AWS Kinesis service takes in thousands of knowledge streams, processes them on an Amazon cluster, and provides ends up in near real time.

Kinesis, Amazon Web Services’ new service for processing a high volume of real-time data, corresponding to that pouring off a stock ticker, is open for business. The system was announced, but not made generally available, Nov. 14 during AWS’s Re:Invent event in Las Vegas.

A customer can start off feeding kilobytes of information into Kinesis and move as much as terabytes over the process an hour, reckoning on the demands of the actual-time data stream. Streams from hundreds or thousands of sources, which includes social media, investment research services, or news services, could be added to an original stream, allowing Kinesis to indicate correlations between real-time events.

Breaking news items, inclusive of a report that the anchovy harvest has failed off the coast of Chile, could have a huge impact on trading at an exchange just like the Chicago Board of Trade. Likewise, companies could track Twitter, Facebook, and Google+ traffic following business announcements, akin to the close of a positive quarter or a product line addition.

Kinesis is accessible through AWS’s US East-1 complex in Ashburn, Va., but would be rolled out to other Amazon regional data centers in 2014.

Applications built to exploit Kinesis can produce near real-time dashboards, alerts, and reports that may drive real-time business decision making, equivalent to whether to alter pricing on a hot-selling product or whether to regulate an advertising strategy, in response to Terry Hanold, VP, AWS cloud commerce.

Kinesis applications could collect data from server logs in real time and analyze what’s happening on an internet site during a hectic holiday shopping period, or collect data on dozens or hundreds of devices at the factory floor to identify where the subsequent delay might occur.

One reason to do data-stream analysis within the cloud is that this type of service can elastically expand to fulfill the information streams’ demands. Hanold said within the announcement that consumers can capture data streams with some clicks at the Amazon management console or by programming an application with a straightforward API call.

Enterprise developers often develop such systems themselves, using open source Hadoop or other resources. But Hadoop 1.0 and knowledge warehouses are likely to need time to upload data, analyze it in batch mode, and report at the results. Real-time data feeds haven’t been a fit, although Hadoop 2.0 may change that.

[Like to learn more about Hadoop as a streaming system? See Hadoop 2.0 Goes GA: New Workloads Await. ]

Kinesis can absorb data feeds, perform analysis on them, after which route them to Amazon’s Redshift data warehouse service, DynamoDB database system, or S3 object storage. It could use load balancing and elastic scaling to create clusters to host the info streams fed into it. It may also work with Amazon CloudWatch to offer throughput, latency, and utilization statistics back to the management console.

Khawaja Shams, a scientist on the NASA Jet Propulsion Laboratory, took the stage at Re:Invent Nov. 14 to assert he had tested Kinesis by plugging in a Twitter stream of information and asking Kinesis to decide the utilization of the word “Mars.” Shams hoped to measure the recognition of space exploration after India launched a mission to Mars. But he learned that the “Mars” that appeared most often in Tweets was Bruno Mars, the singer, not the planet. Following up, he was in a position to learn that the most important concentration of the singer’s fans is at the West Coast. It wasn’t the guidelines he originally sought, but he had discovered an influence of Kinesis and located methods to query it.

Amazon hopes Kinesis turns into a method for developers to feature real-time analytics to their applications, letting Kinesis and EC2 scale the system as needed. With this type of service , a developer could collect and analyze very quite a lot of data while not having to grasp much more than an API call. “It does the heavy lifting so that you do not have to,” said Shams.

Charles Babcock is an editor-at-large for InformationWeek, having joined the publication in 2003. He’s the previous editor-in-chief of Digital News, former software editor of Computerworld and previous technology editor of Interactive Week.

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