1. Future of AIOps –GAVS View

2. 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

3. 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

4. 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

5. All In One Pane Of Action

6. Predictions

7. 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

8. 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

9. 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’

10. 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

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

12. 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

13. 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

14. 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