AI in Infrastructure Services

Anomaly Detection

Anomaly Detection

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

Threat Detection

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

Storage Management

Storage Management

Storage resources are managed continuously for optimum utilisation and performance. Predictive Analytics automatically adjusts capacity of storage by adding new volumes proactively. Configuration Management, Energy Saving, Proactive failures Predictions, Trouble shooting and automated fixes.

Services

Artificial Intelligence Services for Infrastructure Systems

  • The demand for greater resources
  • The necessity for AI insecurity
  • Intelligent Monitoring
  • Automated Support & Intelligent Storage
  • AI-defined Infrastructure Management
  • Monitoring & Engagement Ecosystem.
  • System of Record & Automation.
  • Data Lake, Artificial Intelligence, Time Series Database & Analysis
Artificial Intelligence Services for Infrastructure Systems
Artificial Intelligence Solutions offerings for Infrastructure Industry

Artificial Intelligence Solutions offerings for Infrastructure Industry

With the growth in technology and infrastructure, rapid advancements are there in software-defined infrastructure and Cloud Computing. This has enabled the IT Infrastructure to be flexible, intangible and on-demand. On the other hand, IT Infrastructure is not yet intelligent enough to understand the correlation between the IT elements, recognising the data trends and further take the appropriate decisions. Therefore, Artificial Intelligence is introduced. It enables to access and manage the computing resources to train, test and deploy AI algorithms.

  • Capacity Planning & Resource Utilisation
  • Incident Management
  • Kubernetes and Amazon Web Services
  • Smart Architecture & Real-Time Cost Analysis
  • Dynamic Thresholding, Automatic Identification & Pattern Detection
  • Operational Noise Reduction & Energy Saving
  • Configuration Management , Intelligent Monitoring and Storage

Features of AI Driven Infrastructure Platform

Automated Behaviour Prediction

Automated Behaviour Prediction

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

Root Cause Analysis

Root Cause Analysis

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

Data-Driven Recommendations

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.

DevOps and Cloud Automation

DevOps and Cloud Automation

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.

Digital Transformation

Digital Transformation

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

Alert Notifications and Faster Deployment

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.

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