open
  1 (866) 866-2320 Resources Events Blog

IT Operations Analytics Changes the Rules

Blog

IT Operations Analytics Changes the Rules


 

Advances in analytic technologies and business intelligence now allow organizations to go big, go fast, go deep, with their business data. Current trends center on tackling business challenges with big data analytics, taking advantage of opportunities for new business insights.

For example, technologies for managing and analyzing customers' behavior are in place in many organizations that were drowning in disperse and diverse data sets and struggling to make sense of it. The cost and performance improvements in advanced analytics mean companies can ask more complicated questions than ever before and deliver more useful information to help run their businesses.

Analytics Getting More Attention

While emerging solutions are becoming prevalent quickly, the advent of these systems is creating an environment in which many traditional elements of IT are also shifting. IT operations analytics comes to 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 IT operations management areas. IT operations analytics is a discipline that combines complex-event processing, statistical pattern discovery, behavior learning engines, unstructured text file search, topology mapping and analysis, and multidimensional database analysis.

For example, Milind Govekar, managing vice president at Gartner, explained that analytics are beginning to impact the cloud market. "We also expect more next-generation analytics to come to the forefront to address an increasingly hybrid cloud environment. 

The recently published Hype Report, from Gartner on IT Operations Management, shows the momentum that IT Operations Analytics is gathering in this space.

IT Operations Analytics

Interest in IT operations Analytics

With feedback from our customers and industry input, we are seeing more demand for IT to apply an analytics-driven approach to better manage IT operations in complex and dynamic IT environments, significantly improving how operational information will be handled.

IT ops Today

The pace of change in today's IT world is truly astonishing. With cost pressures and complexity frustrating many IT ops teams, IT is expected to help the business side weave together multiple kinds of technology to solve time-pressured business challenges, pushing the IT landscape in complexity, having to support a wider range of technologies and platforms, and accelerated release schedules.

For IT Operations, change is a fact of life. Change takes place at every level of the application and infrastructure stack and impacts nearly every part of the business. When virtual environments co-exist with physical and cloud entities, it is much harder to troubleshoot performance issues and IT admins may spend hours trying to isolate a problem. Just dynamic workload management mechanism makes this effort incredibly harder. Even with the management capabilities that virtualization and cloud vendors offer, they still lack in monitoring and analytics areas.

The Traditional Approach to IT operations

The approach to IT operations has traditionally been static and manual process driven. IT's processes are largely based on pre-defined and pretty rigid workflows. Change Management has been defined in the ITIL set of best practices for the area of IT Service Management as a set of step-like processes. Metrics are also applied so that information on issues such as failed or successful changes are compared to. 

With the operations team striving for full control over all IT processes and changes to environments, IT teams have in many cases been content with slow processes, seeking to ensure quality. In today's larger organizations, responsibility is typically spread out over multiple departments based on functional IT silos, or, given to one silo. It is not just difficult for one silo to possesss the breadth of expertise required to prevent and solve problems given the complexity of the applications and infrastructure they are expected to support, but also it's pace of change, required flexibility of business processes, outsourcing and many other factors. 

Due to the inherent, rigid structure of traditional IT workflows, activities that take place outside of this process are just not taken into account. The pressure from ever- changing business demands, can even cause an IT ops professional to skip steps in the defined workflow, like skipping a critical testing stage, to meet deadlines. 

So when a system outage occurs or there is a drop in performance, this mandates that a series of activities be initiated, including root-cause analysis of failures. While IT administrators try to stick to established, and well-planned processes to try to pinpoint the problem, this approach reduces an organization's ability to be lean and agile, relying on older automation technologies (or manual processes) with little to no management of the changes.

Analyzing Business Data

The business side of the organization found itself confronting a similar state as we described IT ops, with increased pressure to make use of growing piles of unstructured data. Many business organizations were drowning in data and struggling to make sense of it. The big challenge in big data is going from lots of raw data and turning it into a form that business can make sense of it. So companies have looked into how to add value through aggregating multiple data sets. How much data one has is less critical than how efficiently it can be analyzed. The information gained from varied perspectives is beneficial for Business Intelligence, tapping directly into their customer sentiment. Current business trends center on tackling big data challenges with analytics and to take advantage of opportunities for new business insights, with technologies for managing and analyzing large, diverse data sets in place. Advanced analytics now means business managers can ask more complicated questions than ever before and reach more useful information to help run their businesses. 

Furthermore, analytics can now be run in seconds that once would have taken overnight. The process of carrying out analytics on large data sets, often involving running a query, looking for patterns, and making adjustments before running the next query. 

The systems of elements that causally interact in a business domain tend to be complex infrastructure, but are extremely difficult to discover and model. Business Intelligence solution for managing and analyzing large, diverse data sets, provide valuable insights into projects and portfolios.

IT operations Faces Lots of Information

So, look business applied analytics to their data challenge, why are IT operations, who enable the technology for business and BI analytics, behind? The IT operations domain continues to confront enormous volumes of data at far greater rates than ever imaginable. The systems in the IT domain for enabling this business services also tend to be extremely complex and multilayered, appealing to automated discovery and modeling.

Most organizations do not have a single department that owns end-to-end environment management. The components of a single application may run on different physical and virtual systems that communicate across networks, which in turn may include internal and external segments with limited visibility.

A large array of legacy IT event and performance monitoring technology currently exists. This includes:

  • Business Transactions Monitoring (BTM)
  • Application Performance Management (APM)
  • System Management (SM)
  • Change & Configuration Management (CCM)
  • Incident Management (IM)
There are tools for BTM, APM, SM, Service Desk each handling their particular scope of metrics and data with this complexity each in their own process silo, not yet achieving broad and deep visibility into the IT environments

Using This Information Is Just Visibility

Even with these technologies, for managers surveying today's IT data center, the view is overwhelming. Across a landscape filled with cloud offerings, virtual servers, employee-owned devices, inherited and acquired assets, and disparate systems, IT professionals struggle to apply these technologies for clear answers into an increasingly difficult and distorted field of applications and infrastructure.

Need Actionable Information For IT ops

Today's configuration management and change management tools, including CMDB and others, are too rigid and too effort intensive to handle the complexity and dynamics of the modern data center. They lack the intelligent analytics and correlation with operational data coming from other IT processes required to translate abundant detailed configuration data and frequent changes into critical decision-support information.

A new generation of IT operation analytics technologies is emerging, providing IT the insight to address problems early on. In doing so, IT professionals are preventing the fire drills that result in MTTR (mean time to repair) focus and metrics. In turn, IT should have 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. 

Vendors , Analysts Talking about Analytics

Today's approach to IT operations is changing, with more of a view to cross processes, not just in silos. Now that analytics in the spirit of BI are penetrating IT operations, analysts such as Gartner and others are enthusiastic about the technology. Vendors are also approaching company decision makers to consider how to take advantage of the information they are collecting and apply advanced analytics in context of IT operations. 

Applying BI Tools?

In considering new tools for IT, BI tools just can't be applied as is to IT ops. While principal technology platform can be similar relevant domain expertise and heuristics are required to provide accurate answers to the key operational questions. The algorithms and methods processing operational data need to consider relevant context in order to prioritize and categorize the output. Multiple data sources need to be correlated based on the understanding of the data dependencies. Variety of teams participating in IT processes and diversity of their skills require analytics to be able to encapsulate complex technical data in few key highlights while allowing complex drill down for more technical staff. 

operation Intel for IT ops

IT systems can capture and store volumes of valuable information related to their operations that can be applied for improving operational efficiency, lowering IT management costs, and improving quality. Some of this information is automatically captured by the operating system, business systems or database engines, while other information is captured as needed through performance monitoring and profiling tools. The collective operations data needs to be gathered and analyzed, in order to get a more comprehensive view of the entire IT environment stability and productivity. This perspective will aid in root cause analysis of problems impacting business activities. In addition, by tying this data to the context of an environment change, you should be able to identify operational activities that could lead to performance, availability and security issues. This type of insight into IT operations allows you to take steps to pre-empt negative impact of operational actions and prevent issues from turning into larger problems. 

A Unique Approach to IT operations Analytics

Today IT operations faces new levels of challenges that can no longer be handled with existing approaches. This means applying some more serious brain power to help deal with the complexity and dynamics of today's IT environments. Evolven's IT operations Analytics solution delivers the intelligence that IT operation organizations are vying for, allowing them to turn piles of IT operations' data into actionable information.

Evolven provides a versatile technology for monitoring and analyzing applications and infrastructure configuration across the entire environment. Evolven identifies the changes, differences, inconsistencies and misconfigurations that can threaten environment stability or already caused an issue. Evolven covers the vital technology components and applications that make up your business service environment. You get a consolidated view of your entire environment stack, so that various IT teams (devops, operations, infrastructure etc.) can monitor and control configuration and associated changes over the various layers and siloes of the environment stack.

Recognized by leading industry analysts for "transforming change and configuration management" and as the "Industry's most adaptive change management analytics," Evolven is pioneering the promising new field of IT operation Analytics. Evolven's IT operation Analytics solution applies breakthrough automated analytics to enable companies to dramatically increase the performance and availability of their IT environments, reduce the risk of production outages, lower operating costs, and cut environment incident investigation time and effort.

Your Turn
How are you overcoming chronic change and configuration challenges?

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.