Key findings from Heavy Reading's third Open, Automated, & Programmable Transport Networks operator survey highlight the importance of automating the optical layer and exploring the potential of generative AI in transport.
Sponsored by Nokia
Optical networks are integral to IP and optical convergence. Yet, the optical network also operates on its own — as it has for decades — underpinning all types of transport, supporting internal traffic flows and delivering high capacity services directly to wholesale and enterprise customers. A successful transport automation strategy must include the optical network.
As part of its third annual Open, Automated, and Programmable Transport Networks global operator survey, Heavy Reading delved into operators' views on the benefits of transport automation. This blog looks at automation for the optical layer and touches on the potential of generative AI in transport.
On the customer-facing side, network as a service (NaaS) is a hot topic for network operators, as evidenced by conferences dedicated to this topic, such as MEF's Global NaaS Event (GNE). It is also an area where network automation is applied to help generate new revenue streams. Industry forum MEF defines NaaS as the combination of on-demand connectivity, application assurance, cybersecurity and multicloud networking within a standards-based automated ecosystem. Optical networks can play a key role in high bandwidth NaaS applications, such as connecting data centers, supporting multicloud architectures or enabling content delivery networks.
Heavy Reading's survey results indicate that virtualizing network services/locations to support NaaS is at least "important" for 63% of operators surveyed. 17% of operators see the virtualization of network services or locations as "critical."
How important is it to fully virtualize optical network services/locations and execute automated path computation to deliver and realize network as a service?
Reliability is another essential metric for CSPs — across both internal and customer-facing services — and another area where automation is crucial. In last year's survey, operators identified reducing human error and increasing reliability as the top two drivers for transport automation. At the optical layer, operators surveyed this year believe that an automated service activation test for wavelengths is important, with 74% of operators surveyed responding that automating service activation testing is at least "important." For 22% of operators surveyed, these tests are "critical." Just 9% believe automated service activation tests are just "somewhat important" or "not important" at all.
Parsing the data further, Heavy Reading found that the smallest operators (<$50m) place a slightly lower importance on automated tests than larger operators. Large operators have complex networks and services with many touchpoints and risks for introducing errors, thus making automated testing more impactful as operator size increases. Also, smaller operators often do not have the resources to invest in emerging technologies like automation. Heavy Reading expects some lag before automation technology matures and is more widely adopted by smaller operators.
How important is it to automate service activation tests for optical wavelengths prior to service creation?
Lastly, this blog touches on today's megatrend: generative AI. Clearly, generative AI holds tremendous long-term potential for virtually every industry, including telecommunications. But in the limited context of AI to support transport networks, generative AI has not been a major priority to date and has garnered little public attention.
Heavy Reading wanted to better understand which generative AI capabilities are most important for transport automation. Generative AI use cases in transport include providing reporting intelligence of network KPIs, assisting with troubleshooting, performing capacity planning, generating on-demand reports using natural language inputs and sorting through product documentation, among others.
Which generative AI capabilities do you want to adopt for transport automation within the next two years? (Select all that apply)
Heavy Reading asked operators to weigh in on the five use cases shown in the figure above and found that all resonate strongly with operators at this early stage. Providing reporting intelligence of KPIs and assisting with troubleshooting top the list of options (each selected by 55% of respondents), but all five capabilities are of high interest based on the survey results.
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This blog is sponsored by Nokia.
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