The Transformation Transcoding

Logs and Partial Job Submissions
Once the workflow is run and the files are distributed, all transcoding systems will generate log files. Some solutions offer an easy way to parse these log files into CSV or other manipulable reports, gathering information from the database and presenting it in a report format. Others are stuck in a mode where the log files are XML only-great for integrating into a third-party billing solution but not so easy for the average user to gather data from.

All GUI-based systems that were tested, though, have the ability to visually alert the user to particular failures, whether at the analysis, transcoding, or distribution step. Vantage, announced at NAB and now shipping, also has the ability to restart
a failed job that has been identified in the middle of an otherwise complete workflow: should only one transcode in a multiple transcode scenario fail, a user can restart just that one transcode, without having to run the entire job again.

CPU Tax
When it comes to scaling up transcoding resources, one consistent finding in all tests was that adding an additional transcoding node did not double the throughput, nor did adding two nodes triple the throughput. This was more apparent with short content durations; as content lengths moved out beyond 5 minutes, though, the majority of solutions were able to use raw computing power to reach a break-even point at which content was then transcoded in real time for almost all of the multiple outputs.

Several solutions have been proposed to scale enterprise- and carrier-class transcoding products to a point where all content is generated in faster-than-real-time transcoding. These solutions involve ways to eliminate the heavy "CPU tax" from overhead processes inherent to general purpose operating systems, and they hold promise for a linear upswing in throughput on purpose-built transcoding systems.

Enterprise Transcoding Meets Cloud Computing
So what's next in transcoding? For readers with current needs, the decision points seem to centre on the impact of transrating and protocol conversion on your unique transcoding workflows. I'll cover transrating in a future article because it has significant implications for the transcoding process. But knowing upfront what delivery protocols you need will help simplify overall transcoding workflows, especially if the majority of your content delivery is H.264 in an MP4 container format.

Once the report is complete and published, we plan to turn our attention to web-based (also called cloud-based) transcoding solutions, to see how they compare to enterprise solutions and the emerging specialised media operating system noted above.

While we've not yet done testing on these SaaS solutions, our preliminary reviews indicate that they appear to hold promise, even with the heavy CPU tax that most SaaS solutions incur.

The idea of transcoding via the web is not new, but recent advances have seen the elimination of a long-standing bottleneck: long upload times negating the benefits of faster transcoding across tens or hundreds of CPUs. Now, instead of the incremental increases in speed for transcoding a single file to a single format, SaaS transcoding service providers take advantage of mass-scale computing to generate the 10-20 simultaneous outputs.

In a recent press release, one company claims to have performed 4,500 video encodes at 100Mbps, each in a 20-minute period using 900 processors. Another company claims it is transcoding more than 1 million video files per month, with an average of seven outputs per video file. Yet another is claiming it is transcoding millions of video files per month.

The misconception of SaaS solutions, driven partly by the way cloud encoding platforms are pitched, leaves the impression that an enterprise should immediately shift all its processes and workflows to the cloud. In reality, our initial review of real-world workflow processes indicates that SaaS solutions are best optimised when they integrate with existing enterprise applications, processes and workflows.

Taking advantage of local processing for some steps while relying on massive processing for other steps allows a user to gain the best of both approaches to transcoding and enterprises are not forced to decide between cloud-only and existing enterprise solutions.

This isn't to say SaaS has no potential, just that it has a way to go to reach the robustness of enterprise solutions necessary for comparative testing. There is hope, though, within the derivative of SaaS solutions known as online video platforms (OVPs), which transcode and deliver within the same integrated platform.

As such, our game plan is to invite mature SaaS and OVPs to a comparative test of their own shortly after IBC, followed by an early 2011 round of testing that compares hybrid cloud-enterprise solutions against online-only solutions. The results from our current enterprise-class transcoding comparison tests will serve as a baseline for quality, speed and workflow integration. Sounds like quite a bit more time under the hood, providing a much-needed comparison service for users of key transcoding solutions.

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