Building datacenters was not a competitive advantage for Netflix, delivering video is. At that time, Netflix decided to move to AWS. Netflix moved to AWS because it wanted a more reliable infrastructure. Netflix wanted to remove any single point of failure from its system. AWS offered highly reliable databases, storage and redundant datacenters. Netflix wanted to become a global service without building its own datacenters. None of these capabilities were available in its old datacenters and never would be. AWS does all the undifferentiated heavy lifting for Netflix.
This lets Netflixians focus on providing business value. 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. Within each region, Netflix operates in three different availability zones. Netflix has said there are no plans to operate out of more regions. Most companies operate out of just one region, let alone two or three. 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. What happens if the entire Dublin region fails? Does that mean Netflix should stop working for you?
Of course not! Netflix, after detecting the failure, redirects you to Virginia. Your device would now talk to the Virginia region instead of Dublin. You might not even notice there was a failure. How often does an AWS region fail? Once a month. Netflix runs monthly tests. Every month Netflix causes a region to fail on purpose just to make sure its system can handle region level failures. A region can be evacuated in six minutes. Netflix calls this their global services model. Any customer can be served out of any region.
This is amazing. AWS has no magic sauce for handling region failures or serving customers out of multiple regions. Netflix has done all this work on its own. Netflix is a pioneer in figuring out how to create reliable systems using multiple regions. Another advantage of being in these three regions is that it gives Netflix world-wide coverage.
This may surprise a lot of people, but AWS is cheaper for Netflix.
The cloud costs per streaming view ended up being a fraction of the cost of its old datacenters. Rather than have a lot of extra computers hanging around doing nothing just to handle peak load, Netflix only had to pay for what was needed, when it was needed. This includes scalable computing, scalable storage, business logic, scalable distributed databases, big data processing and analytics, recommendations, transcoding, and hundreds of other functions.
Scalable computing is EC2 and scalable storage is S3. Nothing new for us here. View a list of potential videos to watch? Ask for more details about a video? Netflix uses both DynamoDB and Cassandra for their distributed databases. A database stores data. Your data is copied to multiple computers so if one or even two computers holding your data fail, your data will be safe. In fact, your data is copied to all three regions. That way, if a region fails your data will be there when the new region is ready to start using it.
Scalable means the database can handle as much data as you ever want to put into it. More computers can be added as necessary to handle more data. Netflix collects a lot of information. Netflix knows what everyone has watched when they watched it and where they were when they watched. Netflix knows which videos members have looked at but decided not to watch. Netflix knows how many times each video has been watched…and a lot more. Making sense of all that data is called analytics. Data is analyzed to answer specific questions.
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. You might be surprised to learn the image shown for each video is selected specifically for you. Not everyone sees the same image.
Everyone used to see the same header image. Members were shown at a random one picture from a group of options, like the pictures in the above Stranger Things collage. Netflix counted every time the video was watched, recording which picture was displayed when the video was selected. For all the other pictures, it was watched only once each. Since the group picture was the best at getting members to watch, Netflix would make it the header image for Stranger Things forever. This is called being data-driven.
Netflix is known for being a data-driven company. Data is gathered—in this case, the number of views associated with each picture—and used to make the best decisions possible—in this case, which header image to select. Clever, but can you imagine doing better? Yes, by using more data.
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You and I are likely very different people. Do you think we are motivated by the same kind of header image? Probably not. We have different tastes. We have different preferences. Netflix knows this too. Netflix tries to select the artwork highlighting the most relevant aspect of a video to you. How do they do that? Remember, Netflix records and counts everything you do on their site. They know which kind of movies you like best, which actors you like the most, and so on. Netflix must choose a header image to show you. Which image should Netflix show you? If you like comedies, Netflix will show you an image featuring Robin Williams.
If you prefer romantic movies, Netflix will show you an image Matt Damon and Minnie Driver poised for a kiss.
The Matt Damon and Minnie Driver image conveys a completely different message. It sends a strong personalized signal indicating what a movie is about. Can you see how choosing the best possible personalized artwork might make you more likely to watch a particular video? Netflix tries to minimize regret.
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Netflix wants you to be happy with the videos you watch, so they pick the best header images they can for you. This is just one small example of how data analysis is used by Netflix. Netflix uses these kind of strategies everywhere. Usually Netflix will show you only 40 to 50 video options, yet they have many thousands of videos available. In fact, everything you see see on a Netflix screen was chosen specifically for you using machine learning. Before you can watch a video on your favorite device of choice, Netflix must convert the video into a format that works best for your device.
This process is called transcoding or encoding. Transcoding is the process that converts a video file from one format to another, to make videos viewable across different platforms and devices. Who sends video to Netflix? Production houses and studios. Netflix calls this video source media. The new video is given to the Content Operations Team for processing. A terabyte is big.
Imagine 60 stacks of paper as tall as the Eiffel Tower. The first thing Netflix does is spend a lot of time validating the video. 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 video chunks are then put through the pipeline so they can be encoded in parallel.
In parallel simply means the chunks are processed at the same time. Which would be faster, one person washing the dogs one after another? Or would it be faster to hire one hundred dog washers and wash them all the same time? They need a lot of servers to process these huge video files in parallel. It works too.
Netflix says a source media file can be encoded and pushed to their CDN in as little as 30 minutes. The encoding process creates a lot of files. The end goal for Netflix is to support every internet-connected device. Netflix started streaming video in on Microsoft Windows. In all, Netflix supports different devices.
Each device has a video format that looks best on that particular device. Netflix also creates files optimized for different network speeds.
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There are also files for different audio formats. Audio is encoded into different levels of quality and in different languages. There are also files included for subtitles. A video may have subtitles in a number of different languages. There are a lot of different viewing options for every video. What you see depends on your device, your network quality, your Netflix plan, and your language choice.
Stranger Things season 2 has even more files. It was shot in 8K and has nine episodes. The source video files were many, many terabytes of data. It took , CPU hours to encode just one season. A CDN is a content distribution network. Content for Netflix—is of course—the video files we discussed in the previous section. Distribution means video files are copied from a central location, over a network and stored on computers located all over the world.
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. The video stream must pass through a lot of networks, including an undersea cable, so the connection will be slow and unreliable. By moving video content as close as possible to the people watching it, the viewing experience will be as fast and reliable as possible.
Each location with a computer storing video content is called a PoP or point of presence. Each PoP is a physical location that provides access to the internet. It houses servers, routers, and other telecommunications equipment. In , 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.
To support the streaming service, Netflix built its own simple CDN in five different locations within the United States. The Netflix video catalog was small enough at the time that each location contained all of its content. In , Netflix decided to use 3rd-party CDNs. Around this time, the pricing for 3rd-party CDNs was coming down. Using 3rd-party CDNs made perfect sense for Netflix. Why spend all the time and effort building a CDN of your own when you can instantly reach the globe using existing CDN services?
In fact, pretty much every company does. For example, the NFL has used Akamai to stream live football games. By not building out its own CDN, Netflix had more time to work on other higher priority projects. Netflix put a lot of time and effort into developing smarter clients. Netflix created algorithms to adapt to changing networks conditions. Even in the face of errors, overloaded networks, and overloaded servers, Netflix wants members always viewing the best picture possible.
One technique Netflix developed is switching to a different video source—say another CDN, or a different server—to get a better result. 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 , 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. Open Connect launched in The 3rd-party CDNs must support users accessing any kind of content from anywhere in the world. Netflix has a much simpler job.
Netflix knows exactly who its users are because they must subscribe to Netflix. Netflix knows exactly which videos it needs to serve. Netflix also knows a lot about it members. The company knows which videos they like to watch and when they like to watch them.
With this kind of knowledge, Netflix built a really high-performing CDN. Netflix developed its own computer system for video storage. There are many OCAs in the above picture. OCAs are grouped into clusters of multiple servers. Each OCA is a fast server, highly optimized for delivering large files, with lots and lots of hard disks or flash drives for storing video. There are several different kinds of OCAs for different purposes.
Smaller OCAs are filled with video every day, during off-peak hours, using a process Netflix calls proactive cachin g. You could buy the same computers if you wanted to. Netflix had their computers specially made to match their logo color. Yes, every OCA has a web server. 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.
For the best possible video viewing experience, what Netflix would really like to do is cache video in your house. The next best thing is to put a mini-Netflix as close to your house as they can. Netflix delivers huge amounts of video traffic from thousands of servers in more than 1, locations around the world. Take a look at this map of video serving locations:. Other video services, like YouTube and Amazon, deliver video on their own backbone network.
These companies literally built their own global network for delivering video to users. An ISP is your internet provider. It might be Verizon, Comcast, or thousands of other services. Each wire in the above picture connects one network to another network. For Netflix, this is another win. IXPs are all over the world.
Netflix has all this video sitting in S3. They have all these video serving computers spread throughout the world. Netflix uses a process it calls proactive caching to efficiently copy video to OCAs. A cache is a hiding place, especially one in the ground, for ammunition, food and treasures. Each location they bury nuts is a cache. During the winter, any squirrel can find a nut cache and chow down. Arctic explorers sent small teams ahead to cache food, fuel and other supplies along the route they were taking.
The larger team following behind would stop at every cache location and resupply. Both the squirrels and Arctic explorers were being proactive ; they were doing something ahead of time to prepare for later. Everywhere in the world, Netflix, knows to a high degree of accuracy what its members like to watch and when they like to watch it. Remember how we said Netflix was a data-driven company? Netflix uses its popularity data to predict which videos members probably will want to watch tomorrow in each location. Netflix copies the predicted videos to one or more OCAs at each location.
This is called prepositioning. Video is placed on OCAs before anyone even asks. This gives great service to members. The video they want to watch is already close to them, ready and available for streaming. These are too small to contain the entire Netflix catalog of videos. Still, other locations have big OCAs containing the entire Netflix catalog. These get their videos from S3. Each OCA is in charge of making sure it has all the videos on its list. Otherwise, a nearby OCA with the video will be found and copied.
This means videos can be copied during quiet, off-peak hours, substantially reducing bandwidth usage for ISPs. Since Netflix knows all the videos it must cache, it knows exactly where each video is at all times. Sign in to vote. Any news about a Silverlight fast update which can fix this incompatibility with Mavericks? Saturday, October 26, PM. I also had the same problem on my 15inch RMBP. I did a couple of things to fix it. First make sure you have the latest silverlight version installed. Restart your browser try it again. If it still doesn't work then go into your browser settings I use Safari and make sure internet plug-ins box is unselected.
For chrome make sure you disable any extensions like flash block and make sure plugins box is either selected to click to play or run automatically. If it still doesn't work then reboot into recovery partition and repair disk and repair permissions reboot into main drive and try it. I had to reboot and repair permissions twice and it started working again.
Lets hope this helps! Sunday, October 27, PM. Tuesday, October 29, PM.