Predictive Analytics Using AI Applications & AIOps Framework

Predictive Analytics

Predictive Analytics are critical for AIOPs platforms. ZIF’s algorithms forecast incidents based on their knowledge of trends & incident symptoms – gained by analyzing tons of historic data. ZIF^TM then generates opportunity cards a minimum of 60 minutes in advance, along with suggested proactive remedial measures, giving IT engineers a lead time to fix issues.

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Ensure better performance by forecasting resource utilization

Predicts ticket volumes, spikes and resource utilization levels in advance.

Provides accurate resource utilization and usage predictions
Dynamically orchestrates virtual infrastructure, with minimal manual intervention, on an on-demand basis

Predictive techniques to prevent outages

ZIF^TM leverages predictive analytics to build intelligent and resilient IT systems

Forecast Utilization

Forecast Incident Volume

Detect & Predict Potential Failures

Predict Performance Degradation

Forecast Incident Volume and stay a step ahead

ZIF^TM predicts incident volumes and usage pattern for up to a year.

Predicts when bandwidth, storage and application hits are most likely to spike or exceed capacity.
Predicts exactly when a warning would manifest into a problem and suggests possible corrective actions

Predict Potential Failures & Liabilities

Advanced Intelligent Incident Analytics (AIIA) enable identification of patterns and situations that precede an outage.

Forecasts exactly when you’ll exceed capacity and face spikes, then takes preventive actions accordingly
Identifies problems even when they originate elsewhere – e.g. a change implemented in the network can cause the application to fail
Uses AI logic that learn through outages and similar problems to identify the conditions leading to an outage well in advance

Predict Performance Degradation

Forecasting system behavior helps identify potential performance degradation leading to a future application failure.

It enables increased availability of systems and cost avoidance.

Other Features

Predictive Analytics

Predictive Analytics are critical for AIOPs platforms. ZIF’s algorithms forecast incidents based on their knowledge of trends & incident symptoms – gained by analyzing tons of historic data. ZIF then generates opportunity cards a minimum of 60 minutes in advance, along with suggested proactive remedial measures, giving IT engineers a lead time to fix issues.

Correlation & Noise Reduction

Noise reduction and correlation are crucial to bridge siloes across the IT landscape. ZIF helps identify dependencies and relationships across the dynamic infrastructure and increases productivity and efficiency through actionable insights.

Agentless Auto-Discovery

With ZIF, you can ensure automatic discovery of every application in your environment, irrespective of application type, technology or where the application is hosted. Obtain visibility of all users of every application in your environment, their activities, groups and privileges, along with their unique user experience.

Intelligent Automation

One of the key drivers of digital transformation is intelligent automation which simply is the combination of automation and artificial intelligence for smooth business functioning. ZIF enables IT process automation through algorithmic IT operations and its AI-led capabilities for advanced insights, predictions, and auto-remediation which drive consistent business service reliability.

Agentless Monitoring

ZIF is the only end-to-end environment performance monitoring tool which provides full stack visibility and is capable of monitoring infrastructure and application stacks from an enterprise level down to a single device or microservice.