Press Release

CloudFabrix Was Recognized as One of the Only Two Outperformers in 2023 Gigaom AIOps Radar Report and as a Leader and Innovator for the 3rd Consecutive Year

Low code Bot-based Robotic Data Automation Fabric architecture for rapid development and GenAI capabilities for efficiency, sets CloudFabrix apart

PLEASANTON, Calif.-- July 18, 2023 -- CloudFabrix the inventor of Robotic Data Automation Fabric Platform and the Data-centric AIOps Leader, was named a Leader, Innovator, and Outperformer in the 2023 Gigaom Radar report for AIOps for a 3rd consecutive year. The report evaluated 30 major AIOps vendors across Key Criteria for evaluating AIOps solutions and evaluation metrics that should be applied when selecting an AIOps solution. The report segregates these 30 vendors across Leaders, Challengers, and New Entrants, including Forward Mover, Fast Mover, and Outperformer.
CloudFabrix was identified as a Leader, Outperformer, and Innovator. According to the report “CloudFabrix’s Robotic Data Automation and Data Fabric provide a unique method of ingesting data. The solution deploys in any environment and has strong low-code/no-code capabilities throughout. OpenTelemetry data ingestion is supported. Predictive capabilities are functional. The generative AI assistant provides an additional method of querying the environment” which identifies them as an Outperformer among the evaluated 30 vendors.

The report succinctly defines the relationship between Monitoring, Observability, and AIOps(awareness). “As a key component in the development of operational and organizational awareness, AIOps combines data and information from across the enterprise to improve root cause analysis, prediction, and automatic response, reducing time to resolution (MTTR) and producing better enterprise-level outcomes. Moreover, the integration of business intelligence (BI) data enables AIOps to answer questions about the state of the entire business” according to the report.

According to the report, “ The displacement of incumbent tools continues to be a concern with AIOps. The platform players perform best when their tools control monitoring, alert, and event data. For large enterprises, the political capital necessary to displace organically sourced and developed tooling is substantial. Domain-agnostic tools may be better solutions. These can be layered on top of existing tools with little or no redundancy. CloudFabrix is identified as a domain-agnostic solution.

CloudFabrix Data-centric AIOps platform

Gigaom Radar Report for AIOps 2023 (Graphic: Business Wire)
CloudFabrix’s Data-centric AIOps platform
CloudFabrix’s Data-centric AIOps platform combines Observability, AIOps, and Automation within a low-code environment. It is well suited for SMBs, large enterprises, and MSPs and can be deployed as SaaS ( AWS Marketplace), On-premises, or Hybrid and Multi-cloud deployments.

The report further explains why CloudFabrix excels across the Key Criteria of evaluation laid out for evaluating all the vendors -

  • Data collection and analysis
    • Is robust and includes OpenTelemety and CloudFabrix’s RDA bots and data observability pipelines. The platform uses these low-code/no-code bots and pipelines to process, prepare, and transform the raw data into payloads that are tightly integrated around ITSM, collaboration, ChatOps, and workflow automation. AutoML is used in robotic data collection and pipeline creation.
  • Auto-remediation
    • Predictive analytics enables auto-remediation. CloudFabrix provides bi-directional collaboration and workflow management as part of event correlation and incident management workflows. The solution is not dependent on integrations with other workflow tools and has the ability to conduct task and workflow management tasks natively.
  • Customizable Dashboards
    • The solution is built with “composability” as one of its foundational principles, allowing users to create their own dashboards. Dashboards are built using a drag-and-drop dashboard builder as well as JSON-based definitions. Reference dashboard templates are available for prototyping and iterative development.
  • Predictive Analytics
    • CloudFabrix has predictive analytics capabilities built into the platform. As the data is ingested and collected, time series regression models are trained, which can help in performing trending, seasonality, anomaly detection, forecasting and prediction, and KPI forecasting. Models can be (re)trained on a periodic basis or if drift is detected. With enough data, the solution can predict a year into the future. For advanced scenarios, it allows complete customization of the ML model, the use of a different model, or customizing the model with hyperparameter tuning via the low-code ML pipeline.
  • BI Integration
    • Out-of-the-box integrations include Microsoft PowerBI, Tableau, Kibana, Grafana, and AWS Quicksight. There is also integration with Cisco Appdynamics Business IQ. Integrating with new BI tools is accomplished using low-code REST API bots and data transformation systems. Data payloads can be constructed and sent to the BI tool to populate analytics and dashboards
  • Multi-cloud support
    • The solution is architecturally built to support multi-cloud environments and hybrid cloud environments, including private-cloud remote/branch/edge environments. The platform provides single-pane visibility into multi-cloud data.
  • Service-level management
    • CloudFabrix offers SLO management capabilities by defining SLOs via policies and/or thresholds, and predictive alerting criteria can be defined to identify potential performance issues. The data can also be integrated with third-party BI tools.
  • Task and Workflow management
    • The platform uses low-code/no-code bots and pipelines to process, prepare, and transform the raw data into payloads that are tightly integrated around ITSM, collaboration, ChatOps, and workflow automation. AutoML is used in robotic data collection and pipeline creation.
  • Value metrics
    • CloudFabrix’s data-centric AIOps platform captures key MTTx value metrics to provide insights about performance, including forecasting when failures will occur and tracking how well such failures are detected and addressed. Metrics and KPIs can also be defined using low-code/no-code bots, and can be produced using a generative AI assistant and by querying using CloudFabrix’s CFX query language.
To learn more about AIOps and Observability market trends and “Why CloudFabrix is an Outperformer in Gigaom 2023 Radar report?”, please attend this webinar on July 27th' 2023

Supporting Quotes

Dr. Anjali Fields, General Manager, and Practice Lead, Datacenter Transformation, Wipro
"We would like to congratulate CloudFabrix on their inclusion into the 2023 Gigaom Radar report for AIOps, as an Outperformer. We have 1st hand experienced their capabilities during our joint Proof of Concept (POC) in our Centre of Excellence (COE) and we can say with the highest confidence that their accolades are well deserved" said Anjali Fields, General Manager and Practice Lead, Datacenter Transformation, Wipro.

Shailesh Manjrekar, Chief Marketing Officer, CloudFabrix
“It has been an absolute honor to be recognized as a leader and innovator in the Gigaom Radar report for three consecutive years. This year we hit it out of the park to be recognized as one of the only two Outperformers, among 30 other very respectable contenders” said Shailesh Manjrekar, CloudFabrix. He further asserted” This is a testimony to our team’s vision, and has demonstrated our ability to consistently innovate and execute, year over year for this Experience Economy”.

About CloudFabrix™

CloudFabrix is the leading Data-centric AIOps Platform vendor and the inventor of Robotic Data Automation Fabric (RDAF). RDAF delivers integrated, enriched and actionable data pipelines to operational and analytical systems. RDAF unifies Observability, AIOps, and Automation for Operational Systems and enriches analytical systems. CloudFabrix empowers Business and IT leaders with AI-powered actionable intelligence to make faster and better decisions and accelerate IT planning and Autonomous operations. For more information, visit

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