Big Data Startup Unveils End-to-End IT Management

Nov. 17, 2015
OpsDataStore’s new product builds relationships between systems, applications and machines across the enterprise to provide a clear view of interactions and anomalies in the work environment.

Atlanta-based startup OpsDataStore, which launched its business just last month with $3 million in Series A funding, will announce the availability of its first product today.

OpsDataStore 1.0 is a Big Data back end that provides real-time visibility and transparency across operations and application performance so that information technology (IT) professionals can proactively prevent performance and availability issues, thereby avoiding downtime and its associated revenue loss.

The company’s new technology can blend and manage different data sources, providing a unified view of all IT systems, applications and machine relationships across the enterprise—and the factory floor, company officials said.

The technology solves the problem of disjointed legacy management frameworks that have been set up as closed software suites focused on only a slice of enterprise data, be it storage, networking, servers or operating systems. IT organizations, however, need an end-to-end monitoring and troubleshooting system, which is what OpsDataStore delivers. The key to the company’s ability to deliver a holistic management system is its partner ecosystem, also announced today.

OpsDataStore has aligned itself with management tool companies AppDynamics, Dynatrace and ExtraHop, as well as visual analytics vendors Qlik and Tableau. Platform partners include Microsoft and VMware. In addition, a data collector software development kit (SDK) allows anyone to write a plug-in to integrate a new source of data.

“We are the first vendor to accept data from all vendors and end up with relationships of data, not just dumb data,” said OpsDataStore CEO Bernd Harzog. “And we have a business model that allows us to partner with vendors instead of compete.”

The product is so new that the company has no customers yet, however, Harzog sees a huge potential for this technology in manufacturing organizations. “The purpose is to use the relationships and the analytics built into the product to tell you where things are going wrong,” he said.

And, while there is a heavy IT focus, having insight into these systems is an important part of keeping an integrated plant up and running because the technology shows anomalies in things that are deterministically related to each other.

“If you see things going wrong with real time instrumentation on the factory floor, the first thing you want to do is figure out what could be causing it.,” Harzog said. “And the first step is figuring out what that machine is connected to, or what it’s dependent upon, because the machine is not an island.”

OpsDataStore is built on Apache Cassandra, an open source distributed database system designed for storing and managing large amounts of information across commodity servers. It is the same backend that LinkedIn servers use to process millions of transactions to make recommendations of people you may know, for example. This makes it a powerful data consumption and analytics tool.

“We are an IT technology designed to keep up with the pace of operations technology (OT),” Harzog said.

Key features include:

  • Open data collection architecture to consume data from any platform and any management software product.
  • A dynamic object model which relates items to each other at ingest time and maintains a continuously updated topology map of the entire environment over time.
  • Real-time scalable big data back end built on open source, low latency and big data technologies.
  • Open query architecture supporting both REST API and ODBC as an API for data access.
  • Support for leading business intelligence tools with dashboards implemented in QlikView and Tableau.

Pricing for the on-premise software is $100 per year for each instance of Windows or Linux from which data is collected. So, the cost to a manufacturing environment with 1,000 machines supported by 1,000 servers in IT would be $100,000 per year. There is no charge for the machines or end user devices generating the data.

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