广播公司的云迁移入门
T他的文章提供了一个入门 how a traditional broadcaster could start to move services to a cloud provider. I spoke with an engineer from a government-owned European television station and subscription service who agreed to walk us through the process without direct attribution.
“We’ve created what you call the common cloud platform team that sets up the environment and related services to deploy a cloud instance,工程师说。. This team makes sure there’s tooling to deploy new code 和服务. It is responsible for security and scaling, so not every single team has to do the same work to learn the most effective way to scale.
Working in a cloud environment requires a shift in how workflows are used and provisioned. Essentially, you’re setting up a CPU (and/or a GPU) and assigning work to it. A common mistake for someone transitioning to cloud services is forgetting to turn the service off 在使用后. Service limits with a ceiling can prevent something that is badly configured from running up an unexpectedly large bill that shows up 30 days later.
“在云工作流程中, you have to be more explicit about permissions and firewall rules,工程师说。. “It also requires you to understand your workloads, such as how many CPUs you are going to use to run something, 你需要多大的存储空间, and how many viewers you’re expecting to stream to.”
A request to move workflow to the cloud could stem from a number of requirements: to transition from CapEx to OpEx, 提供冗余, to transition end-of-life on-prem applications, or to support a specific sporting event that’s expected to be very popular.
进行供应商
One of the inevitable questions that arise in cloud migration is build, buy, or both?
“有很多领域, 如果你从外部供应商那里购买, you have to do a lot of work yourself if you aren’t lucky enough that they’ve done the work for you. Some have absolutely, but it’s a minority at the moment,” says our engineer. “当我们开始的时候, we looked at switching on vendors for some of our stream 基础设施 that we wanted to run live. 我们是
replacing all our live apps in the live stream and wanted a vendor that supported multi-
时间冲. 事实证明这很难.”
The engineer outlined a couple of things to keep in mind when choosing vendors:
- Make sure you find vendors that actually know the cloud and have written the application to be cloud-native (and we’re not even looking yet at multi-cloud).
- Understand the performance of cloud virtual machines or cloud storage, and understand how it impacts the product and performance.
Cost isn’t really a barrier, the engineer says; it’s more of a change to thinking in a consumption-
based way: “The cloud is kind of nebulous to the C-suite. You’re not buying a physical thing, and some people tend to view that as a risk. The benefits of scale are what we’ve primarily focused on here. There are other benefits, like security and redundancy, that we can discuss in the future.”
How do you find the exact balance in which you provision enough services so you don’t come up short, 但是你也不要花太多的钱? Testing configurations should almost go without saying, but the engineer I spoke with notes that some organizations don’t recognize the need for testing and tend to proceed without it. “They expect things to work the same in the cloud as they did on-prem, and that’s not the case.”
Still, there are some deployments that won’t really benefit moving to the cloud. Something that is fairly steady and doesn’t have the need for peak use will most likely be more cost-effective on-prem.
在最近的流媒体连接活动中, 安迪海滩, CTO of media and entertainment at Microsoft, likened the difference between cloud and on-prem to “cattle and pets.” To paraphrase Beach’s analogy, cattle are part of the food chain, but you keep feeding pets. However, the challenge is that most people don’t figure out what their pets cost to keep.
If most typical broadcast media companies considering cloud migration were to figure out how much their on-prem systems cost and do a direct cost comparison, they would likely conclude that more services should run in the cloud. Odds are that those that do take the leap into cloud services won’t regret the decision from a financial perspective—at least until they forget to spin them down.
The engineer I spoke with discusses such a sporting event: “We wanted to scale to an audience we wouldn’t be able to reach with the on-premise 基础设施. Either we had to go and buy a lot more hardware, or we had to find another solution. 这就是云的由来. We’re likely to have somewhat similar peaks to other streaming services, 而是因为我们有生活, it might not be the same sort of peak we see as somebody who has mainly 视频点播.”
几个工作流程
“The first workloads we moved had the most peaks, 哪个是视频平台,工程师回忆道。. “The video platform processes the metadata about what’s available. It contains 信息 about what content is watched, 这个系列的下一个内容是什么, 如果观众想继续观看. It also has all the ways of browsing content, like news, drama, and 视频点播.”
For the authentication and access management workflow, let’s go with a cloud-based SaaS provider. Next come the consumer commercial parts, like selecting the right streaming package. 这意味着升级, 降级, or any sort of partner integration in which you get entitlements from being a customer of a cable provider. The web front end is also cloud-based now.
“Most of our streaming originates in the cloud, with the exception of our live signals from on-
premise because that’s where the TV is produced,” our source says.
Processing a piece of content scales very easily. As the streaming services have matured, they’ve licensed larger content catalogs. The engineer notes, “We’ve licensed big catalogs, run on the cloud. Some of the day-to-day encoding runs in the basement data center. 它在做
本质上是一样的, but we haven’t updated the on-prem technology, 所以我们希望逐步淘汰这种做法.
“One piece of content might take 45 minutes, but we can run hundreds of them at the same time. 我们还需要分配存储空间. 如果是内部的，我们可能会受到限制. In the cloud, we can do hundreds or thousands at a time if we wanted to.”
扩展成本
The engineer’s organization has a diverse set of offerings that includes scheduled broadcasts, 视频点播, 弹出式频道. “Many organizations haven’t had to estimate costs in the way you would in the cloud,工程师说。. “This requires an estimate of how much programming is going to be done over the next year and how many viewers are expected to watch it. That’s not something broadcasters are used to, because programming just fits into a live channel. Planning for the content that you’re going to run is pretty much spot on, but how are you going to predict whether it will be 500,000用户或550用户,000个用户?”
Scale is more challenging to predict with some events than with others. “Some things we can predict, like we know a sports event is going to be popular,工程师说。. “有些预测很难. You end up trying to make sure that you can scale under most circumstances, but that means you have to over-provision capacity, 这就增加了成本. Or you can use auto-scaling groups, which programmatically scale capacity without user involvement. I don’t think cost estimating is particularly hard, as long as you accept that you’re going to be off by 10 or 15%.” Getting more exact numbers “is almost impossible.”
Advance provisioning is key to managing scale, the engineer explains. “我们将提前开始供应, and if it’s something hitting our resource allocation, 我们在它成为问题之前抓住它. Even if we get those settings right, it might not be the same settings that work well for others.”
Other things to plan for include the following:
- 数据传输成本
亚马逊网络服务 - 你的CDN缓存有多有效
“I think it’s probably easier for me to understand the cost of the cloud because everything has a price,工程师说。. “I can model my workloads and how much data transfer and how many CPUs I’m going to use.”
其他需要关注的事情:
- CPU和GPU是什么样的
这是你所需要的 - 你需要多大的存储空间
你需要多容易访问它 - 当你的
服务已关闭
“I don’t see people doing the same cost estimation f或在-premise,工程师说。. “Very rarely do you have an internal price for what it costs to actually run workloads on-premise. What usually happens is that people plan and buy X number of servers, 把它们放在架子上, and then we have a bill for electricity over time. But that doesn’t tell you the cost of your workloads. 它告诉你服务器的成本. You’re not actually pricing your workloads because your workloads take up only 10% of what you’re using there.”
Nadine Krefetz has a consulting background providing project and program management for many of the areas she writes about. She also does competitive analysis and technical marketing focused on the streaming industry. Half of her brain is unstructured data, and the other half is structured data. 可以联系到她 nadinek@realitysoftware.com 或在 LinkedIn.
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