Issue link: http://cp.revolio.com/i/207723
I t's no secret that the IT landscape has become increasingly complex, modular, distributed and dynamic. To be competitive in the global marketplace, 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 interdependent 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 accelerated 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 Operations, 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 adaptability 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 www.datacenterjournal.com 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 system 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 practical 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 applications (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 elements 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 business. 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 Operations 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 information and from a variety of sources: logs, application performance availability data, change and configuration data, and transaction 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 challenges truly are "Big Data" problems. This Big Data problem is glaringly evident as applications are moved through multiple complex environments, advancing 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 information, IT Operations Analytics automatically collects comprehensive amounts of data and analyzes this information for critical insights. THE DATA CENTER JOURNAL | 23