Data-centric AIOps Platform
for Hybrid Deployments
Powered by Robotic Data Automation Fabric
Siloed Operational Domains have Gaps
RDAF™ is world’s first data fabric architected to unify Data Observability, Security & Automation Domains and take on the challenges of data intelligence and automation.
Digital-first businesses are striving for service assurance, which has become the lifeblood for their businesses applications. But these applications are increasingly getting complex across legacy and containerized cloud-native architectures, multi-cloud distributed micro services, and with the rise of 5G and edge.
RDAF consolidates your disparate data sources, converges on the root cause by applying dynamic AI/ML pipelines and concludes by remediating with intelligent automation. Data-driven organizations should explore, evaluate and implement RDAF for faster innovation, faster time to value, meet SLAs and SLOs, and excel at customer experiences.
CloudFabrix Data-centric AIOps Platform
Powered by Robotic Data Automation Fabric
Robotic Data Automation Platform
Unifying Observability, AIOps & Automation
CloudFabrix is a leading cross-domain Observability, AIOps and Automation solution that uses AI/ML technologies to reduce noisy incidents, accelerate incident resolution with root cause analysis and provide predictive intelligence to prevent unplanned outages or service degradations.
A data fabric is a critical component for successful Generative AI (GenAI) implementation. It provides the necessary foundation for accessing, managing, and governing the vast amounts of data required to train and fine-tune AI models.
The convergence of Generative AI, Data Fabric, Observability, and AIOps is reshaping the landscape of IT operations. A Gen AI Data Fabric offers a powerful foundation for enhancing observability and AIOps capabilities.
Data fabric and observability pipelines are complementary components in modern data architectures. While data fabric focuses on creating a unified data layer, observability pipelines ensure the health and performance of data systems.
CloudFabrix RDAF employs a bot-based architecture to streamline data automation and management. This approach combines the power of a data fabric with the flexibility and ease of use of a low-code platform.
CloudFabrix Composable Analytics is a powerful feature within the CloudFabrix AIOps platform that empowers users to create tailored analytics solutions based on their specific needs. It leverages the underlying Robotic Data Automation Fabric (RDAF) to deliver actionable insights from vast amounts of data.
Key Tenets
Cloud Native Architecture
Secure, multi-tenant, microservices and containerized based
Low Code/No Code Platform
Business professionals with minimal or no coding experience can build observable data pipelines and fill the talent gaps in their organization
Self-Service IDE
Experiment, Automate and Publish Data & ML Pipelines for Observability and Log Intelligence with RDA Studio
Eliminate Data Silos
Democratizing and self-serving data insights to multiple personas - citizen developers, CloudOps and SecOps teams, Splunk, Elastic admins, IT engineers, SREs, and DevOps, DataOps teams.
Build pipelines with DataBots
Prebuilt libraries or purpose built. Databot is a containerized atomic unit, with access to datastore and messaging api’s, AI/ML libraries and low code programability
Data Fabric
cfxEdge and cfxCloud secure messaging and deployment. Data pipelines comprising of DataBots
Data services
Log Intelligence, AIOps, AIA, IT service Management, DataOps
BYOT – Bring your own tool
Unify all disparate data sources with on the fly integration
Data In motion
Designed for batch and streaming data Edge and IoT data sources
Optimized Ingest
Parallel high throughput streaming and batch ingest at edge or cloud. Seamless onboarding
cfxCloud Autonomous Enterprise Strategy
Turn Data Swamps into Actionable Insights and Automation
Security
CloudFabrix Commitment to Security & Privacy
CloudFabrix is committed to maintaining the availability, integrity, and confidentiality of customer data. We’ve implemented robust processes and standards to secure customer data across all our platform operations.
