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Predict System Failures and Performance Issues with Analytics

There are no shortcuts when it comes to predictive analytics.



The key to establishing predictive infrastructure analytics is not to buy the most expensive tool, but rather establish sound IT monitoring processes, which provides component level insights and maximize the functionality of current tools.

Your Challenge

Companies struggle with predictive analytics due to:

  • Over-reliance on additional technology: IT leaders can’t just depend on technology redundancy to prevent downtime. N+2 redundancy across the environment does not guarantee zero downtime and zero performance hits.
  • Belief that a new monitoring tool will be the silver bullet: While a new tool will provide additional functionality, immature processes will hamper the effectiveness of the tool and dilute the value of your investment.
  • Lack of clarity regarding day-to-day business demand: Predictive analytics rely on a detailed discovery process, large volumes of samples captured, and a clear understanding of fluctuations in business demand.

Our Solution

  • Quickly recuperate value from the project by focusing on a single critical application/service and avoid project delays.
  • Document the end-to-end process flow for the critical application/service and clearly define how the application integrates with business process.
  • Establish relevant component-level metrics to define a baseline for each dependency in the overall process.
  • Continuously track and monitor the baseline operating characteristics to establish a signature of normal performance that can be used to predict deviations and aberrations. 

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Search Code: 80199
Published: March 23, 2016
Last Revised: March 23, 2016

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