Close
Close

Published

Amdocs aligns with AT&T open source, with ONAP and Acumos moves

Amdocs is seeking to reinvent itself as an open source integrator, and is relying heavily on aligning with AT&T’s own open platform initiatives.

The software vendor worked with AT&T on ECOMP, the management and orchestration platform which is now the basis of the would-be open standard, ONAP (Open Network Automation Protocol). It has talked about the growth opportunities from projects to help operators deploy and integrate ONAP-based systems.

At the Open Networking Summit last week, Amdocs announced that it had worked with Microsoft to enable ONAP on the Microsoft Azure cloud platform, and will open source that code next month. That will help MNOs to support virtual network services running on Azure, orchestrated and managed with ONAP.

“This project is a first step in the evolution of ONAP to manage a multi-cloud environment where network capacity can be consumed in a dynamic way across a combination of private and public clouds,” said Anthony Goonetilleke, group president of Amdocs Technology.

Yousef Khalidi, corporate VP for Azure networking at Microsoft, added: “Today’s next generation operators are challenged by the complexity and cost of developing their existing network infrastructures and require new cloud services to enable faster network virtualization. To address these issues, Amdocs and Microsoft are using ONAP to control network services on Microsoft Azure.”

Meanwhile, Amdocs has joined another AT&T-initiated open source project, Acumos AI, as a founding member. The Linux Foundation-hosted project addresses AI model discovery, development and sharing, especially in content and media sectors. The group aims to establish a common platform for the exchange of machine learning solutions, while making AI more accessible to all companies.

Amdocs said it will contribute knowledge of AI data, mapping and data tools from a customer experience, network and media standpoint.

AT&T announced in November that it was working with Indian integrator Tech Mahindra to build Acumos, with the aim of making it cheaper and simpler for operators to deploy and share AI applications, via a marketplace system. That could accelerate the uptake of AI-driven telco processes, from network planning and optimization, to consumer services; and it will also reduce the power of the major AI platform providers.

Acumos is an extensible framework for AI and machine learning (ML) solutions, built on open source technologies and running on AT&T Indigo. It can federate across various AI tools available today (for instance connecting two microservices derived from Google and Amazon). It allows those AI microservices to be edited, integrated, packaged, trained and deployed and they can then be accessed from the marketplace, and chained to create more complex services.

As AT&T is getting Acumos into the open source process at an earlier stage than it did ECOMP, it should benefit more quickly from innovations coming from a wide community.

“We’re opening up AI,” said Mazin Gilbert, VP of advanced technology at AT&T Labs, at the launch. “We’re focusing on the telecommunication, media and technology spaces, starting with the network. The platform will be available to anyone and the more users who adopt it, the better it will get.”

He added: “The problem – which is why we started this – is we have tens of these applications. Each of them is a different technology, different tool, different set of people, different vendor, different partner, even a different team inside AT&T. How do we go from tens to thousands? The answer is that we can’t, it’s cost-prohibitive. Acumos helps to stitch together the outputs of many of the great AI tools in the industry so they’re Legos, not snowflakes.”

Tech Mahindra will work with enterprises to help them apply the AI services and tap into intelligent telecoms connectivity to enable new use cases. The firm’s SVP and strategic business unit head, Raman Abrol, said: “Our ultimate goal with the Acumos Project is to accelerate and industrialize the deployment of AI at enterprises and get developers and businesses to collaborate effectively in order to improve how we all live, work and play.”

Close