CloudFabrix comes to associate observability and AIOps

Specializing in application analytics and intelligence, start-up CloudFabrix provides IT managers and operations personnel with insights into how applications are performing across layers and domains. A kind of combination of observability, AIOps and automation.

Based in Pleasanton, Calif., the team behind CloudFabrix has the distinction of having launched several start-ups in recent years, three of which (Cloupia, Pari Networks and Jahi Networks) were previously acquired by Cisco. Founded in 2015 by Raju Datla (CEO), Raju Penmetsa (CTO), Bhaskar Krishnamsetty (CPO) and Satyan Raju (CDO), CloudFabrix is ​​at the origin of the concept called Robotic Data Automation Fabric (RDAF), which aims to respond to a problem particular in companies: the preparation of data before its exploitation with analytical tools. Due to the increasing complexity and volume of data pipelines, real-time acquisition, cleaning, contextualization and statistical analysis have become difficult to achieve with manual means. However, a cohort of technologies has emerged to operationalize this data flow automation in AIOps mode.

The Cloudfabrix team has already created and sold three start-ups to Cisco. (SL credit)

“We offer a turnkey, data-centric AI operations platform […] This is the vision we started to develop in 2015 [lors de la création de CloudFabrix]. Of course, in 2018 Gartner coined this term AIOps and now that’s what it’s called,” said Shailesh Manjrekar, CMO of CloudFabrix, during an IT Press Tour in Silicon Valley. “Doing an AI project on a small POC is one thing, making it operational at scale in a real-world example isn’t so great, and that’s the opportunity we saw with CloudFabrix. How can we use AI to improve AI? operationalization of data pipelines? In its trade, the start-up calls it RDA, Robotic Data Automation, a platform capable of automating the flow of data from disparate sources. A mode of operation close to RPA, but RDA combines bots from low code supported by artificial intelligence to automate the processes of collecting, cleaning, validating, extracting, metadata enrichment, processing and data integration. Rather than replacing traditional ETL and ELT systems, RDA complements them by improving access and sharing of data in distributed environments. As it increases the availability and quality of data for all forms of business applications, when combined with RPA and automation, RDA proves to be a very powerful automation tool. powerful.

Available locally or in the cloud, the CloudFabrix platform is based on microservices. (SL credit)

Big data and machine learning

RDA is often associated with AIOps, the combination of big data and machine learning to automate data analysis operations. With its RDAF platform, CloudFabrix unifies observability, AIOps, and automation. “You can automate core AIOps activities such as data metadata discovery, data quality analysis, data enrichment, data integration, incident remediation, and more,” says start.

“Observability is a very rich field. The typical client has between 5 and 10 observability tools, and the result is that it becomes a kind of tsunami with a multitude of warning noises. Then it’s about finding the needle in the haystack. So this is the challenge of observability security, and also of your SIM, you can’t configure everything with a simple Zero Trust environment”, explains CloudFabrix’s marketing manager.

With its bots, CloudFabrix helps IT managers and operations staff resolve IS issues very quickly. (SL credit)

Cloudfabrix’s RDAF platform is built on microservices, which means everything can be deployed on-premises or in hybrid mode, with a control plane in the cloud and data remaining on-premises to meet regulations like GDPR. The startup calls this mode of operation distributed data, that is, no type of data leaves the customer’s datacenter. The CloudFabrix solution can also be deployed on AWS – it is present on the AWS Marketplace – and runs on EC2 or serverless instances. And since the solution is based on microservices, it can also be installed on any Kubernetes distribution. The RDAF platform is, in fact, aimed at four challenges, namely data integration with the use of 1,000 bots to interface with Kafka, for example. The second concerns the problem of data quality. You need pipelines that can take data, normalize it, and enrich it. The third challenge concerns the lack of skills. Not everyone is familiar with data operations and working with Python and JavaScript. And the final challenge relates to data silos with streams coming from the edge, the point of sale, and multiple environments. How to put it all together? CloudFabrix uses its distributed data fabric.

To differentiate itself from its main competitors (DataDog, Dynatrace, LogicMonitor and PagerDuty), CloudFabrix highlights its ability to map services to differentiate applications. The startup also offers a log intelligence service for CISOs and DevOps. Then there’s composable analysis, which is the ability to mix and match any of these services – from arrays to pipelines to services – to find the cause of the malfunction.

To grow its business, CloudFabrix has established numerous partnerships with publishers and distributors. (SL credit)

To market its platform, CloudFabrix has entered into strategic partnerships with Cisco, DXC, HPE and IBM. Discussions are also ongoing with Dell. “IBM and Cisco use our SDK to build their own bots,” said Shailesh Manjrekar. The start-up also works with integrators and resellers. Although CloudFabrix’s headquarters are located in Pleasanton, California, the company has subsidiaries in India and the United Kingdom. The start-up, which has already raised US$ 25 million, expects great growth in 2023. It already announces around 500 clients in fiance, hospital sector (Kaiser centers in the United States), industry (Tata in India) or consulting (Varutra) .

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