AIOps - Minority Report of IT world
Minority Report is a 2002 American science fiction film directed by Steven Spielberg. Why am I talking about movies all of a sudden? The movie had a very interesting theme where a special police unit can arrest murderers before they commit their crimes; for me, system failures, or any failure, for that matter, in IT is a crime. Even though we can’t predict the future in real life, we can at least analyze real-time data and stats to reach a conclusion and avoid or stop crime before it affects your system.
IT industry has been all about innovation and evolution since the start. We have seen drastic changes in how we process, analyze and store. These changes have impacted IT infrastructure requirements; legacy infrastructure to the cloud and container-centric environments is one of the outcomes. The increased size of IT infrastructure has resulted in increased computing performance and processing speeds. But, this is at the expense of increased infrastructure complexity. So, to make sure your IT infrastructure relentlessly delivers the expected performance without fail, you need systems that can monitor, alert and diagnose; Server monitoring, physical or virtual, SLA monitoring, Application monitoring, Capacity planning, and Cloud infrastructure monitoring, to name a few. This all gave rise to a term called “IT Operations” or “ITOA,” which is nothing but a system with a set of people who operates on a simple principle - monitor IT infrastructure and operations, look for an IT failure, act on the IT failure, analyze and process static data and avoid future failures with the analyzed historical and static data. The operating principle points to the system's frailty; it uses historical and static data. This was all good till operations teams could cope with the continuously increasing rate of change. But recent advancements have caused the rate of change to accelerate exponentially, which will go up. If you keep on sticking with the same approach, the IT operation team will soon be surrounded by a pool with sharks of Red Alerts of the system or IT failures, which eventually will hamper overall system performance and, ultimately, your business.
Why AIOps?
IT admins need a system to cope with the ever-changing IT requirements, and AIOps is just the thing. AIOps, as Gartner calls it, separates itself from ITOA because it uses real-time data in addition to historical data. AIOps refers to solutions that use artificial intelligence and machine learning to automate tasks and processes, eventually reducing the required human intervention part to a minimum.
The principle used by AIOps is simple, take inputs from existing monitoring tools, apply algorithmic techniques, analyze them, and produce an output that is an insight action item for the operations team. AIOps analyze historical and real-time data, issue an early warning for probable problems, bring it up to the right department or person, apply a fix automatically if possible, and raise a ticket in advance instead of letting that problem become a disaster, then document it in your catalog. You can also have this ticketing system loop in with a predefined set of measures for a set of problems that can be solved with the help of machine learning and artificial intelligence.
How to AIOps?
A typical AIOps platform will have:
• Monitoring system: comprised of the necessary monitoring tools, providing visibility across the infrastructure
• Data pool: with all the historical and real-time records which will be analyzed with the help of algorithms, all tickets raised, all solutions suggested, and all the actions taken along with results
• Intelligent Analytics and Engagement System: with predictive algorithms, automated solutions, and alert mechanisms which will run automated scripts for solutions and alert concerned personnel or system with the help of machine learning and artificial intelligence
What can you get out of AIOps?
It is evident that AIOps will help us ensure all functions are up and running, and in the case of failure, AIOps ensure it is ironed out, even before we notice it was there. Apart from conspicuous benefits, you can have better visibility into infrastructure, real-time analysis, automated behavior prediction, recommended actions, scheduled maintenance and performance assessment cycles, and all the analysis reports. As a result, you can trim down resolution time, operational and maintenance cost, time to detect and restore and scale up on productivity, agility, quality, user experience, and availability, giving you an edge over your competition.
As per Gartner’s study, about half of global enterprises will be using AIOps, although only 5% of them use it as of 2017; even with all the monitoring tools and systems, the human brain has its own limitations. So, instead of waiting, detecting, analyzing, and solving, we can have a new approach with AIOps where we can analyze, predict, and avoid or solve as soon as or even before the problem arises.
Most organizations are good at the ‘Dev’ part, but very few excel when it comes to the ‘Ops’ part, which is the core of the AIOps platform. Opcito’s DevOps and Machine Learning expertise are the key factors while moving ahead into the AIOps world. In our next blog, we will discuss the possibilities to make your DevOps intelligent using AIOps.