AIOps needs to process vast amounts of data from hybrid environments and diverse data sources. But raw data is often unusable. Automate all AIOps data prep and integrations with intelligent data bots and low-code data pipelines using Robotic Data Automation
Ingest logs, events and traces from any monitoring tool (APM, ITIM, Cloud, Log etc.) to perform high-scale unsupervised ML driven from multiple data sources to reduce alert noise, reduce tickets and bring actionability to incidents.
Accelerate incident resolution by having all the incident context, incident causing alerts, CI/stack impact assessment, triage data like time series metrics & logs, root cause insights, in-place collaboration console and diagnostic tools - all at one place.
Proactively watch critical IT services or stacks to predict or prevent IT failures, by continously observing leading indicators, anomalies, correlated behaviors or user specified outcomes. Stacks or services are automatically learned by system, but can also be feteched from CMDB or manually defined by administrator.
Gain real-time 360-degree IT asset visibility, utilization and dependencies, along with key insights about upcoming lifecycle events (like end of sale/support/life), supportability risks due to missing or out-of-contract assets, identify non-compliant assets and measure/track enterprise specific plan of record or compliance policies.
CloudFabrix Observability solution comes with native support of monitoring infrastructure, application, services of both traditional and cloud native architectures with metrics, logs and traces using open source technologies. Customers can also ingest data from 3rd party tools to standardize access of observability data across the enterprise.
- Sr. Principal IT Consultant, Leading Managed Healthcare
- Sr. Director, NetOps
- IT Director, Command Center
- Sr. Director, Major Incident Management
- Sr. Enterprise Architect, Infrastructure Services
- VP, Engineering & Operations
- Practice Lead, IT Modernization & Transformation