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.
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.
On the basis of analysis of infrastructure, application and users, issues are predicted in advance that affects availability and performance.
It involves identification and correlation of issues across the higher amount of data. Pattern Detection, detect Cyber Attacks and identifies abnormalities.
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.
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.
End-to-End Visibility into infrastructure and applications, BlockChain, Internet of Things(IoT), Virtual Reality, Augmented Reality, 3D Printing and Robotics , increase in bandwidth.
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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