CloudFabrix Strengthens Platform with Variety of AIOps and Observability Enhancements

CloudFabrix, a leading AIOps software vendor, is making upgrades to its AIOps and Observability platforms, accelerating AIOps adoption by filling IT visibility gaps, simplifying and automating data preparation and integrations, eliminating re-tooling and by driving business/IT outcomes.

Additionally, AIOps evaluations and proof of concept (POC) projects can be implemented in a matter of just days and weeks with the company's newly announced POC Express offer, according to the vendor.

With AIOps 2.0, CloudFabrix is advancing AIOps to overcome these challenges so customers can easily embrace AIOps, achieve faster ROI and realize its true potential and benefits.

Enterprises are still struggling with IT visibility gaps in their dynamic and ever-expanding multi-cloud hybrid environments. Success of AIOps projects hinges on the quality and completeness of data that is available for AIOps to analyze.

CloudFabrix Observability-in-a-Box was squarely designed to fill these gaps, by providing a unified solution to continuously monitor, collect and send metrics, logs and traces, as a unified dataset to its AIOps solution.

Additionally, the solution provides Artificial Intelligence (AI) inferencing at the edge, enabling dynamic alert thresholds, predictive alerting, anomaly detection, baselining and more. The solution has a minimal footprint and can be run in just one VM using a Docker-based microservices environment.

AIOps Radar view accelerates root cause analysis (RCA) by collecting all contextual data and analyzing it for anomalies and correlation to expedite root cause analysis.

It then surfaces the root cause, noticeable data points and important changes that point to a root cause to help narrow the scope of investigation.

Business, service and IT operational outcomes can be tracked by continuously collecting service metrics with full-stack data and correlating it with the health and performance of the underlying technology stack.

With CFXDX, AIOps implementation times can be cut in half, enabled by rapid development of new data integrations, reusable and modular data flow pipelines and interoperability with the rest of the IT ecosystem (i.e., Data Lake/Ticketing/BI Tools/RPA). CFXDX accelerated data integration implementation in many advanced use cases like e-bonding, and CMDB synchronization and incident NLP classification using OpenAI/GPT-3.

A key pain point of AIOps has been lengthy proof of concept (POC) and pilot projects. With AIOps POC Express, POC projects can be completed in a matter of days to weeks, instead of several months. Results can be presented based on historical and offline data, without having to perform tool deployments and live integrations with production tools. Customers can provide historical incident data and alert data (optional) and identify primary sources of alert noise generation, identify blind spots and establish potential ticket volume reduction that can be achieved with AIOps.

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