New Data Center

‘BIG DATA’ Realities Demand

New IT Analytics Approach

by sAsHA gILenson

It ops

22 | THE DATA CENTER JOURNAL www.datacenterjournal.com

THE DATA CENTER JOURNAL | 23 www.datacenterjournal.com

It’s no secret that the IT landscape has become increasingly complex, modular, distributed and dynamic. To be competitive in the global market-place, organizations have been driven

to rapidly innovate while not sacrificing cost efficiency or speed. Now more and more sophisticated technologies are in the data center, creating many moving inter-dependent pieces, with many individual configuration parameters.

For IT Operations, this presents new management challenges. Without visibility into the huge amount of configuration and content, the slightest changes can have a major impact on operations, and leave IT Operations in the dark as to how the system reacts in response to environmental changes.

Business requirements are driving high-paced change activity with acceler-ated application deployment and software deployment schedules. The recent Gartner Hype Cycle for IT Operations Management report emphasized this, saying how “the business has control over more IT decisions than ever before, and is influencing CEOs to consider alternatives that are faster, more agile and responsive so that the business can accelerate its pace, while facing cost pressures in an economically uncertain environment.”

Charged with delivering and maintaining that quality, IT Operations management now has to stay on top of an ever-growing collection of information and environment content. Yet, for IT Opera-tions, managing change on every level of the application and infrastructure stack is complicated by:

More Data: Amount of data to manage has increased by an order of magnitude.

Complexity: The increased demand for system adaptabil-ity requiring complex internal structure.

Dynamics: Systems are now composed of a large number of moving parts, requiring global visibility for maintaining performance and availability.

IT teams face many issues that they have to stay on top of in order to maintain

top performance and availability. Over the last 15 years, the headlines have remained consistent, showing the chronic nature of change and configuration management challenges and how these lead to critical operational issues.

Without systems to manage and organize this growth and lacking essential controls, IT can end up drowning in its own data.

The combination of growing data volume, variety, velocity and increasing sys-tem complexity is forcing many traditional approaches in IT to change, ushering in IT Operations Analytics solutions to take on this challenge.

It oPerAtIons overwHeLMed

The growing complexity of application environments and IT architecture makes it harder than ever to collect and analyze reams of technical (i.e. application) data to generate operational improvements and support business momentum.

IT Operations needs to address practi-cal day-to-day operations questions, like:

• When an incident occurs, can you quickly know “what changed”?

• Can you automatically validate that your release deployed accurately?

• Can you quickly identify what is an incident’s root-cause?

• Can you automatically analyze the consistency of your environments?

These are the types of questions that application owners and IT Operations managers don’t have time to answer because they’re too busy trying to maintain the performance and availability of their ap-plications (a full time job in its own right). This can be seen in the recent report, Turn Big Data Inward with IT Analytics, where Forrester declared, “If you can’t manage today’s complexity, you stand no chance of managing tomorrow’s. With each passing day, the problem of complexity gets worse. More complex systems present more ele-ments to manage and more data, so growing complexity exacerbates an already difficult problem.”

While available IT management tools collect and present IT with enormous amounts of raw data, they really lack the analytics capabilities and the granularity to make sense of the high volumes of “noisy”

IT system availability and performance data. This has left IT Operations without the tools or technology to analyze overwhelming amounts of raw data, and unable to extract actual meaning buried in all that data.

IT Operations leaders are looking for new ways to deliver more value to the busi-ness. Tools for effective decision making can improve the infrastructure and operations (I&O) team’s ability to allocate resources to the right types of activities.

A bIg dAtA ProbLeM

To make critical decisions, IT Op-erations teams need to reach information that is buried in piles of noisy, distracting data. Monitoring tools, like APM or BSM solutions, can gather a lot of this informa-tion and from a variety of sources: logs, application performance availability data, change and configuration data, and transac-tion data. Yet, it’s a “needle in the haystack” problem: you know it’s there but you just can’t find it. For IT Operations, these chal-lenges truly are “Big Data” problems.

This Big Data problem is glaringly evident as applications are moved through multiple complex environments, advanc-ing through the application lifecycle. Since development focuses on quickly delivering application changes through parallel and agile methodologies, IT Operations needs to ensure that the applications work as a whole, leaving gaps to occur throughout this flow.

This means applying new tools to help deal with the complexity and dynamics of today’s IT environments. By applying some of the same thinking as used in business intelligence, IT can bring the analysis of big data inwards for IT Operations, to sift through all of the big data to find patterns.

It oPerAtIons AnALytIcs MAKe tHe bIg dAtA cHALLenge MAnAgeAbLe

IT Operations Analytics is better equipped to manage this kind of big data challenge. Providing IT Operations teams the ability to work in closer collaboration and greater visibility into critical informa-tion, IT Operations Analytics automatically collects comprehensive amounts of data and analyzes this information for critical insights.

24 | THE DATA CENTER JOURNAL www.datacenterjournal.com

The recently released Gartner Hype Cycle report on IT Operations Manage-ment report explained why IT Opera-tions Analytics expected to accelerate to mainstream, saying that “With a limited budget, access to IT operations analytics can facilitate making decisions quickly in a dynamic environment, thereby enabling more effective planning and better use of virtualization by leveraging cloud manage-ment platforms and DevOps.”

IT Operations Analytics can be a powerful addition to IT management tools, as Gartner Research VP, Will Cappelli observed in the recent report, Will IT Op-erations Analytics Platforms Replace APM Suites?, “IT operations teams should use IT Operations Analytics (ITOA) platforms to supplement and not replace investments in end-user experience monitoring, applica-tion topology discovery and modeling, user-defined transaction profiling, and deep-dive component monitoring.”

When IT Operations Analytics is ap-plied to change and configuration manage-ment, using changes as a context base for analysis, IT Operations can turn piles of IT change and configuration data into action-able insights.

extrAct MeAnIngFuL InForMAtIon wItH It oPerAtIons AnALytIcs

Using mathematical algorithms and other innovations, IT Operations Analyt-ics tools carry out calculations that churn through immense amounts of data, extract-ing meaningful information from a sea of raw data.

The various emerging IT Opera-tions Analytics solutions take a different perspective on this abundant information. Using monitoring agents to track changes to configurations, system and applica-tion components, IT Operations Analyt-ics can parse log files to understand what changes were made and even who made them, enabling IT Operations staff to more quickly assess and pinpoint a problem. IT Operations staff can also use trending data to assess the risks of potential changes by comparing a change to historical analysis. IT Operations Analytics feeds data into its algorithms for producing business-relevant reporting and alerts.

IT Analytics tools can help IT Opera-tions ensure control with:

• Makingdataanalysisactionableby applying statistical pattern discovery and recognition (SPDR).

Assessing statistical clusters of application-stack usage and operations patterns to identify exceptions to or devia-tions from complex enterprise data center operations before they result in end-user experience issues. Textual pattern analyt-ics sift through streams of textual data, such as logs, to find patterns that can be used to identify conditions and behaviors overlooked by more traditional numerical collection technologies.

• Configurationanalyticsdy-namically captures all change configura-tion information across IT environments, analyzing configurations to detect what has changed from when the system was working fine, verifying change consistency between environments, spotting discrep-ancies from desired configuration (drift), and identifying which of the changes can impact the environment or alternatively are a root cause of an investigated issue.

sIMPLIFyIng It oPerAtIons To keep IT Operations running

efficiently in support of the business, IT Operations Analytics is being applied to key data center use cases:

Incident management. MTTR is woefully high in most organiza-tions. IT Operations Analytics can dramati-cally reduce the time required to respond to incidents and even feed efforts to eliminate incidents from occurring in the first place. For instance, when an incident occurs to-day, IT Operations starts a race against time to sort through the sea of dispersed data in an attempt to figure out “what changed” from the last time the system was working fine, and what caused the incident. IT Op-erations Analytics transforms this process by applying pattern and statistics based algorithms to automatically analyze all changes that occurred since the system was working fine, identifying the incident root-cause before it can impact performance.

Problem management. Very similar analytics technologies can help those involved in problem management to

arrive at root cause, or a probable cause, identification.

Change management. IT Operations Analytics technologies can perform sanity checks to determine the probability of success before any change is executed.

Configuration management. IT Operations Analytics can detect discrep-ancies from desired configuration (drift) and reduce risk to environment stability.

resHAPIng cHAnge And conFIgurAtIon MAnAgeMent wItH It oPerAtIons AnALytIcs

Today IT Operation Analytics are considered mainly within the context of APM and machine event management. One of the other critical operations areas that could be reshaped with IT Operations Analytics is change and configuration man-agement. With widening adoption of Agile development processes, IT Operations faces hundreds of changes going into produc-tion on a daily basis for environments that can include thousands of different con-figuration parameters. When any of these parameters are mis-configured or omitted, operations can be impacted, quickly turn-ing into a harmful incident possibly leading to an outage with lost opportunities that impact reputation, customers, financial per-formance, legal liabilities, and the overall organization.

Enterprises should know that de-pending on the quality of their IT service revenue and profitability, in response to the painful and chronic change and configura-tion challenges that undermine today’s IT Operations, enterprises can implement IT Operations Analytics to shorten incident response times, make releases seamless, and significantly reduce the number of incidents and downtime. n

about the author: Sasha Gilenson is CEO for Evolven Software, a provider of IT Operations Analytics. Prior to Evolven, Sasha spent 13 years at Mercury Interactive. He studied at the London Business School and has more than 15 years of experience in IT Operations. http://www.evolven.com

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