Prediction for Business Service Assurance

Artificial Intelligence for IT Operations (AIOps) uses technologies like Big Data and Machine Learning (ML) to automate the resolution and identification of the common problems of Information Technology (IT).

Zero Incident Framework (ZIF) is an AIOps based TechOps platform which enables proactive detection and remediation of incidents which helps an enterprise to move towards a Zero Incident Enterprise.

Five modules of ZIF:

• -        Discover: To auto-discover all the IT assets and mission-critical workloads
• -        Monitor: End-to-end enterprise performance monitoring
• -        Analyze: Analyze and correlate alerts/events across tools
• -        Predict: Predictive techniques to prevent outages
• -        Remediate: Prescriptive remediation with minimal or no manual intervention

Predictive Analysis is ZIF’s USP. ZIF encompasses Supervised, Unsupervised and Reinforcement Learning algorithms for realization of various businesses use. They are:

                  Supervised Learning Algorithm:

·        Linear prediction

·        Seasonality based prediction

·        Recommended resolution

·        Virtual Supervisor

·        False Probability

·        Anomaly Deduction

·        Estimated Time to Complete

Unsupervised Learning Algorithm:

·        Sequence-based mining

·        Keyboard extraction

·        Sentiment Analysis (CSAT)

·        Data labeling

·        Log Analytics

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                        Reinforcement Learning Algorithms:

·        Log Rotation

·        Optimizing resource utilization

How does ZIF work:

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•       ZIF can receive and process all kinds of data through its ingestion capabilities
• -        Predicts anomalies by analyzing these data
• -        Anomalies can be presented as ‘Opportunity cards’ to eliminate any undesired incidents
• -        It brings out the paradigm shift since its proactive and reactive
• -        Predictions occur at multiple levels

Sub-Functions of the Predictive Model:

Functions:

-        Forecast capacity needs

·        Provides accurate resource utilization and usage predictions

·        Orchestrates the virtual infrastructure

-        Forecast Incident Volume:

·        Predicts to spike and exceed capacity

·        Predicts corrective actions

-        Detects potential failures:

·        Forecasts when capacity is about to exceed

·        Identifies problems even when they originate somewhere else

Benefits:

• -        Reduced manual effort
• -        Reduced errors
• -        Reduced cost of operations
• -        Optimized staffing
• -        Proactive IT Operations
• -        Drive towards zero outage
• -        Enhanced user experience

Predict module can categorize the opportunity cards into three swim lanes. They are:

• -        Warning swim lane: Opportunity Cards that have an “Expected Time of Impact” (ETI) beyond 60 minutes.
• -        Critical swim lane: Opportunity Cards that have an ETI within 60 minutes.
• -        Processed / Lost: Opportunity Cards that have been processed or lost without taking any action.

The above article has been taken from Zero Incident Framework, that is the best tool for predictive analytics using ai applications, and a leading cognitive process automation tools for business