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In the last article in this series, we looked at why integrated monitoring is a necessity in modern broadcast IP workflows. In this article, we dig deeper to understand what is new in IP monitoring and how this integrates with traditional workflows.
Television ratings service Nielsen recently released a report that showed streaming platforms pulled in a bigger share of viewers’ time then broadcast networks did. In fact, Netflix and YouTube alone now make up about 12 percent of the time Americans spend in front of their TVs.
Optimization gained from transitioning to the cloud isn’t just about saving money, it also embraces improving reliability, enhancing agility and responsiveness, and providing better visibility into overall operations.
Video, audio and metadata monitoring in the IP domain requires different parameter checking than is typically available from the mainstream monitoring tools found in IT. The contents of the data payload is less predictable and packet distribution more tightly defined leading to the need to use specialist media stream centric monitoring tools.
In the previous article in this two-part series we looked at how cloud systems are empowering storytellers to convey their message and communicate with viewers. In this article we investigate further the advantages for production and creative teams.
The focus of much of the latest broadcast TV R&D is the Remote Integration Model (REMI). From millions of Skype meetings over consumer ISPs to the recent Winter Olympics TV broadcasts, REMI is significantly changing the internal dynamics of live, between-the-glass, remote TV production and viewing.
Television is still a niche industry, but nonetheless, one of the most powerful storytelling mediums in existence. Whether reporting news events, delivering educational seminars, or product reviews, television still outperforms all other mediums in terms of its ability to communicate to mass audiences.
In the last article in this series, we looked at how PTP V2.1 has improved security. In this part, we investigate how robustness and monitoring is further improved to provide resilient and accurate network timing.