Balaji Uppili, Chief Customer Success Officer, GAVS
Artificial Intelligence in IT operations (AIOps) is rapidly pacing up with digital transformation. Over the years, there has been a paradigm shift of enterprise application and IT infrastructure. With a mindset to enhance flexibility and agility of business processes, organizations are readily adopting cloud platforms to provision their on-premise software. Implementation of technologies like AIOps and hybrid environment has facilitated organizations to gauge the operational challenges and reduced their operational costs considerably. It helps enterprises in:
With the increasing efficiency and sophistication of our IT systems, their complexity opens up a constant slew of challenges for IT Ops departments, and Artificial Intelligence for IT Operations (AIOps) today has emerged as the answer to manage such complexities.
AIOps combines the power of Big Data and Machine Learning and automation and offers process automation independent of manual resources. What makes AIOps a winner is its functionality of combining data driven insights from various systems and operational tools that brings significant improvements and probably the best solution for now and future along with cost efficiency.
Driving data through Analytics for meaningful, actionable insights and the subsequent optimization and transformation using Machine Learning that helps in informed decisions and enables IT Ops resources to spend more of their time in quality tasks to support business goals rather than fighting the day to day blips and glitches.
With the Zero Incident FrameworkTM (ZIF) picking so much attention, we thought this is the best time to bring you some insights from our Leadership.
In conversation with Balaji Uppili, Chief Customer Success Officer, at GAVS;
Why do you think AIOps is picking up pace suddenly when these issues have been existing in the industry for the past many years?
Balaji: AIOps is really picking up because the day to day operations are becoming more complex and the amount of operational issues are increasing by the day. Also, AIOps is no longer being used as operational tool but more strategic. This creates bandwidth from an operational standpoint and also in the cost aspects as well. This also provides lot more predictability and proactive approach.
What do you think is the next phase of AIOps?
Balaji: The various dimensions of Machine Learning like Reinforcement Learning, Reinforcement deep learning would definitely take off. A good interface with a virtual assistant / conversational assistant is the future.
Is AI truly helping infra team to be ahead of the curve or is it just a hype?
Balaji: It is not a hype at all. There is also no other alternative to it as well. AI is now the key expectation for running efficient and seamless operations.
How do you quantify the ROI to CIOs when they invest in these products?
Balaji: The quantification happens from reduction in license costs for various tools being deployed and also optimization due to automation and shift left from a process optimization stand point. These will have direct reduction in operational costs both asset and resources (labor included).
What makes ZIF the biggest differentiator in the market?
Balaji: Its ability to reduce noise in the operations (eliminate unwanted data points and also eliminate spikes due to seasonality in operations) world in an enterprise clubbed with its predictability capability (provide approaches to learn from past historical data and arrive at models for the future) which can help the CIO be ahead of the operations both from end user experience and costs.
How do you claim to have embraced AI in ZIF?
Balaji: The various algorithms are very AI driven. The self-learning from both historical data and current environment and context and using that to predict the future is all in the platform.
What is the success rate your customer’s have seen, by adopting ZIF?
Balaji: As regards to automation, customers have seen at least 30%+ automation of operations and processes over 12 months and some even 50%+. With regards to noise reduction and correlations about 70%+(avoiding duplicates and eliminating seasonalities) and predictions in some cases with about 80%+ probability.
How do you think an organization should evaluate the right AIOps platform? What parameters should they consider?
Balaji: The theme of our platform at GAVS is “Zero Incident”. How can we get all enterprises to a zero incident state? If that theme is applied, then each and every aspect of the operation is evaluated towards a zero incident journey and this will automatically result in massive cost savings and significant increase in end user experience.
By implementing AIOps platform, are organizations creating unemployment?
Balaji: This is a wrong myth and assumption. If we don’t automate and don’t become a responsive and agile enterprise, then the businesses won’t run. The future is all about AIOps and beyond and hence adoption of these concepts by the teams is critical. This will help the teams to reskill themselves to working on automation, data science and related areas and thereby enhance their own value both within the organization they serve and outside as well. The AIOps platforms are evolving to make you better and hence a change management and re-hash of the workforce goes with it.
How do you make sure ZIF is always ahead of the curve in the AIOps space?
Balaji: Our internal research and marketing team plays a huge role in keeping us ahead. In addition, our partnership with Microsoft, Gartner, Everest and more importantly with IIT Madras, does help us to be ahead of the curve.