CloudFabrix Announces AIOps 2.0 to Accelerate and Simplify AIOps Implementations at the 2021 AIOps Virtual Conference
Announced Observability & AIOps Product Capabilities
04 Feb, 2021, 08:42 ET
PLEASANTON, Calif., Feb. 4, 2021 /PRNewswire/ -- CloudFabrix, a leading AIOps software vendor, made major Observability & AIOps 2.0 announcements at its 2021 AIOps Virtual Conference. AIOps 2.0 accelerates AIOps adoption by filling IT visibility gaps, simplifying & 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 & weeks with the company's newly announced POC Express offer. AIOps Virtual Conference on-demand content can be accessed with a free registration at https://www.cloudfabrix.com/aiops-virtual-conference/
Traditional AIOps implementations were expensive and bogged down by lengthy implementations, complex data integrations, extensive retooling efforts and manual instrumentations, while solving only limited use cases. 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.
"As detailed in our DEJ research report (19 Key Areas Shaping IT Performance Markets in 2020), we see almost a 3x increase in the number of top performing organizations that have AIOps as their budget item," says Bojan Simic, founder DEJ, and also a keynote speaker at the conference. "Enterprises have a lot of hope and expectation from AIOps and we are at a critical juncture where AIOps projects need to be made easy to evaluate & implement. CloudFabrix AIOps 2.0 innovations and announcements are a huge leap in this direction."
Key New Product Announcements:
Observability-in-a-Box & Edge AI: 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 & 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.
"By 2025, 50% of new cloud-native application monitoring will use open-source instrumentation instead of vendor-specific agents for improved interoperability up from 5% in 2019," says Gartner. Observability-in-a-Box leverages open-source technologies and open telemetry instrumentation that provide great flexibility and investment protection to switch to any analytics software in the future. The solution can be deployed in a branch, edge, data center or in the cloud within minutes. Learn more: https://www.cloudfabrix.com/observability/
AIOps Radar View - Bird's eye view of real-time Application or Outcome performance: This new feature provides two key capabilities
1) 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.
2) Track performance of Outcomes: 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.
CFXDX - Modern Data Preparation & Integration Automation:
IT operations data is generated by many structured and unstructured sources and tools, spread across different domains and environments. This poses a continuous challenge for AIOps implementations to efficiently acquire and ingest data while also integrating with complementary tools within the IT ecosystem. 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. Learn more: https://www.cloudfabrix.com/cfxdx/
AIOps POC Express: 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. Customers and partners can sign up for POC Express here: https://www.cloudfabrix.com/poc-express/request-poc-express
- AIOps 2.0 –https://www.cloudfabrix.com/aiops-solution/
- AIOps Virtual Conference On-Demand Content - https://www.cloudfabrix.com/aiops-virtual-conference/
CloudFabrix is the provider of the AIOps and Observability platform that scales and accelerates digital IT lifecycle planning and autonomous IT operations. CloudFabrix simplifies and unifies IT operations and governance of both traditional and modern applications across multi-cloud environments by using its AIOps suite of Apps. CloudFabrix empowers IT leaders and operations personnel with actionable intelligence to make faster and better decisions. CloudFabrix is headquartered in Pleasanton, CA, USA with branch offices in India and the United Kingdom.
SOURCE CloudFabrix Software
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