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UPDATE 08/03/15: Starting today, API v2 of comments, captions and video flagging services are turned down.

------------------------------------------------------------------------------------------------------------------------------------------------------UPDATE 06/03/15: Starting today, most YouTube Data API v2 calls will receive 410 Gone HTTP responses.

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UPDATE 05/06/15: Starting today, YouTube Data API v2 video feeds will only return the support video.

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UPDATE: With the launch of video abuse reporting and video search for developer, the Data API v3 supports every feature scheduled to be migrated from the soon-to-be-turned-down Data API v2.

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With the recent additions of comments, captions, and RSS push notifications, the Data API v3 supports almost every feature scheduled to be migrated from the soon-to-be-turned-down Data API v2. The only remaining feature to be migrated is video flagging, which will launch in the coming days. The new API brings in many features from the latest version of YouTube, making sure your users are getting the best YouTube experience on any screen.

For a quick memory lane trip, in March 2014, we announced that the Data API v2 would be retired on April 20, 2015, and would be shut down soon thereafter. To help with your migration, we launched the migration guide in September 2014, and have also been giving you regular notices on v3 feature updates.

Retirement plan

If you’re still using the Data API v2, today we’ll start showing a video at the top of your users’ video feeds that will notify them of how they might be affected. Apart from that, your apps will work as usual.

In early May, Data API v2 video calls will start returning only the warning video introduced on April 20. Users will not be able to view other videos on apps that use the v2 API video calls. See youtube.com/devicesupport for affected devices.

By late May, v2 API calls except for comments and captions will receive 410 Gone HTTP responses. You can test your application’s reaction to this response by pointing the application at eol.gdata.youtube.com instead of gdata.youtube.com. While you should migrate your app as soon as possible, these features will work in the Data API v2 until the end of July 2015 to avoid any outages.

How you can migrate

Check out the frequently asked questions and migration guide for the most up-to-date instructions on how to update specific features to use the Data API v3. The guide now lists all of the Data API v2 functionality that is being deprecated and won't be offered in the Data API v3. It also includes updated instructions for a few newly migrated features, like comments, captions, and video flagging.

- Ibrahim Ulukaya, and the YouTube for Developers team

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Cindy 3 hours ago

I wish my app could manage YouTube comments.

Ibrahim 2 hours ago

Then it's your day today. With the new YouTube Data API (v3) you can now have comments in your app. Just register your application to use the v3 API and then check out the documentation for the  Comments and CommentThreads resources and their methods.

Andy 2 hours ago

+Cindy R u still on v2? U know the v2 API is being deprecated on April 20, and you’ve updated to v3 right?

Andy 1 hour ago

+Ibrahim I can haz client libraries, too?

Ibrahim 30 minutes ago

Yes, there are client libraries for many different programming languages, and there are already Java, PHP, and Python code samples.

Matt 20 minutes ago

My brother had a python and he used to feed it mice. Pretty gross!

Cindy 10 minutes ago

Thanks, +Ibrahim. This is very cool. The APIs Explorer lets you try out sample calls before writing any code, too.

Ibrahim 5 minutes ago

Check out this interactive demo that uses the new comments retrieval feature and Google Prediction APIs. The demo displays audience sentiment against any video by retrieving the video's comments and feeding them to the Cloud Prediction API for the sentiment analysis.

- Ibrahim Ulukaya, Andy Diamondstein and the YouTube for Developers team

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As more people watch more high-quality videos across more screens, we need video formats that provide better resolution without increasing bandwidth usage. That’s why we started encoding YouTube videos in VP9, the open-source codec that brings HD and even 4K (2160p) quality at half the bandwidth used by other known codecs.

VP9 is the most efficient video compression codec in widespread use today. In the last year alone, YouTube users have already watched more than 25 billion hours of VP9 video, billions of which would not have been played in HD without VP9's bandwidth benefits. And with more of our device partners adopting VP9, we wanted to give you a primer on the technology.

How VP9 works

Videos hold a lot of information. If video were stored in the same format that a camera sensor uses when shooting a scene, the resulting files would be enormous — raw 4K is up to 18,000 Mbps! Instead, modern video compression looks at a video more like a person might, by encoding a description of the features in a scene, and tracking how those features move and change. This compression is hundreds of times more efficient than a camera sensor's recording and is what makes video streaming possible.

While VP9 uses the same basic blueprint as previous codecs, the WebM team has packed improvements into VP9 to get more quality out of each byte of video. For instance, the encoder prioritizes the sharpest image features, and the codec now uses asymmetric transforms to help keep even the most challenging scenes looking crisp and block-free.

Here's a comparison between the image quality you'd get watching Janelle Monaé with VP9 or legacy H.264 transcodes on a 600Kbps connection:

View: VP9H.264Combined

Bringing quality to the people

This new format bumps everybody one notch closer to our goal of instant, high-quality, buffer-free videos. That means that if your Internet connection used to only play up to 480p without buffering on YouTube, it can now play silky smooth 720p with VP9.

VP9 also has benefits for people with limited bandwidth or expensive data plans. By cutting bitrates in as much as half, it dramatically increases the set of users that can watch 360p quality video without increased rebuffering or cost.

Opening the door to 4K

And for those who can never get enough pixels (including your humble author!), VP9 unlocks the burgeoning world of 4K videos. At larger video sizes, VP9 actually gets even more efficient than its predecessors, so uninterrupted 4K content can now be streamed by a significant and growing part of the YouTube audience. The amount of 4K video uploaded to YouTube has more than tripled in the past year, and VP9 helps us plan for improved streaming into the future. You can find 4K videos by using the search filter, or see some of our favorites in this playlist.

Where can I use VP9?

Thanks to our device partners, VP9 decoding support is available today in the Chrome web browser, in Android devices like the Samsung Galaxy S6, and in TVs and game consoles from Sony, LG, Sharp, and more. More than 20 device partners across the industry are launching products in 2015 and beyond using VP9.

To learn more about producing your own VP9 content, see our FFMpeg encoding guide or check out the Adobe Premier WebM plugin.

Steven Robertson, Software Engineer, recently watched “St. Lucia - Before The Dive.”

[Cross-posted from the Google Cloud Platform Blog] 

• Add more replicas for better read throughput and data durability
• Introduce sharding to scale your write throughput and let your data set grow beyond a single machine
• Create separate replica pools for batch jobs and backups, to isolate them from live traffic
• Clone the whole deployment into multiple datacenters worldwide for disaster recovery and lower latency

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[Cross-posted from the Google Cloud Platform Blog] 

Your new website is growing exponentially. After a few rounds of high fives, you start scaling to meet this unexpected demand. While you can always add more front-end servers, eventually your database becomes a bottleneck, which leads you to . . .

• Add more replicas for better read throughput and data durability
• Introduce sharding to scale your write throughput and let your data set grow beyond a single machine
• Create separate replica pools for batch jobs and backups, to isolate them from live traffic
• Clone the whole deployment into multiple datacenters worldwide for disaster recovery and lower latency

At YouTube, we went on that journey as we scaled our MySQL deployment, which today handles the metadata for billions of daily video views and 300 hours of new video uploads per minute. To do this, we developed the Vitess platform, which addresses scaling challenges while hiding the associated complexity from the application layer.

Vitess is available as an open-source project and runs best in a containerized environment. With Kubernetes and Google Container Engine as your container cluster manager, it's now a lot easier to get started. We’ve created a single deployment configuration for Vitess that works on any platform that Kubernetes supports.

In addition to being easy to deploy in a container cluster, Vitess also takes full advantage of the benefits offered by a container cluster manager, in particular:

• Horizontal scaling – add capacity by launching additional nodes rather than making one huge node
• Dynamic placement – let the cluster manager schedule Vitess containers wherever it wants
• Declarative specification – describe your desired end state, and let the cluster manager create it
• Self-healing components – recover automatically from machine failures

In this environment, Vitess provides a MySQL storage layer with improved durability, scalability, and manageability.

We're just getting started with this integration, but you can already run Vitess on Kubernetes yourself. For more on Vitess, check out vitess.io, ask questions on our forum, or join us on GitHub. In particular, take a look at our overview to understand the trade-offs of Vitess versus NoSQL solutions and fully-managed MySQL solutions like Google Cloud SQL.

-Posted by Anthony Yeh, Software Engineer, YouTube