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Microservices Expo: Article

Preventive IT Analytics

An ounce of prevention is worth $2 billion

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.

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.

Why now?
There are three key reasons why preventive analytics are emerging now.

Not long ago, car enthusiasts would spend time under the hood juicing their "hot rods" performance. Now, with the incorporation of complex chipsets throughout the vehicle operations, those days of tinkering are gone. The same is true with most of today's enterprise grade application stacks - IT "under the hood" is just too complex for anyone to understand and manage without adequate tools.

Second, the IT professional's job is nearly impossible with the proliferation of hot IT trends including enterprise social media, mobility, "Big Data," and end-user demand for SaaS or cloud application support. IT organizations are struggling with these trends and losing the race to get in front of applying technology for business benefit versus maintaining technology operations. Preventive analytics helps shift the time required to maintain operations by preventing incidents, war room exercises, RCAs (root cause analyses), and the like.

Finally, advanced mathematics, machine-learning technologies, higher compute power and low cost are all enabling the processing of these massive volumes of data and computational algorithms in speeds that were not possible before.

What you should do about it.
Get going...

For the IT operations and application operations organizations around the globe who are mature enough or who have enough to gain from preventing application performance affecting incidents, they are seeking out those APM or related technology vendors developing this preventive analytics practice and technology. They want to test it out in real-world settings and are regularly surprised - positively - with the results.

If you are operating in a rapidly changing and early stage organization, you may want to keep an eye on these technologies and know that, when you are ready, they are available to help you mature your organization and operations.

Note, the key is not trying to measure or monitor everything. Successful organizations are focusing on a particular pain or value point and are taking the technology for a test run.

In some cases, the deployment may take some time and there may be a "discovery" or "due diligence" process as you identify the best application and the right metrics to feed into the analytics engine, but there is an alluring and worthwhile return on investment in time and technology.

It does not have to be a world of science fiction to know that an ounce of prevention equals a pound of cure - and, in this case, potentially millions or billions of dollars as the APM industry figures out how to shift from MTTR focused activities to MTTP - more time to PREVENT incidents in the first place.

More Stories By Ray Solnik

Ray Solnik is President of Appnomic Systems. As president of Appnomic Systems, he has P & L responsibility with a focus on business growth in North America. He brings to Appnomic twenty years of experience in cloud computing, managed network services, and data communications.

Prior to Appnomic, Ray was president and COO of OpSource, an early SaaS/IaaS provider, which was acquired and is now the core Cloud offering of Dimension Data - a $4 billion systems integrator. Ray has helped multiple next generation companies develop and drive strategies resulting in successful fundraising from top venture capital investors, including Gengo, PowerCloud Systems, and CrowdFlower.

Earlier in his career, Ray was chief development officer of New Edge Networks (acquired by EarthLink), and president of AT&T’s consumer Internet services business, AT&T WorldNet. He has a bachelor's degree in economics from the University of Michigan and an MBA from Stanford Graduate School of Business. He lives in Silicon Valley.

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