity to build competitive advantage and innovate for their customers, he added.
