Artificial Intelligence to Predict Oracle ERP Business Application Issues across Hybrid IT
Many enterprises are accelerating their digital transformation and increasing their dependency on critical business processes built on solutions like Oracle ERP and custom Java applications. Meeting the business SLA for critical business processes is highly dependent on the uptime and performance of underlying and application entities. Ensuring the uptime and performance of the entire stack supporting the business process is very challenging when they are distributed in hybrid IT environment.
FixStream AIOps platform combines its powerful multi-layer correlation across business KPIs, application and infrastructure across a multi-vendor and multi-domain environment. By doing so, it enables IT Operations to reduce MTTR, predict when business application issues will occur across any portion of their hybrid IT stack, and to gain unprecedented insights into mission critical business processes such Order-to-Cash, Procure-to-Pay, and eCommerce.
- Dynamic discovery of applications and logically group the applications to business process such as O2C, P2P, SCM, eCommerce etc.
- Ingestion of business KPIs via FixStream open API layer and correlation with business applications and infra
- Personalized single-pane-of-glass views of business process and operational health
- Quick view into infrastructure health and application health supporting the business process
Business and IT Operations KPI dashboard
- Automated mapping of business KPI issues to business and system errors
- Reduction of root cause identification time from hours/days/weeks to minutes
- Business processes built on Oracle ERP, Oracle Real Application Clusters, Oracle VM hypervisor, Oracle Fusion Middleware
Business Process to IT Infrastructure Mapping
- Flow2Path™ mapping of application flows to the infrastructure path
- Automated mapping of business process to underlying compute, network and storage infrastructure
- Contextual overlay of operational data such as server/network/storage performance metrics and log events for rapid root cause identification
- Identification of flows in on-premises, hybrid, public or Oracle ERP cloud deployments
Time-series Event Correlation and Prediction
- Events are stored in time-series and correlated and analyzed via machine learning algorithms for patterns and anomalies
- Dynamic thresholding and multivariate anomaly detection identifies critical planned and unplanned business events
- Sequential pattern detection for incident prediction