Today’s IT operations face some great challenges. Modern IT infrastructures are constantly changing at an unprecedented pace, environment complexity is greater than ever, and IT still operates in silos. The volume, velocity, and variety of the data IT operations is up against deserves to be called a big data problem.
Looking to overcome this problem, a new category of IT management tools recently emerged: IT operations analytics (ITOA), as it was coined by Gartner analysts, or simply IT analytics.
More and more senior IT operations managers are starting to leverage ITOA tools as a source of operational data for making key decisions. Leading vendors and startups have made significant progress in leveraging analytics for providing better IT operational insights. These ITOA solutions are the natural first step for elevating the capabilities of the current IT management toolset.
Yet, they are still limited. ITOA tools are constrained by operating in narrow silos (application performance management, log, network, etc.), by concentrating on just the symptoms that surround issues, and by their own limited analytics capabilities.
Now is the time for the next step: to realize the benefits and promise that IT operations analytics offers. IT stakeholders responsible for stability, performance, and security of business systems need to break out of their silos and apply a blended analytics approach that combines major sources of information for comprehensive analysis.
ITOA Today: More of the Same
Today's ITOA solutions are restricted by silos, a focus on symptoms, and weak analytics.
Stuck in Silos
Current ITOA solutions perpetuate silo operations. In the typical silo analytics approach, a number of essential data feeds still go unprocessed and are not correlated together, including deployment and release automation information, service requests, environment configuration, software configuration, application data and many others. One person may see performance while another sees logs, but no one sees the whole picture.
IT operations data is much more diverse, so while these insights are important, they fall short of actually nailing down sensitive issues. Rather, mapping the data to the environment components exhibiting abnormal behavior would help improve root cause analysis.
Focused on Symptoms
ITOA solutions focus on “symptoms” that represent a manifestation of a problem but not the true root cause of a problem. The root cause can be an undesired change, yet the concept of monitoring and analyzing changes is still missing from today’s ITOA tools.
Heavily relying on symptoms alone leaves IT with some critical drawbacks. It is very difficult and time-consuming to identify the true root cause of a problem just from symptoms. Reverse engineering from the symptom takes too much investigation time to be practical.
Even more, by relying only on symptoms, ITOA tools are left waiting for abnormal behavior to appear and only then pursue potential issues. Once a symptom is observed, it could be too late—users may already be experiencing the impact of the abnormal system behavior.