Building advanced analytics into a Modern Software Factory

How CA is Fast-Tracking the Process with CA Jarvis

Digital natives like Amazon, Google and Facebook know the power of data. Whether identifying predictive insights, prescriptive actions or, ultimately, mind-blowing customer experiences, data is increasingly the fuel that drives competitive differentiation and marketplace success. And we’re in the early stages of an artificial intelligence and machine learning revolution that’s rising from an advanced analytics foundation.

But if you’re not a digital native, where do you begin?

For many companies, the first step in retooling is exposing the myriad data assets available, from existing transactional data to currently untapped operational data (aka dark data) to the online data that was previously thought of as inconsequential (aka data exhaust).

This is a challenge that we confronted at CA. Rather than having individual teams investigate the many rapidly-evolving tools and architectures – continually reinventing the wheel – we took a systematic approach enabling all product lines to accelerate their “analytics-driven” goals.

A team exploring the use of advanced analytics to prevent malicious bot attacks as part of the CA Accelerator program created a comprehensive, real-time analytics stack, which is known today as CA Jarvis. With some additional research and tooling, Jarvis is now CA’s analytics platform that uses best of breed open-source tools like Spark, Kafka and Elasticsearch and architectures like Lambda and microservices to expose data to function-specific algorithms and data science in our offerings. Products expose real-time visibility and insights by applying the latest data science and machine learning techniques to large, diverse data sets in a seamless way.

The target audience for Jarvis is developers, data analysts and product managers who have existing use cases but are stuck behind the logjam of decisions that come with building analytics-driven applications. With Jarvis, they can quickly deploy new capabilities while leaving the execution details to the underlying technology via Jarvis.

Importantly, teams are not required to choose CA Jarvis for their needs – they may choose to go their own way – but the early results confirm that product teams see overwhelming value in the Jarvis platform approach. To date, offerings across the Agile Operations, API Management and Security product lines have adopted Jarvis for their needs, with several more in progress.

And as analytics technology changes, product teams continue to benefit as Jarvis incorporates the best additions by swapping in more advanced tools as they become available and demonstrate enterprise-class reliability.

The time gained by choosing Jarvis ensures product teams focus on delivering maximum value to customers rather than having to become experts on underlying analytics tools and the latest trends.

In short, they spend their time building solutions, not infrastructure.


Attending CA World?  Visit CA Jarvis in the Accelerator Zone.

David McNierney
David is an enterprise software veteran who has held a variety of roles ranging from…


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