What is AIOps?
How It Works?
- State of the art machine learning algorithms that learns from baseline performance of across all layers including applications and the infrastructure, automatically learning and alerting whenever any deviations are detected.
- Predictive capabilities across all layers to identify probable causes of issues as well as impending ones, preventing interruptions to services in advance.
- Foresight into the future by identifying resources that are close to exhaustion to allow for capacity planning, ensuring the customer experience is never compromised.
Non-intrusive data collection
- Provides REST API for users to feed data for prediction and analytics - Transparent data collection modules allow users audit and self-configuration
- Cross-layer correlation and impact prediction (applications, virtualizations, infrastructures and facilities) - Failure and fatiguesp prediction of infrastructure devices for optimized resource utilization and planning - Applies state-of-the-art and US-patented machine learning technology to predict failure and degradation of disks, including HDDs and SSDs across SATA and SAS. Predicts disk and host behavior, including performance and usage, which is critical to streamlining the operation of storage and servers
Impact Analysis and Correlation
- The impact of a potential risk is visualized by correlating the affected components. - Correlation from hardware layer to virtualization layers in infrastructure and applications.
Full Stack Visibility
- Easy-to-use dashboard provides total visibility of disk performance and health status.
- Application Performance Monitoring (APM) from AppDynamics, NewRelic and Dynatrace
- Public Clouds from Amazon AWS and Microsoft Azure
- Server and Application Virtualization from VMware and Kubernetes
- Hyperconverged Infrastructure from VMware and Nutanix