2015年3月4日
By 1月时特约编辑
专题文章

Buyer's Guide to Cloud-Based Video 编码和 Transcoding 2015

云编码有两个截然不同的市场:视频点播(VOD)和直播. I’ll address them individually in that order.

VOD的云编码

让我们首先简要介绍一下应该考虑VOD云编码的组织. 对于很多组织来说, 以前对云编码最大的反对——上传时间——可能不再是一个问题. 具体地说, 如果您正在生成多个自适应包以从云交付, 上传单个文件并在云中创建包可能更有效, as opposed to encoding locally 和 uploading the resulting streams.

在这个动态之外, if you’re encoding third-party files uploaded to you, as in a user-generated content scenario, cloud encoding is a natural. 同样，如果您的编码需求是小容量和/或零星的，那么为什么要投资编码硬件呢, 软件, 和 expertise if it’s not important to your business? At the other end of the spectrum, 如果你有基本一致的编码需求，只有偶尔的高峰, you should consider the cloud for these overages.

话虽如此, no matter what business you’re in, the benefits of cloud encoding are so compelling, that the next time you face a major encoding purchase decision, you should strongly consider a cloud solution. 以下是您在选择供应商时应该考虑的关键问题.

从清单开始

高效选拔过程的第一步是淘汰那些根本不符合你需求的候选人, so start with the hard questions. 要做到这一点, 创建一个列表，列出你要上传的所有格式和你要上传的输入位置. Then list all the output formats you’ll need, as well as the delivery locations 和 any related requirements. 要特别注意数字版权管理(DRM)和字幕, which smaller or newer cloud vendors generally don’t support.

Be as specific as possible about the other items on the list. 例如，尽早确保你的候选人支持你将要使用的格式. 如果您希望从监视文件夹或S3存储桶上传，也请勾选. 如果您需要交付到CDN或Amazon Web Services S3 bucket，也要检查. 最值得注意的是，许多编码服务都是云平台的附属服务 Amazon’s Elastic Transcoder, have significant limitations in all these areas.

积分吗??

一旦您淘汰了无法完成工作的供应商，就该考虑集成了. 具体地说, if cloud encoding will supplement existing on-prem encoding, 启动和正在进行的操作将是最容易的，如果你有一个单一的控制点，可以使用相同的预设. Multiple vendors, including 电影《百家乐app下载》英文名和 Telestream, provide both of these features. 此外, 谐波 offers ProMedia Carbon as a 软件 product, as a cloud-based service in the AWS Marketplace, 并通过编码.com with integrated control 和 shared presets. If you’re encoding locally now but are looking to the cloud, see if your on-prem provider has a cloud offering.

WHAT’S THE OPERATIONAL PARADIGM?

有四种主要的云编码模型，每种都有自己的优点和缺点:

Software as a Service (SaaS): You upload your files into the cloud 和 pay based on usage. 您没有资本支出或内部运营支出，并且需要最少的编码专业知识. 该服务负责根据需要分配额外的cpu，以便为所有客户提供足够的性能, but no customer has dedicated CPUs.
Platform as a Service (PaaS)您每月租用一定数量的cpu，所有cpu都专门用于您的操作. When you press the Go button, the files start to encode. 除了每月的费用，您还需要支付每月消耗的CPU小时数.
私有云SaaS: 您可以像访问云SaaS一样访问服务，但操作是在专有硬件上运行的. 这可以带来出色的性能，但可能会限制公司的可扩展性.
卷你自己的: 您租用云硬件，并在云中安装和管理编码器. You save CAPEX on the hardware, 但是必须买, 安装, 和 maintain the 软件, 和 supply the encoding expertise. 你会得到速溶的, dedicated access to the cloud when needed, 但可伸缩性有限，因为您负责提供额外的云实例和软件.

澄清一下, 在某些情况下, these definitions present distinctions without a difference, particularly between SaaS 和 PaaS. 一些SaaS提供商显然为包括MTV和Funny or Die在内的客户提供了较短的排队时间和有竞争力的编码时间. Where PaaS vendors contractually deliver instant access to encoding, 云的近乎无限的可伸缩性确保了SaaS供应商提供几乎相同的访问.

它可用吗??

确保操作范例适合您的专业水平和期望的操作模式. 小容量编码器可能希望在云界面中创建预设，并手动或通过手表文件夹上传文件——并非所有云供应商都支持这一点. At the other end of the spectrum, high-volume users need an API for automated operation 和 reporting. 如果你在这门课上, 让您的程序员尽早查看API文档，了解它是否满足您的需求，并估计实现和支持集成的容易程度.

质量怎么样??

所有编码供应商, 云和其他, claim superior quality; perhaps it’s in their DNA, or maybe they just assume it’s expected. 然而，我跑了 multiple qualitative comparisons of cloud encoding vendors, 和 the differences have been minimal. 在逻辑上, this makes sense; many cloud vendors use the x264 codec, which is well-documented 和 mature, so the output quality should be similar among all implementations. Other vendors—such as 电影《百家乐app下载》英文名, which has its own H.264 codec—have been competing with x264 和 other H.264 codecs for years, 和 have achieved similar quality. 所以，一般来说，除非你的测试显示相反，否则我会忽略所有质量声明.

One recent claim that I haven’t yet tested is the QuickFire.电视的 claim of 30 percent better quality at the same file size. 很明显, higher quality is always better, but I would verify these claims before making a buying decision.

演出怎么样??

在我进行的各种试验中，我确实发现了显著的性能差异, 虽然在某种程度上, performance can relate to the operational paradigm of each service. 这是, 使用PaaS时，如果为编码任务分配单个CPU，您将得到一组结果, 但是，如果您分配10个cpu，并让它们在启动作业时处于旋转状态，那么结果就完全不同了. 再次,QuickFire.TV owes its results to running on its own hardware in a private cloud.

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