AI along with Microservices Architecture stack involves –
Multi-Accelerator Hardware
Hyper Converged Infrastructure
Continuous Insights
AI Driven Dynamic Storage
Agile Multi-cloud deployment, containerization and virtualization
High Bandwidth and Low Latency
High Performance AI software, libraries, and models
AIOps with Microservices Involves
Automatic Discovery – For executing Advanced Analytics on accurate data having continuous discovery and mapping.
Precision and Visibility – To perform Artificial Intelligence training to give deep visibility to Microservices applications.
Application Modelling – To update changes in Real-Time, troubleshooting with precision, prediction, problem resolution with full stack application of strong data model to achieve intelligent analysis of predictions and problems.
Cloud Native , Containers and Microservices – For infrastructure alignment, visualization, eliminating configuration leveraging containerisation and orchestration.
Real-Time AI Driven Incident Monitoring – For performance insights, Monitoring at a faster pace, actionable information, alerts alignment, tracing data, predicting warnings and changes.
AI Powered Trouble shooting – To assist monitoring and management tasks in eliminating errors and enabling flawless deployments.
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