IT Operation Analytics – Next Generation Tools
Published on : Saturday 03-07-2021
Taking IT operations analytics to new dimensions using predictive analytics.
While every IT organisation fancies investing their budget dollars in the next big technology, and every vendor proclaims to offer that, their relationship is grounded in more mundane reality. There is business to be done every day, and applications that need to run round the clock to support them. Often, what defines a vendor’s success (and in turn the organisation’s IT team) is not what “new” they bring to the table, but how they manage what’s already there. And with so many different outsourcing options to choose from, organisations are looking for a fresher, more dynamic approach for IT operations management.
Challenges abound in today’s industry landscape. The current set of tools, where most of the data is usually captured either in the ticket management system or a knowledge base, is mostly two dimensional. It’s easy to see what incidents got recorded on an application, when, where, how, etc. And perhaps, only if there is a best practice governance and an enthusiastic team, the correct root cause or the symptoms behind it. But that is it!! The recorded data does not show any real pattern by itself and does not provide any indication of an application behaviour in relation to future time, events or critical changes. Most importantly, it is very difficult to create a productivity chart overlaying how external factors (major fixes, upgrades, infrastructure changes, hardware, and software age etc.), could impact an application’s health.
With the successful adoption of a myriad BI tools, technology surely is not a deterrent. The key is to define an IT Operations Analytics model (and build it accordingly) that can provide end to end visibility into the IT operations and predict with a high accuracy how they will be impacted in future, so that better plans can be put in place, costly mistakes avoided, and a lot of time and effort is saved.
Next generation IT Operations Analytics tools could have myriad of features, but the four mentioned below are essential:
KPI & SLA Dashboards
This would be the easy one to guess – isn’t it – who doesn’t like dashboards!! Almost every IT operation is measured by multiple key performance indicators (KPI), whether it’s related to application uptime and recovery, number of incidents, event recurrence, or application uptime and downtime flexibility.
At a bare minimum, dashboards should be able to provide a quick time period view (6 months to 3 years) of an application’s overall performance, its ticketing trends, its unbroken runtime and SLA (service level adherence), and importantly its relative performance against similar applications in the same category. All the information should be made available in a clean, easy to use format, and within a few clicks. Managers would ideally like to use this on a weekly, sometime daily basis to keep a tab on the overall application landscape. Additionally, dashboards should go beyond providing only numerical trends, and provide extra visibility on interesting terms, word clouds, and unstructured text patterns from the historical archive.
Application Complexity Rating & Predictive Pricing
A very effective long term tool, both for the IT organisations to keep an objective, quantitative score of their applications, and for the vendors to negotiate support pricing, this is another key feature that’s gaining prominence in the higher echelons.
While there is no single approach to define how “complex” an application really is, multiple parameters can be chosen based on relative measures, it can include its size and usage, volatility, criticality in the SLA pyramid, etc. The key is to define a solid algorithm that can provide a comprehensive score to an application based on weightages assigned to different parameters. This can not only help organisations (and their vendors) plan resources to support these, but also define a common, objective and non(less)-contentious way of application pricing. As applications change in the long term, this model can help provide a new rating and predictive pricing, an attribute that every IT organisation desires to have in today’s day and age.
Data discovery
Unlike the proverbial Jack and the Beanstalk theory – not every egg that the goose lays is golden. In the IT Operations world, this roughly equates to the fact that not every information presented to you is valuable to understand applications’ health. But the trick lies in data discovery tools that can mine the data with little guidance and can throw back some golden nuggets – that’s exactly what a data discovery tool should do. It should ideally be able to combine the power of statistical algorithms such as correlation and association and should be able to parse through large volumes of data to show interesting patterns.
In the real world, IT teams support hundreds of applications with tens of years’ worth of history on ticketing data. In this case data discovery may be extremely useful to mine information showing the most interesting patterns, whether it’s a type of failure or recovery for an application that resulted in a certain impact, or the correlation of multiple events (e.g., upgrading an application causing issues with the other) in the past. This is valuable insight for the IT operations teams to be able to understand causal relationships and avoid repeating costly mistakes
Predictive analytics – Train and test
Finally, it all boils down to the clairvoyance that the IT Operation Analytics can provide. This is the most complex, and if done right, the most rewarding feature of all.
Mostly used by application architects and application experts, this allows them to look at a large history of ticketing data, use specific algorithms to unearth organic patterns and relationships, and then train the model over a period to predict results. This could help predict basic items such as incident volumes and incident time of occurrence to more complex events such as application downtime, SLA impact, mean time to report and repair.
Summary
In the modern analytics era, it has become possible to apply the business intelligence best practices to IT operations and look beyond a traditional “respond and resolve” mind-set. Next Generation IT Operations Analytics promises to deliver more pertinent and predictable information regarding the applications and infrastructure that fall under the IT operations gamut.
Article Courtesy: NASSCOM Community – an open knowledge sharing platform for the Indian technology industry:
https://community.nasscom.in/communities/it-services/taking-it-operations-analytics-new-dimensions-using-predictive-analytics