Overview of AIOps Monitoring with Microservices
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.