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August - 2014 - issue > CEO Viewpoint
Why IT Big Data Needs its Own Analytics?
Sasha Gilenson
Co-founder & CEO-Evolven
Wednesday, August 6, 2014
Founded in 2007 and headquartered at Jersey City, NJ, Evolven's IT Operations Analytics provides intelligent answers to key IT operations challenges: how to accelerate incident resolution, how to avoid harmful and risky changes, and how to assess and optimize IT operations performance.

IT Operations Powers Business Big Data

Using Big Data is currently seen as a solution for everything these days. Businesses and government agencies alike are collecting large volumes of diverse data from web logs, click streams, sensors, and many other sources, looking to extract insights hidden in this poly-structured "big data", that can alert them to everything from product problems to potential market opportunities spawned by specific events.

To get an understanding of the interrelationships of this data, IT support teams provide support for the massive volumes of unstructured and semi-structured big data, extracting value from this data for the business, by applying emerging Big Data analytics solutions. IT management teams can integrate unstructured data with structured data from core business applications, analyzing the combined data set, and integrating big data discoveries into the enterprise.

IT Operations, themselves, also face their own "big data" challenges due to the volume, variety and velocity of IT information overwhelming IT operations in the data center. So by applying the Big Data analytics perspective to IT operations, there is an opportunity to not only make a strategic change in the way IT operates, but also extract tremendous value. Now is the time to apply some of the same Big Data thinking that has been put to work for business management to IT, and bring the analysis of big data inwards for IT Operations, with IT Operations Analytics (ITOA)tools.

Overwhelming IT Ops Big Data Means Big Outages

Over the last decade, headlines have remained consistent, showing how IT management chases critical operational issues. It's no longer good enough to try to react quickly to outages, tracking down root causes only gets more difficult as complexity grows and IT operations has to wrestle with both too much and incomplete information from mountains of logs, event data, configuration parameters, APM systems, Security data, and IT defined KPI's.
This past year, for example, Amazon.com, Microsoft's Outlook.com, and Google all suffered significant outages that not only upset users, but also made headlines everywhere. In August 2013, a short Google outage sent web traffic plummeting by as much as 40 percent, where all its services from Google Search to Gmail to YouTube stopped working across the world.

Analyzing IT Data makes IT Operations More Effective

IT Operations Analytics tools have the ability to collect and manage every bit of IT data (performance metrics, monitoring data, changes, events, topology, logs and machine data) to provide complete insight into the IT environment, allowing for easy correlation and contextual analysis of harmful anomalies. Analyzing the millions or billions of daily changes, performance alerts, machine events in log files, and other structured and unstructured data from a wide variety of sources, IT operations can deal with the volume, velocity, and variety of IT big data and gain insight for early detection of potential problems.

How IT Operations Analytics Empowers IT

Analyzing these massive amounts of data that IT collects across the increasingly dynamic environments can be a daunting task.

In a fast-changing world, it is simply not acceptable anymore to wait until customers complain that something is wrong. Problems need to be solved before they occur. With IT Operations Analytics, this is a lot easier to achieve as the latest tools zero IT operations automatically on a subset of relevant high-risk events in business systems and IT environments hosting them. For example, there are IT Operations Analytics technologies that automatically highlight changes applied to various layers of IT environments that can produce negative impact on performance, availability or security of the critical business systems. These modern analytics tools provide actionable insights in easily interpretable context allowing IT Operations to simply spot potential problems and quickly avoid them before they can cause any negative impact. ITOA tools combine domain expertise with mathematical algorithms, allowing IT operations to recognize and evaluate patterns and topology in multi-dimensional data at a glance.

ITOA tools detect emerging problems faster, allowing IT operations pros to:

• Learn normal operational behavior across the IT environments, including how metrics behave together.
• Identify metric relationship changes that could signal a problem long before traditional thresholds change
• Identify problems before one knows where to look for them
• Detect service impacts that are not identifiable by fixed thresholds alone.
• Address root cause analysis by indicating the most likely suspects.
• Reduce expensive and time-consuming false alerts.

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