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Generative AI for Data Center Infrastructure Management


Generative AI for Data center Infrastructure Automation

Generative AI based methods to influence the IT Infrastructure Automation and Management. Leading AI Solutions for Infrastructure Management and Operations Service Offerings –

  • XenonStack The Necessity for AI Insecurity Image

    The necessity for AI insecurity

  • XenonStack the Demand for Greater Resources Image

    The demand for greater resources

  • XenonStack Intelligent Monitoring Image

    Intelligent Monitoring

  • XenonStack Automated Support Intelligent Storage Image

    Automated Support & Intelligent Storage

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    AI-defined Infrastructure Management

  • XenonStack Monitoring Engagement Ecosystem Image

    Monitoring & Engagement Ecosystem

Generative AI Solutions for Cloud Infrastructure Management

Harnessing Generative AI for Accessing and managing the computing resources effectively.

Anomaly Detection

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Real-Time Decision Making, Auto-encoders in High Performing Systems,Real-Time Root Cause Analysis, Cyber Intrusions and Fraud, find Temporal Patterns, prevention of potential outages and disruptions faced by the infrastructure.

Threat Detection

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Detects Distributed Denial of Service Attacks(DDoS) and BotNet, Security Automation, Predictive analysis, diagnosis, and recommendations, enhances human analysis, automates repetitive security tasks, and closes zero-day vulnerabilities.

Intelligent Storage Monitoring

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Storage resources are managed continuously for optimum utilisation and performance. Predictive Analytics automatically adjusts capacity of storage by adding new volumes proactively. Configuration Management and Energy Saving.

Features of Generative AI Enabled Infrastructure Platform

AI Transformation for Infrastructure and Operations.

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Automated Behaviour Prediction

On the basis of analysis of infrastructure, application and users, issues are predicted in advance that affect availability and performance.

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Root Cause Analysis - Intelligent infrastructure continuous Monitoring

It involves identification and correlation of issues across the higher amount of data. Pattern Detection, detects Cyber Attacks and identifies abnormalities.

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Data-Driven Recommendations

Better Decision Making at Real-Time and Historical Data, focuses on Data Ingestion, Storage and Data Management, safe Data Pipeline, establish Data Governance, ingesting various data types, Supervised Learning.

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DevOps Intelligence

Automatic Monitoring for deployment of metrics, Continuous Monitoring, quickly invoke issue detection rollbacks, Infrastructure as a Code (IaaC), generate on-demand infra utilisation metrics, Intelligent-Ops.

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Digital Transformation - Integrate IoT and Edge computing workloads

End-to-End Visibility into infrastructure and applications, BlockChain, Internet of Things(IoT), Virtual Reality, Augmented Reality, 3D Printing and Robotics , increase in bandwidth.

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Alert Notifications and Faster Deployment

Reduce operational noise across the production stack, deploy automated actions for known events with embedded business logic, increase the speed of monitoring and performance issues.

AI Infrastructure Related Insights

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