It is well known that visibility is a foundation of control. The same applies to IT operations. However, in today’s continuously expanding data centers, dynamic IT environments produce far too much data for IT operations to keep track of.
Billions of machine events, environment and application changes, performance and availability metrics, and vast amounts of other structured and unstructured IT operations data from a wide variety of sources go mostly unprocessed, requiring greater visibility into IT’s Big Data problem.
With little time available and too many tools already in place, the IT industry needs to shift to a new approach. Now IT Operations Analytics tools can automatically offer real actionable insights, rather than just slicing and dicing overwhelming amounts of data, allowing IT managers to be better informed for making decisions about their environments and critical business systems.
This new approach and supporting technologies stand to transform IT operations, providing a true single pane of glass and promoting the collaboration of various IT teams, enabling a more proactive approach to IT operations and drive more agile and flexible IT processes.
Factors Driving IT Big Data Challenges
Current business trends center on tackling big data challenges with analytics to gain business insights. So, when we consider how business has applied analytics to their specific data challenges, why are IT operations, who actually enable the technology for business and BI analytics, lagging behind?
Traditional IT management tools have been applied to monitor infrastructure and applications, automate and manage IT operations processes in data centres, yet they can’t process all of the raw data now being collected. Lacking the ability to provide visibility and insight into the actual meaning buried in this data, IT operations doesn’t have an effective way to track down problems and also prevent them.
As an example, changes being one of the key contributors to these problems still remain a blind spot of IT operations exposing business systems to risk each time a change happens in application, infrastructure, data or workload. Challenges faced by IT operations have intensified due to both the rapid growth in performance and event monitoring data volumes, as well as for the following reasons:
Many in IT operations currently cite complexity as the root cause of many issues. With millions of different configuration items to manage, each controlled by thousands of configuration parameters and growing interdependence between the environment components, IT operations finds it difficult to manage and control the delivery of critical business services.
According to Forrester Research, “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. Time is now the enemy because complexity is growing exponentially and inexorably.”
For IT Operations, changes occur constantly. Where application updates used to be a monthly occurrence, with a few weeks for application stabilisation in production, now, however, accelerated application and software deployment schedules are driving high-paced change activity.
The same applies to the schedule of infrastructure updates. Implementation of agile development processes, and adopting such practices as continuous integration and continuous build, are pushing higher numbers of changes, making it practically impossible to keep IT environments stable, and creating higher risk for error.
Many organisations still don’t have a single authority accountable for end-to-end ownership of IT environment management. Rather applications may run on different physical and virtual systems that communicate across networks, which in turn may include internal and external segments with limited visibility.
While there are tools for BTM (business transaction management), APM (application performance management), SM (service management), and Service Desk, they each focus on handling their particular scope of metrics and data in their own process silos, lacking broad and deep visibility into the state of the overall IT environment.
IT Analytics Tools Take New Perspective
Between applications, environments, and individual instances, mistakes and unauthorized changes happen, demanding that IT ops spend long amounts of time managing IT systems. With change requests and changes coming at a blinding pace, IT operations teams have tried to rely on automated approaches to keep up. While able to accelerate responses, only when automation is integrated with analytics can automated tools effectively take on change issues.
To improve decision-making about business technology services and their underlying infrastructure and applications, IT operations needs to apply the big data concept to the IT side of the organisation. New IT Operations Analytics tools take a fresh perspective on the abundant data and complexity confronting operations teams.
According to a recent survey, 81% of IT professionals surveyed agreed that IT Operations Analytics should be applied to IT’s big data challenges, to enable IT operations to better manage critical business technology services.
A New Approach To Tackle Big Data
Various new tools are incorporating analytics and are taking different perspectives on the abundant information confronting IT Operations teams. Netuitive analyses application performance data. Splunk indexes and searches machine data including various logs. OpTier takes a transaction-centric approach, feeding data into their analytics module, carrying out granular analysis down to the transaction instance level to keep track of everything at a birds-eye view.
Yet, managing the change and configuration of multiple environments is still the curse of IT Operations. Whenever a change is made, there are a myriad of ways it can negatively impact environment stability. While solutions like APM collect metrics assessing the state of environment components such as disk storage growth, a rise in I/O or even the entire business transaction time, they have difficulty connecting these metrics to a root cause. Looking through the context of changes, IT operations can actually tie in a top down perspective of IT activities with their actual impact measured through APM.
By basing analytics on a blend of IT data (log, APM, CM, Security), IT Operations Analytics can sift through terabytes of operations data in real time, to spot and present issues to users in understandable context to better handle problems critical to IT health and performance.
IT Operations Analytics can help users uncover why environments are not operating as they should, correlating various metrics into context of activities changing state of the environment (release, infrastructure update, user workload change etc.) and handle the problem, allowing operators to successfully remediate it.
Between applications, application infrastructure and infrastructure, mistakes and unauthorised changes creep in (as has been seen with some high profile outages) making IT ops spend more time managing configuration and changes. IT Operations Analytics can take a complex IT environment overflowing with data and transform it, turning operational data into a competitive tool that provides users with the right information at the right time.