Introducing compelling services--and driving technical advancements to deliver those services--is a way of life in the telecom and networking world. Over the past 20 years alone, the networking industry has launched many exciting services, such as IPTV, Video on Demand, IMS voice and video telephony, 4G services and of course, cloud based applications like Netflix and WhatsApp.
Imagine for a second that you’re operating an industrial plant. Giant machinery enveloped by metal pipes and thickets of wire that hums along while steam billows from above. All of a sudden, it all comes to a screetching halt.
What’s the problem? How long until it’s fixed? Without visibility into the status of each critical component of your operation, it’s going to be a very long process tyring to get everything back online. Wouldn’t it be great if you had an all-seeing eye and an automatic way of resolving these issues, many before they ever happen?
Verizon recently launched its multi-services edge (MSE), with Juniper playing an instrumental role in this groundbreaking new platform. Verizon’s MSE is SDN (software-defined networking) in action: it essentially “cloudifies” the network with an overlay of software control so that Verizon can operate the network more efficiently and respond to changes in the marketplace much faster. Juniper has applied its deep software expertise to provide disaggregation, automation, and virtualization to help bring Verizon’s new network architecture to market quickly, enabling Verizon to serve the rapidly evolving needs of their customers.
Why training and culture are key to unlocking the potential of IP for media and broadcast companies? A lack of relevant skills in IP and IT is threatening to undermine broadcasters as IT, IP and increasingly data are becoming the backbone of the industry. Broadcasters need to retrain and upskill staff and create a culture of change to drive innovation.
A key issue for operators is detecting the existence of a problem within the network infrastructure in a timely way and working out how to divert traffic from the affected location. Currently this is dealt with in a manual, labor-intensive way. Doing this automatically and in a predictive manner dramatically reduces the amount of time that traffic is impacted, thus greatly improving the reliability of the service.