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IT Operations Analytics is On the Rise and Redefining IT Operations


IT Operations Analytics is On the Rise and Redefining IT Operations


The pace of change in today's IT world is truly astonishing. IT Operations is now overwhelmed — by the volume, velocity and variety of change and configuration data — lacking insight or actionable information, and making change and configuration problems a chronic pain.

Driven by modern business requirements, numerous organizations have started to re-evaluate their current processes and tools and their ability to support the evolution of IT environments, forcing many traditional approaches in IT to be reconsidered. As depicted in the Forrester report, Turn Big Data Inward With IT Analytics, "The tools present us with the raw data, and lots of it, but sufficient insight into the actual meaning buried in all that data is still remarkably scarce. For this very reason, IT analytics tools hold the promise of helping IT organizations better manage the technology that runs their business. Think of it as turning the concept of big data inward to make better decisions about the business technology services and the underlying infrastructure and applications."

Better equipped to manage these big data challenges, IT Operations Analytics solutions are emerging to redefine how IT operations maintains performance and availability.As reported in Gartner's new Hype Cycle report, IT Operations Analytics will accelerate to mainstream by 2018, saying "…cost optimization continues to be a primary concern for many IT leaders with an increasing spotlight on IT financial management. With a limited budget, access to IT operations analytics can facilitate making decisions quickly in a dynamic environment, thereby enabling more effective planning."

So as we see IT Operations Analytics gain both industry interest and the attention of experts, this is really nudging IT management technology towards a new S-curve growth cycle.

Only Marginal Returns are seen from Traditional IT Management Tools

Change is a fact of life in IT Operations.

Change takes place at every level of the application and infrastructure stack, impacting nearly every part of the business. As IT environments have grown in size and complexity, keeping production at high availability and disaster recovery systems in complete sync across IT teams and domains (e.g., server, storage, databases and virtualization) has become a bigger challenge. Generating huge amounts of data, management of this growing rate of change is even more difficult. Will Cappelli notes that "with the adoption of agile style development methodologies, the rate at which systems change has also increased dramatically (in many enterprises by an order of magnitude). In order to keep abreast of systems change, sampling must take place more frequently. In fact, for many environments, event and performance data should be extracted almost continuously." (IT Operations Analytics Technology Requires Planning and Training).  

Creating further obstacles for gaining a clear perspective of issues that impact service management, most organizations are run in a departmental silo structure, lacking a single authority that has end-to-end environment ownership for application management.

During the last 15-20 years in IT operations, enterprises have made huge investments in IT management tools. Yet, the existing tools were not designed to deal with the big data problem. With the complexity of IT systems, the dynamics of IT operations and multiple teams working in silos IT operations needs not only to automate, but also collect data down to the finest details, ultimately analyzing all changes and consolidating information to unify the various operations silos. None of the traditional tools have actually done this, never approaching this situation as a 'big data' problem.

In a recently published report from Gartner, frustration with traditional IT management tools is evident as "the Big Four surrendered share and stunted market growth, while a new generation of ITOM (IT Operations Management) vendors grew significantly faster than the market." (Source: Market Share Analysis: IT Operations Management Software Worldwide, 2012: by Laurie F. Wurster et al).

This Gartner report states that two of the leading providers in this sector, IBM and BMC, did show modest year-on-year growth in 2012 of 0.8 percent and 0.9 percent respectively, but CA and HP declined 0.6 percent and 4.3 percent. In contrast, a group of the fastest-growing companies mustered growth rates ranging from 84.4 percent to 45.5 percent.

Approaching a New Technology S-curve

IT Operations AnalyticsThe technology S-curve model has often been used to describe the life cycle of innovation, mapping the progress of technology innovation against new performance challenges. 

With the emergence of IT Operations Analytics, a new and more innovative approach is taking on complexity and dynamics in data center operations. This 'on the rise' technology is driving a transition to a new S-curve, shifting to the right and higher than the original curve, impacting data center performance.

The Emergence of IT Operations Analytics

Many traditional elements of IT are also shifting with the emergence of IT Operations Analytics solution. IT Operations Analytics can quickly discover the root causes of IT system performance problems, assess the relative impact when multiple causes are involved, analyze service cost and anticipate performance impacting events among other under the responsibility of IT operations management. Looking at how IT Operations Analytics has already been applied,Gartner principal analysts (Will Cappelli, Colin Fletcher, and Jonah Kowall) note that "…these tools have solved, and will continue to emerge to solve, specific IT operations problems; e.g., workload automation analytics, application performance monitoring (APM), performance and capacity analytics, root cause analysis (RCA), etc."

IT Operations Analytics Is Redefining IT Operations

In the spirit of business intelligence (BI), IT Operations Analytics solutions are penetrating IT operations. Primarily used to discover complex patterns in high volumes of often "noisy" IT system availability and performance data, IT operations analytics (ITOA) technologies provide real inference capacities not found in traditional tools. Extracting insight buried in piles of complex data, IT Operations Analytics can provide visibility and help IT operations teams to proactively determine risks, impacts, or potential for outages due to granular configuration changes. 

This expectation is underscored by the outlook described in Gartner's recent Hype Cycle in IT Operations report, stating that IT Operations Analytics "…will provide CIOs and senior IT operations managers with a source of operational and business data. The importance of this source will increase dramatically over the next five years, as more and more business processes become essentially digitized and, as a consequence, will, in their execution, generate data that is directly captured, aggregated and analyzed by ITOA platforms."

Improving IT Operations Performance

As most IT operations teams put in a disproportionate amount of time in chasing various root causes of performance issues, IT operations leaders are looking for new ways to deliver more value to their business. Ovum, an industry-leading analyst firm, has stated that "gaining actionable information from the wealth of data generated through change and configuration management activities can help IT work proactively, reduce disruptions to normal service, and help more effectively manage change." 

IT Operations Analytics tools are appearing as powerful solutions for IT, to help to sift through all of the big data to find patterns and insights. The alternative is IT management continuing to struggle, and descend in a downward spiral. Now is the time to apply to IT some of the same thinking put to work for business intelligence, and bring the analysis of big data inwards for IT Operations.

Your Turn
When performance drops can you quickly know what changed?

About the Author
Sasha Gilenson
Sasha Gilenson enjoyed a long and successful career at Mercury Interactive (acquired by HP), having led the company's QA organization, participating in establishing Mercury's Software as a Service (SaaS), as well as leading a Business Unit in Europe and Asia.

Sasha played a key role in the development of Mercury's worldwide Business Technology Optimization (BTO) strategy and drove field operations of the Wireless Business Unit, all while taking on the duties as the Mercury's top "guru" in quality processes and IT practices domain. In this capacity, Sasha has advised numerous Fortune 500 companies on technology and process optimization, and in turn, acquired a comprehensive and rare knowledge of the market and industry practices.

Sasha holds an M.Sc. in Computer Science from Latvian University and MBA from London Business School.