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Many broadcast processes are moving to the cloud, including quality control and monitoring.
We recently spoke with Paul Briscoe, Chief Architect of TAG Video System, about cloud monitoring and the company’s new media control system, which enables real-time insight and analysis across multiple deployments. .
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Our conversation has been condensed and edited for clarity.
How many of those processes that were put in place during the pandemic have now cemented themselves into your clients’ workflows?
A lot of people want to go back to real studio facilities for many kinds of productions, but they’ve also realized at the same time that they can release those productions outside in a trivial way, compared to the idea of releasing a production outside before.
You must repay the value of this studio over time. So you fill it with people all the time. If this studio disappears, you can still do a lot of programming.
Some of the palliative technologies that we saw in the very beginning, of course, are disappearing.
Is it a process evolution?
As more and more professional broadcast pieces have taken hold in the new world, we are seeing integration at a distance. We are seeing fully cloud-based live production, which continues to grow.
Even in the midst of it all, NBC decided to take this big shot at the Olympics. They had 4K and they had HDR and they had all kinds of things going on and everything just worked. These unfortunate circumstances have really done a lot for the industry in terms of getting things done.
You have to see what sticks and what evolves and it is normal for things to evolve. From the old comes many new things every time.
How is TAG adopting the cloud for its media control system?
The TAG MCM platform that we have had for years is capable of receiving just about any signal format in the IP domain. From UHD or full uncompressed HDR to OTT.
The application runs on a compute instance of a given size, which can be a physical server, it can be a cloud-equivalent compute instance, or a cloud server.
You can, in a given instance, accommodate a number of channels, depending on the formats and the amount of computation required by each. If you need more, you spawn a second instance of TAG, and the two talk to each other and work as one big instance.
When there are 20, 30 or 40, all talking to each other, it becomes very happy from a data management point of view. It becomes increasingly difficult for us to build a meaningful system when we cannot scale. So we introduced the media control system.
It’s a platform that lives as an orchestrator on top of the MCMs and while it’s not a full system orchestrator, it’s a full orchestrator for the TAG devices that live below.
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What benefits does MCS bring to MCM?
The first thing we gain is that users have a single point of user interface. We have advanced user management, we have integration with IT-based user management systems.
We provide integration via our API to other orchestration, automation and control systems. At the MCM level, we have introduced a data channel called Redis and it provides a data channel that can transport a large volume of data from the MCMs to the MCS.
It allows you to use this data with database tools and, most commonly, things like visualizations. So putting counters and charts and graphs on a screen.
Then the other thing you can do with that data is apply it to computing power. You can let AI and machine learning examine your data over time because it resides in a large database. You can keep as much or as little data as you want. You can go back and do a retrospective analysis, you can enter to check the contracts, the SLAs have been met.
We have now provided a single point of integration for an arbitrarily scaled system of TAG monitoring instances.
And it allows for mixed deployments?
You can now deploy TAG instances wherever you want geographically. A mix of in the field, on servers, in virtual machines, in a server farm or in the cloud, any combination of these, anywhere in the world.
The MCS control system will actually integrate them into a single monitoring dataset, from which you can now create end-to-end paths. Literally from the studio, to the OTT edge and at any scale and any geographic scope.
How does MCS enable rapid deployment or change of workflows?
If you are monitoring a live event, for example, from studio to satellite, cable and OTT. We can deploy more monitoring points in this ecosystem, whatever it is, topologically or geographically. Then using MCS we can correlate all of these things into a program path.
We have penalty box modes, for example, where we quietly monitor in the background. If something happens, we can take action by letting you know, whether it’s an alert or an alarm. Until throwing the image into a penalty box screen somewhere.
Now you can quickly deploy and understand this workflow, monitor it, and really visualize it as it exists.