Too Much IT Operations Data? Try Analyzing It with Cognitive Insights
It is time for a new approach: analytics and cognitive computing.
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Businesses
today are trying to solve a giant and growing jigsaw puzzle created by
IT operations data, the data generated by IT systems, applications and
networks. Everything from system successes to system failures, and all
points in between, are logged and saved as IT operations data.As cloud, mobile and analytics applications continue to become competitive necessities for every business -- not just technology companies -- it’s becoming more and more important to keep the supporting backbone of these applications healthy: the IT network. To do so, businesses must analyze massive amounts of IT operations data to better understand how their data centers are functioning, what problems are emerging, and how to improve IT efficiency. Solving a problem in this environment is worse than trying to solve a jigsaw puzzle. It’s like a jigsaw puzzle that has thousands and thousands of extra pieces, many of which aren’t relevant to the picture you’re building.
IT operations has now become a Big Data challenge. The transformation to mobile and cloud has significantly increased the complexity and density of IT operations data, and traditional IT teams and practices can’t keep up. Every day there are huge amounts of structured and unstructured operational information generated by IT systems: log files, system events, performance metrics and more.
Consider that a typical 5,000-server business generates more than a terabyte of IT operations data daily. As more business data is created, it must be stored, networked and exploited. This generates more operations data, driving a growth rate of 15 to 20 percent annually.
Most operations data is typically archived, forgotten and discarded, but businesses now know there is value in saving, learning from and using this data to improve IT efficiency. The data can be used to identify patterns and minute deviations, respond to IT system problems before downtime happens, predict issues before service is affected, and optimize the way IT and application infrastructure is managed. However, IT operations data has become too vast for humans to manage manually.
IT operations data management tactics need to be more efficient to solve the puzzle. One typical but inefficient approach, for example, is to bring together network, storage, application and infrastructure specialists to argue about where the problem lies. That usually results in an IT administrator sifting through massive amounts of data manually in an attempt to accurately identify the root cause of a problem.
It is time for a new approach: analytics and cognitive computing. For years analytics have been used to manage IT capacity, planning and performance management, but today's more advanced analytics technology, combined with cognitive computing, is bringing new and expanded capabilities, providing accurate and deep insights on IT operations data.
Using these new tools, IT administrators can quickly isolate relevant data, separating important information from irrelevant information, and learning and understanding associations between different data points. Analytics and cognitive software can learn and identify trends and patterns to predict issues before they occur.
The combination of analytics and cognitive computing are the ideal solution for solving the IT operations data puzzle. These tools can simplify IT problem detection, predicting issues, and quickly isolating their root causes. With analytics and cognitive computing, IT administrators can now tackle the Big Data challenge posed by IT operations head on, unlocking the true potential of such valuable data.
If you want to learn more about cognitive computing, download a free chapter of Smart Machines, by IBM Research Director John E. Kelly III.
A version of this article appeared on Wired Innovations Insights on Dec. 4, 2013.
Edith Stern is an IBM Distinguished Engineer and Master Inventor at IBM, with more than 100 patents to her name.
The interactive graphic below explains what IT operations data is in more detail and how businesses can use it:
http://www.rossmanart.com/ITO/ITO1.html#
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