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Sumo Logic Extends Machine Data Analytics Reach

Machine data is now not only more distributed than ever, it’s also being used to influence decisions that go well beyond what’s occurring inside the IT organizations. To make it easier to employ machine data across the enterprise, Sumo Logic this week announced it has extended the reach of its namesake cloud analytics services into […]

Written By
MV
Mike Vizard
Jun 7, 2017

Machine data is now not only more distributed than ever, it’s also being used to influence decisions that go well beyond what’s occurring inside the IT organizations. To make it easier to employ machine data across the enterprise, Sumo Logic this week announced it has extended the reach of its namesake cloud analytics services into the realm of public clouds while also making available dashboards aimed at non-technical users. New platforms now supported include Amazon Web Services (AWS), Google Cloud Platform (GCP), Heroku, Microsoft Azure and the Pivotal Cloud Foundry platform-as-a-service (PaaS) environment.

In addition, Sumo Logic has altered the licensing terms under which it provides access to its cloud service to provide organizations with a Sumo Cloud Flex option under which terms can be negotiated based on the use case for the data. Currently available under a private beta program, Sumo Cloud Flex provides an alternative to paying for access to the analytics service based on the total amount of data ingested.

Kalyan Ramanathan, vice president of product marketing for Sumo Logic, says Sumo Logic is trying to make its machine data analytics more affordable in cases where the usage pattern might be, for example, more seasonal.

“We’re trying to account for use cases based on time and the value to the business,” says Ramanathan.

SumoLogic

Machine data these days can easily wind up being too much of a good thing. Because IT organizations generally pay to access machine data analytics based on the amount of data they ingest, many of them need to limit the amount of machine data they analyze. In cases where machine data is being used in a security analytics application, limiting the amount of data that can be analyzed is counterproductive. Of course, some organizations solve this issue by acquiring an enterprise licensing agreement. But alas, not every organization can afford such a machine data analytics luxury.

MV

Michael Vizard is a seasoned IT journalist, with nearly 30 years of experience writing and editing about enterprise IT issues. He is a contributor to publications including Programmableweb, IT Business Edge, CIOinsight and UBM Tech. He formerly was editorial director for Ziff-Davis Enterprise, where he launched the company’s custom content division, and has also served as editor in chief for CRN and InfoWorld. He also has held editorial positions at PC Week, Computerworld and Digital Review.

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