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Tina Popielarczyk
I pulled this chapter together from dozens of sources that were at times somewhat contradictory. Facts on the ground change over time and depend who is telling the story and what audience they're addressing. I tried to create as coherent a narrative as I could. If there are any errors I'd be more than happy to fix them. Keep in mind this article is not a technical deep dive. It's a big picture type article. For example, I don't mention the word microservice even once :-)
Given our discussion in the What is Cloud Computing? chapter, you might expect Netflix to serve video using AWS. Press play in a Netflix application and video stored in S3 would be streamed from S3, over the internet, directly to your device.
Another relevant factoid is Netflix is subscription based. Members pay Netflix monthly and can cancel at any time. When you press play to chill on Netflix, it had better work. Unhappy members unsubscribe.
The client is the user interface on any device used to browse and play Netflix videos. It could be an app on your iPhone, a website on your desktop computer, or even an app on your Smart TV. Netflix controls each and every client for each and every device.
Everything that happens before you hit play happens in the backend, which runs in AWS. That includes things like preparing all new incoming video and handling requests from all apps, websites, TVs, and other devices.
In 2007 Netflix introduced their streaming video-on-demand service that allowed subscribers to stream television series and films via the Netflix website on personal computers, or the Netflix software on a variety of supported platforms, including smartphones and tablets, digital media players, video game consoles, and smart TVs.
Netflix succeeded. Netflix certainly executed well, but they were late to the game, and that helped them. By 2007 the internet was fast enough and cheap enough to support streaming video services. That was never the case before. The addition of fast, low-cost mobile bandwidth and the introduction of powerful mobile devices like smart phones and tablets, has made it easier and cheaper for anyone to stream video at any time from anywhere. Timing is everything.
Building out a datacenter is a lot of work. Ordering equipment takes a long time. Installing and getting all the equipment working takes a long time. And as soon they got everything working they would run out of capacity, and the whole process had to start over again.
The long lead times for equipment forced Netflix to adopt what is known as a vertical scaling strategy. Netflix made big programs that ran on big computers. This approach is called building a monolith. One program did everything.
What Netflix was good at was delivering video to their members. Netflix would rather concentrate on getting better at delivering video rather than getting better at building datacenters. Building datacenters was not a competitive advantage for Netflix, delivering video is.
It took more than eight years for Netflix to complete the process of moving from their own datacenters to AWS. During that period Netflix grew its number of streaming customers eightfold. Netflix now runs on several hundred thousand EC2 instances.
The advantage of having three regions is that any one region can fail, and the other regions will step in handle all the members in the failed region. When a region fails, Netflix calls this evacuating a region.
The header image is meant to intrigue you, to draw you into selecting a video. The idea is the more compelling the header image, the more likely you are to watch a video. And the more videos you watch, the less likely you are to unsubscribe from Netflix.
The first thing Netflix does is spend a lot of time validating the video. It looks for digital artifacts, color changes, or missing frames that may have been caused by previous transcoding attempts or data transmission problems.
A pipeline is simply a series of steps data is put through to make it ready for use, much like an assembly line in a factory. More than 70 different pieces of software have a hand in creating every video.
The idea behind a CDN is simple: put video as close as possible to users by spreading computers throughout the world. When a user wants to watch a video, find the nearest computer with the video on it and stream to the device from there.
In 2007, when Netflix debuted its new streaming service, it had 36 million members in 50 countries, watching more than a billion hours of video each month, streaming multiple terabits of content per second.
At the same time, Netflix was also devoting a lot of effort into all the AWS services we talked about earlier. Netflix calls the services in AWS its control plane. Control plane is a telecommunications term identifying the part of the system that controls everything else. In your body, your brain is the control plane; it controls everything else.
In 2011, Netflix realized at its scale it needed a dedicated CDN solution to maximize network efficiency. Video distribution is a core competency for Netflix and could be a huge competitive advantage.
The number of OCAs on a site depends on how reliable Netflix wants the site to be, the amount of Netflix traffic (bandwidth) that is delivered from that site, and the percentage of traffic a site allows to be streamed.
Within a location, a popular video like House of Cards is copied to many different OCAs. The more popular a video, the more servers it will be copied to. Why? If there was only one copy of a very popular video, streaming the video to members would overwhelm the server. As they say, many hands make light work.
Right now, up to 100% of Netflix content is being served from within ISP networks. This reduces costs by relieving internet congestion for ISPs. At the same time, Netflix members experience a high-quality viewing experience. And network performance improves for everyone.
What may not be immediately obvious is that the OCAs are independent of each other. OCAs act as self-sufficient video-serving archipelagos. Members streaming from one OCA are not affected when other OCAs fail.
While watching a netflix video on a Netflix site, my goal is to have a userscript invoke the playback controls programmatically. Specifically, the volume, level, play/pause state, and time position of the video.
I've been able to manipulate the html5 video element itself, but controlling that directly does not provide the needed netflix control bar feedback to the user. (i.e. video is paused, but the control bar still shows it as playing).
My approach thus far has been to try and locate the elements that represent the "buttons" you click when using the normal controls, and trigger their click events through the userscript. But I can't seem to isolate the proper elements. Additionally netflix is using a javascript compressor/obfuscator which increases the difficulty of finding the proper elements that represent the buttons on the control bar.
The console.log statements are showing some of the things I've found so far. But I haven't figured out how to invoke functions off them, or which of them might have what I'm looking for (I think largely due to the javascript compressor making it difficult for me to follow the code).
You can then use the API to perform various commands on the Netflix player, such as seeking (by using player.seek() with the number of milliseconds in the parentheses), playing or pausing the video (by using player.play() or player.pause() respectively), or controlling the volume (by using player.setVolume() with the value in the parentheses, with 1 being 100 percent and 0 being 0 percent).
So, for example, to get the "button" that controls play and pause, you could use: document.getElementsByClassName("player-control-button player-play-pause")[0]. Then to click it programmatically in tampermonkey, you simply invoke the click event using:
And I haven't figured out a way around that yet (though if your seek is just "fast forward" a bit, you could decrease the video size, set the playback rate to super high, then bring it back down to normal when it reaches the desired location I suppose).
So we need to find a different way to send the seek command. Apparently at one point there was a netflix.cadmium.objects.videoPlayer() or netflix.player javascript objects available with a seek method, however they appear to be absent now.
Most developers' day-to-day is inefficient primarily because of the dozens of fragmented services and tools they use to build, run and scale applications. The inefficiency inadvertently leads to lost productivity. For small companies, the fragmented developer experiences might be tolerable, but the need to unify them grows as the business grows.
Led by Brian Leathem, developers at Netflix, which had adopted a microservices architecture early on, found that this approach was becoming too fragmented as the platform tooling grew. They needed to unify developer experiences across the company's Software Development Life Cycle (SDLC). Brian Leathem shared these insights during PlatformCon 2022.
To unify developer experiences across Netflix's SDLC, the Platform Experiences and Design (PXD) team at Netflix decided to build a federated platform console. The Netflix federated platform console is a one-stop shop for all the tools engineers need to develop and deploy software at scale. It consolidates the dozens of services and tools developers use into a single, easy-to-use interface.
There are too many tools that developers have to work with daily, making it challenging to develop, deliver, and operate services and software. For instance, it is not unusual for a developer to use Bitbucket to review poll requests, Spinnaker to check on their deployment pipelines, Jenkins to check on their build failures, and internal alerting metric tools to check their operational status, etc., throughout the SDLC. In addition, they will likely need to repeat these workflows multiple times.
Product service owners at Netflix have created tools and documentation for developers, but many developers don't know the tools exist. Any developer will not immediately know the many tools and documentation their teams are using and might find themselves relying on tribal knowledge passed along to new team members. On the other hand, a developer that has been around longer might not know about new tools that have been added to improve their daily workflows.
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