AI Engine
Clustering. Regression. Classification. And More

CloudFabrix AI engine is the brain of its AIOps platform and is built on the principles of transparency, extensibility, scalability, easy to use and administer. AI engine provides in-built ML pipelines for core use cases like alert correlation, incident triaging and predictive insights. Additionally, customers can extend system ML pipelines or build new ML pipelines to introduce custom models or algorithms. These ML pipelines can support statical, machine learning or deep learning models that are trained using by neural networks.

  • Open, extensible and highly scalable AI engine
  • Support for deep learning models based on neural networks
  • Automated ML pipeline to reduce operations overhead
  • Pre-built ML templates to cover core AIOps use cases
  • Continuous monitoring and reporting of model performance
  • Support for bring your own model and algorithms

Data Ingestion & Integrations
Data From Any Source, Any Environment. Bi-Directional Integrations

AIOps efficiency hinges on having access to cross-domain IT data and seamless integrations with existing IT systems and tools. With our extensible data ingestion framework, customers can bring data from any source or any environment. Platform's connectors allow seamless bi-directional integrations with ITSM systems, CMDB systems, Automation and enterprise collaboration tools.

  • Extensible and scalable data ingestion architecture
  • Out of the box integrations with featured vendors and tools
  • Broad set of protocols/methods including webhook, API, queue etc.
  • Support for polling and queue based ingestion
  • Covers ITOM, ITSM, CMDB, Collaboration, Automation tools
  • Supports ingestion of both streaming data as well as offline/archival data (for learning)

Enterprise Discovery & Data Collection
Application Discovery & Mapping (ADM). Time Series Metrics and Log Collection. Agentless Enterprise Data Collector

CMDB data is not very accurate in most enterprises. In such cases, AIOps implementation and Asset Intelligence implementations need a mechanism to self-discover IT assets, configurations and mappings from any IT environment (datacenter, remote site or edge).

  • Discover & map config. of IT assets, infra devices, hosts, apps, services and more
  • Agentless approach enables rapid discovery without changing production systems
  • Flexible job scheduling, localized credentialing and easy exporting of results
  • Collect time series performance metrics and logs for Observability
  • Uses secure tunnel to relay performance data & logs to platform
  • Deploy in remote data centers, branch sites, edge environment and managed customer sites

Enterprise Discovery in AIOps
IT Asset Discovery & Mapping

Enterprise Data Collector runs as a standalone VM or Container in any environment. It uses agentless approach and can discover & map IT assets, hosts and workloads. Discovery runs can be scheduled to run periodically and results can be ingested into Dimensions platform for further processing.

Time Series Metrics and Logs Collection

Same Enterprise Data Collector can even collect time series performance metrics or logs from monitored devices, when the collector is deployed as part of our Observability solution. In this model, the collector establishes live connection with the platform over ssl/443 tunnel for data transmission


Built-In Diagnostic Automations Library. IPA/RPA/IAC Integrations for Runbook and Workflow Executions

Our platform enables incident diagnostics automation with built-in command library and incident resolution using 3rd party integrations with IPA/RPA/IAC tools. Diagnostic command automations have no risk and do not change underlying systems, and our platform provides a in-built library of commands that is extensible. On the other hand, incident resolutions do involve some element of risk and often need to perform change in underlying system and our platform takes the approach of partnering with purpose-built automation tools to handoff workflow executions and runbook automations to 3rd party tools.

  • Incident diagnostics automation with built-in library.
  • Automations can be programmed in Shell, Powershell, SQL, Python etc.
  • Tracking of automation job executions, history, results etc.
  • Learning from successful automation runs to deliver recommendations
  • Incident resolution automation workflows via integrations with 3rd party tools (IPA/RPA/IAC)
  • Ability to invoke 3rd party REST APIs and easily integrate with enterprise IT tools

Application Analytics & Intelligence Platform
Cloud Scale Architecture
Microservices. Containers. Cloud Scale.

cfxDimensions supports several standard Microservices architectural patterns like service discovery, configuration management, load balancing, messaging, etc. cfxDimensions can now provide high capacity data ingestion and integration with third party systems. This includes:

  • Enterprise grade platform for large scale Microservices applications
  • Purpose built to develop, deploy and manage cloud native applications
  • Container-ready and native support for Kubernetes environment
  • Deployable and scalable in any cloud environment
  • Rich command-line interface (CLI) and console to address the needs of DevOps
  • Built-in security, governance, multi-tenancy and analytics capabilities

Application Analytics & Intelligence Platform

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Add-On Native Apps

Log Analytics

Provides visualization, advanced analytics, indexing, and archival of IT Logs, Application logs and Events

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IT Monitoring

Providing real-time availability, performance metrics and insights for the full IT stack across hybrid cloud environments

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