Future of AIOps –GAVS View

AIOps – Artificial Intelligence Driven IT Operations AIOps is performing IT operations through self learning and self correcting systems. AIOps deploys: Machine Learning techniques to understand the ever changing IT environment Artificial Intelligence to detect abnormalities Intelligent automation to remediate abnormalities before it impacts

Self Learning AIOps platform should not be depending on CMDB or ADDM or ITSM or Knowledge base for ‘Event Correlation’ It should learn from the kind of events and way those events are happening Reduce the configuration of tools as much as possible; Eliminate the dependency on other tools as much as possible

Pattern Based Alerts, Correlations & Predictions Generate alerts based on historic performance & consumption taking into account the day, time, load, related services & devices Correlate based on the pattern by which the events, logs and alerts are generated in the environment Provide prediction based on pattern based events & alerts No Rules or Configurations or inputs Anywhere

All In One Pane Of Action

Predictions

AIOps Platform Should Be An Adult Babies – consume what they are fed, as good or bad as the inputs Teens – Ask what they want to consume, still dependent on others Adults – Generate and consume, completely independent AIOps platform must not only take the data from other tools, but also know what data it needs and generate those data if they are not available

AIOps – Closer To Application Monitor Analysis Action Application Monitor/Analysis/Action Application Application Monitor/Analysis/Action Move the AI more and more closer to the application that needs to be monitored

Performance - Yesterday, Today & Tomorrow Graphical view of the journey of transactions showing the devices they cross through with response times of the past, present and future between devices , end to end. AIOps should do more than just ‘event correlation’ during an incident. Help engineers understand the performance yesterday – today – tomorrow’

Business Outcomes Outcomes & Benefits ‘Single Pane of Command to efficiently run IT Operations Proactive IT Operations Led by predictive insights, min. 24hrs. ahead of time with over 90% accuracy Outcomes & Benefits ~40% reduction in incidents, and reduced incidents/user per month ~60% reduction in Mean Time to Repair (MTTR) ~ 50% reduction in overall IT Operations costs Agile monitoring & elimination of Digital Dirt, driven by auto discovery

Non Intrusive, Eco friendly No Agents No Connectors No Access to DB AI tools should be least intrusive and most ‘eco friendly’

Predict Business Process Health Predict the performance of each performance counter, relate them with other counters and predict the performance of the server and then the application and then the business process Business Process Health Index Define a framework that quantifies the health of the application and the business process

GAVS’ AIOps Platform for Smart & Intelligent QA Predicts - failure points, regression pack, automation pack, coverage… I&O and Apps Operational Data Unit Testing Data & Analytics Requirements Traceability Matrix Build Management Software Config. Management Code Review Insights Defect Management AI starts not after the application is installed, but much before – even when the application is under development

Zero Incident Framework TM AIOps based TechOps platform that enables proactive detection and remediation of incidents helping organizations drive towards a Zero Incident Enterprise TM GAVS is collaborating with Premier Institution in India for embedding AIOps into each application GAVS has implemented / implementing ZIFTM for 15+ customers across the globe