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Preventive IT Analytics: An Ounce of Prevention is Worth $2 Billion

Category: Computers & Internet: Information Technology

Managing software application performance is complex and increasingly challenging. Surprisingly, even today, massive IT resources remain chained to ensuring applications and infrastructures are up and running smoothly, rather than proactively leveraging strategic technologies to solve business problems or achieve competitive advantage. That world is changing. A new generation of preventive analytic technologies is emerging in the APM (Application Performance Management) industry, unlocking untapped value in this $2+ billion market that is growing $300 million per year. These technologies are only now achievable via revolutionary machine learning technologies, advanced quantitative analytics, and the natural evolution of BI … as BI-like analytics are bleeding into the APM world. IT can now actually predict and anticipate problems. In doing so, IT professionals are preventing the fire drills that result in MTTR (mean time to repair) focus and metrics. In turn, IT has more time to prevent performance incidents from occurring at all, pursue these preventive “fixes” in an orderly and efficient manner, and, ultimately, devote more time to optimizing the use of technology for business gain. It may sound like a science fiction movie, but today’s application performance analytics technology is truly able to predict the future, identify incidents before the occur, and allow IT to solve them in a pre-emptive manner. The chart below from a recent TRAC Research study on TC-APM, Transaction Centric Application Performance Management demonstrates the traditional state of APM in a MTTR (mean time to repair) based world. Chart 1: Average Mean Time to Repair (in minutes) for Issues with Multi-Tier Applications per Incident. TRAC Research Source: TRAC Research, June 2012. As the APM market has evolved from Infrastructure-Centric Application Performance Management (ICAPM) to Transaction-Centric APM (TC-APM), there have been massive gains in accelerating MTTR. In fact, MTTR is more than 70% faster when IT operations can drive analytics and insights from the application transaction layer down versus trying to correlate insights from monitoring infrastructure components and in an upward fashion through the infrastructure. Follow the trend line of the chart above and you can see how the next major step is preventing incidents in the first place – Mean Time to Prevent (MTTP) will become the new, more important metric, over taking MTTR. For Example… An Internet ecommerce customer using preventative or predictive APM analytic technologies such as those provided by Appnomic Systems, Netuitive or Prelert can readily assess a potential issue in real-time to prevent outages or end user affecting response times. The graphic below is a real-world example from an Appnomic Systems’ customer. Chart 2: Average Mean Time to Prevent (in hours) for an Internet ecommerce application pre-outage early warning alert. This chart illustrates how an Internet ecommerce company identified the root cause of an ultimate outage that occurred six hours after an alert from the company’s APM solution with preventive analytics. While, in this case, an early alert did not result in preventing the ultimate outage because this organization was in early stage deployment of preventive analytics and still learning how to use the technology, the IT operations professionals using the technology had an unprecedented, visceral experience of how preventive analytics can work for them. While it may have seemed unbelievable at the time, this company now knows preventive analytics are not science fiction. CIO, CTO & Developer Resources BI Meets APM The chart below helps put this industry trend in perspective. The graphic, from The Data Warehousing Institute (TDWI), frames up how the BI (Business Information) industry has been evolving. As BI-types of analytics are penetrating IT operations and APM tools, analysts including Gartner, EMA, TRAC Research, and others are actively working to help technology buyers consider how to take advantage of this technology confluence and take advantage of the benefits of applying advanced analytics in the APM realm. Chart 3: TDWI Model of the BI Industry with an overlay of how Preventive Analytics are an emerging new frontier. Source: Predictive Analytics: Extending the Value of Your Data Warehousing Investment by Wayne Eckerson, TDWI Best Practices Report, Q1 2007. Reprinted with permission. For more information about TDWI Research, visit tdwi.org. A rich, natural evolution of analytics technology is underway, laying the foundation for the newest application of analytics to the world of IT. On the fundamental TWDI framework, an overlay of the emerging, next phase of BI being applied to application performance management has been added in green where preventive analytics are highlighted and of greatest impact.
Date Added: October 31, 2012 09:54:33 AM
Author: Sujatha
 
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