Kinesisvideo

With Amazon Kinesis Video Streams, you pay only for what you use. There are no resources to provision, no upfront costs, or minimum fees. For Kinesis Video Streams, you pay only for the volume of data you ingest, store, and consume through the service.

If you use WebRTC capabilities, you pay for the number of signaling channels that are active in a given month, number of signaling messages sent and received, and TURN streaming minutes used for relaying media. A signaling channel is considered active in a month if at any time during the month a device or an application connects to it. TURN streaming minutes are metered in 1 minute increments.

Note: You will incur standard AWS data transfer charges when you retrieve data from your video streams to destinations outside of AWS over the internet. A metropolitan city has security cams covering busy traffic intersections. This data is streamed and stored in Amazon Kinesis Video Streams for a 2-week period. Data from five cameras is consumed by a pedestrian counting algorithm running on AWS. A second application consumes the same amount of data to generate a video clip summary.

Their monthly charges will be calculated as follows:. The same amount of data is also consumed by another application that generates a video summary clip.

Note: You will incur standard AWS data transfer charges when you retrieve data from your video streams to destinations outside of AWS over the Internet. A mobile application developer has a smart phone app with users that uses WebRTC capabilities in Kinesis Video Streams for live media streaming.

The monthly charges will be calculated as follows:. Each user app is connected to its own unique signaling channel, for a total of active signaling channels in a month. Each user live streams 50 times in a month and every live streaming session delivers 30 signaling messages, for a total ofmessages in a month. A home security system provider has 1, users.

Each user has one camera in their home that streams when it detects motion. The video is stored in Amazon Kinesis Video Streams for a one-week period. The monthly Kinesis Video Streams charges will be calculated as follows:.

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Video Streams: Each camera streams at 1 Mbps, generating MB of data in 20 minutes of streaming per day, for a total ofMB per day across 1, cameras.

WebRTC: Each cameras is connected to its own unique signaling channel for a total of 1, active signaling channels in a month. Every live streaming session delivers 30 signaling messages, for a total of 3, signaling messages. Product Pricing Glossary Video stream : A resource that enables you to capture live video and other time-encoded data, optionally store it, and consume data. Signaling channel : An optional resource that enables applications to establish peer-to-peer connectivity by exchanging metadata in signaling messages.

TURN streaming : An optional capability for relaying media via the cloud when applications are unable to connect to each other directly for peer-to-peer streaming due to symmetric NAT or other issues.

Pricing example 1: Smart city traffic cameras that use video streams A metropolitan city has security cams covering busy traffic intersections. Each of the cameras generate MB of video data per day, for a total of 39, MB per day. Pricing example 3: Smart home security camera using both video streams and WebRTC A home security system provider has 1, users. Discover more Amazon Kinesis Video Streams resources. Ready to get started? Have more questions?What's KVS and what does it do?

Amazon Kinesis Video Streams makes it easy to securely stream video from connected devices to AWS for analytics, machine learning MLplayback, and other processing.

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Kinesis Video Streams automatically provisions and elastically scales all the infrastructure needed to ingest streaming video data from millions of devices. It also durably stores, encrypts, and indexes video data in your streams, and allows you to access your data through easy-to-use APIs.

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Kinesis Video Streams enables you to playback video for live and on-demand viewing, and quickly build applications that take advantage of computer vision and video analytics through integration with Amazon Rekognition Video, and libraries for ML frameworks such as Apache MxNet, TensorFlow, and OpenCV.

Problem A: stream splitting not to be confused with shard-splitting. This element splits data to multiple pads. Splitting the data flow is useful, for example, when capturing a video where the video is shown on the screen and also encoded and written to a file. Another example is playing music and hooking up a visualization module.

One needs to use separate queue elements in each branch to provide separate threads for each branch. Otherwise a blocked dataflow in one branch would stall the other branches. For more details, see here and here. Each will create two identical streams in Kinesis, named Stream1 and Stream2. The difference is in the location of the "tee" element, which define where in the pipeline the split is performed.

All you have is the stream's ARN.

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For more information about get-hls-streaming-session-urlsee Amazon's official documentation. Note: as you can tell from the resulting file's erratic playback, the fragments often arrive out-of-order and therefore saved out-of-order :. Keep in mind that you can only access chunk-level data with Python. Frame-level data can only be accessed in Java!

Stay up to date! Let's look at some things that aren't obvious, poorly documented, or just hard to do.A name for the signaling channel that you are creating. It must be unique for each account and region. When you create a new stream, Kinesis Video Streams assigns it a version number.

When you change the stream's metadata, Kinesis Video Streams updates the version. For information about how the service works, see How it Works. You must have permissions for the KinesisVideo:CreateStream action. The media type of the stream. Consumers of the stream can use this information when processing the stream. For more information about media types, see Media Types.

If you choose to specify the MediaTypesee Naming Requirements for guidelines. This parameter is optional; the default value is null or empty in JSON. For more information, see DescribeKey. The number of hours that you want to retain the data in the stream. Kinesis Video Streams retains the data in a data store that is associated with the stream. When the DataRetentionInHours value is 0, consumers can still consume the fragments that remain in the service host buffer, which has a retention time limit of 5 minutes and a retention memory limit of MB.

Fragments are removed from the buffer when either limit is reached. A list of tags to associate with the specified stream. Each tag is a key-value pair the value is optional.

Deletes a specified signaling channel. DeleteSignalingChannel is an asynchronous operation. If you don't specify the channel's current version, the most recent version is deleted. This method marks the stream for deletion, and makes the data in the stream inaccessible immediately. To ensure that you have the latest version of the stream before deleting it, you can specify the stream version.

Kinesis Video Streams assigns a version to each stream. When you update a stream, Kinesis Video Streams assigns a new version number. This operation requires permission for the KinesisVideo:DeleteStream action. Specify the version as a safeguard to ensure that your are deleting the correct stream.

If not specified, only the CreationTime is checked before deleting the stream. Returns the most current information about the signaling channel. You must specify either the name or the ARN of the channel that you want to describe. Returns the most current information about the specified stream. Gets an endpoint for a specified stream for either reading or writing.The provided lenses should be compatible with any of the major lens libraries such as lens or lens-family-core.

See Network. KinesisVideo or the AWS documentation to get started. The provided lenses should be compatible with any of the major lens libraries lens or lens-family-core. For any problems, comments, or feedback please create an issue here on GitHub. Note: this library is an auto-generated Haskell package.

AWS re:Invent Launchpad 2017 - Amazon Kinesis Video Streams

Please see amazonka-gen for more information. Parts of the code are derived from AWS service descriptions, licensed under Apache 2. Source files subject to this contain an additional licensing clause in their header. Produced by hackage and Cabal 2. Versions [ faq ] 1. KinesisVideo Network.

kinesisvideo

CreateStream Network. DeleteStream Network. DescribeStream Network. GetDataEndpoint Network.

kinesisvideo

ListStreams Network. ListTagsForStream Network. TagStream Network. Types Network. UntagStream Network. UpdateDataRetention Network.Amazon Kinesis Video Streams makes it easy to securely stream media from connected devices to AWS for storage, analytics, machine learning MLplayback, and other processing. Kinesis Video Streams automatically provisions and elastically scales all the infrastructure needed to ingest streaming media from millions of devices.

It durably stores, encrypts, and indexes media in your streams, and allows you to access your media through easy-to-use APIs. Kinesis Video Streams also supports ultra-low latency two-way media streaming with WebRTC, as a fully managed capability. Time-encoded data is any data in which the records are in a time series, and each record is related to its previous and next records.

Video is an example of time-encoded data, where each frame is related to the previous and next frames through spatial transformations. Amazon Kinesis Video Streams is designed specifically for cost-effective, efficient ingestion, and storage of all kinds of time-encoded data for analytics and ML use cases.

Kinesis Video Streams is ideal for building media streaming applications for camera-enabled IoT devices and for building real-time computer vision-enabled ML applications that are becoming prevalent in a wide range of use cases such as the following:. With Kinesis Video Streams, you can easily stream video and audio from camera-equipped home devices such as baby monitors, webcams, and home surveillance systems to AWS.

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You can then use the streams to build a variety of smart home applications ranging from simple media playback to intelligent lighting, climate control systems, and security solutions. You can use Kinesis Video Streams to securely and cost-effectively ingest, store, playback, and analyze this massive volume of media data to help solve traffic problems, help prevent crime, dispatch emergency responders, and much more. You can then analyze the data using your favorite machine learning framework including Apache MxNet, TensorFlow, and OpenCV for industrial automation use cases like predictive maintenance.

For example, you can predict the lifetime of a gasket or valve and schedule part replacement in advance, reducing downtime and defects in a manufacturing line. Amazon Kinesis Video Streams is a fully managed service for media ingestion, storage, and processing.

It enables you to securely ingest, process, and store video at any scale for applications that power robots, smart cities, industrial automation, security monitoring, machine learning MLand more. Kinesis Video Streams automatically provisions and elastically scales all the infrastructure needed to ingest media streams from millions of devices.

It also durably stores, encrypts, and indexes the media streams and provides easy-to-use APIs so that applications can retrieve and process indexed media fragments based on tags and timestamps.

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Kinesis Video Streams is integrated with Amazon Rekognition Video, enabling you to build computer vision applications that detect objects, events, and people. A video stream is a resource that enables you to capture live video and other time-encoded data, optionally store it, and make the data available for consumption both in real time and on a batch or ad-hoc basis.

When you choose to store data in the video stream, Kinesis Video Streams will encrypt the data, and generate a time-based index on the stored data. The Kinesis video stream can have multiple consuming applications processing the contents of the video stream.

A fragment is a self-contained sequence of media frames. The frames belonging to a fragment should have no dependency on any frames from other fragments. As fragments arrive, Kinesis Video Streams assigns a unique fragment number, in increasing order. A producer is a general term used to refer to a device or source that puts data into a Kinesis video stream.

A producer can be any video-generating device, such as a security camera, a body-worn camera, a smartphone camera, or a dashboard camera.

One producer can generate one or more video streams. For example, a video camera can push video data to one Kinesis video stream and audio data to another. Consumers are your custom applications that consume and process data in Kinesis video streams in real time, or after the data is durably stored and time-indexed when low latency processing is not required.

You can create these consumer applications to run on Amazon EC2 instances. You can also use other Amazon AI services such as Amazon Rekognition, or third party video analytics providers to process your video streams. Upon receiving the data from a producer, Kinesis Video Streams stores incoming media data as chunks.If you've got a moment, please tell us what we did right so we can do more of it. Thanks for letting us know this page needs work. We're sorry we let you down.

If you've got a moment, please tell us how we can make the documentation better. Kinesis Video Streams provides APIs for you to create and manage streams and read or write media data to and from a stream. The Kinesis Video Streams console, in addition to administration functionality, also supports live and video-on-demand playback. Kinesis Video Streams also provides a set of producer libraries that you can use in your application code to extract data from your media sources and upload to your Kinesis video stream.

It also provides APIs for reading and writing media data to a stream, as follows:. In a PutMedia request, the producer sends a stream of media fragments. A fragment is a self-contained sequence of frames. The frames belonging to a fragment should have no dependency on any frames from other fragments.

For more information, see PutMedia.

kinesisvideo

As fragments arrive, Kinesis Video Streams assigns a unique fragment number, in increasing order. It also stores producer-side and server-side time stamps for each fragment, as Kinesis Video Streams-specific metadata.

The API then returns fragments in the order in which they were added to the stream in increasing order by fragment number. The media data in the fragments is packed into a structured format such as Matroska MKV. For more information, see GetMedia. GetMedia knows where the fragments are archived in the data store or available in real time. For example, if GetMedia determines that the starting fragment is archived, it starts returning fragments from the data store.

Amazon Kinesis Video Streams

When it needs to return newer fragments that are not archived yet, GetMedia switches to reading fragments from an in-memory stream buffer. This is an example of a continuous consumer, which processes fragments in the order that they are ingested by the stream. GetMedia enables video-processing applications to fail or fall behind, and then catch up with no additional effort.

kinesisvideo

Using GetMediaapplications can process data that's archived in the data store, and as the application catches up, GetMedia continues to feed media data in real time as it arrives. ListFragments and GetMediaFromFragmentList enable an application to identify segments of video for a particular time range or fragment range, and then fetch those fragments either sequentially or in parallel for processing.

This approach is suitable for MapReduce application suites, which must quickly process large amounts of data in parallel. For example, suppose that a consumer wants to process one day's worth of video fragments. The consumer would do the following:. Get a list of fragments by calling the ListFragments API and specifying a time range to select the desired collection of fragments.

The API returns metadata from all the fragments in the specified time range. Take the fragment metadata list and retrieve fragments, in any order.Released: Apr 8, Type annotations for boto3. KinesisVideo 1.

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View statistics for this project via Libraries. Tags boto3, kinesisvideo, type-annotations, boto3-stubs, mypy, typeshed, autocomplete, auto-generated. Generated by mypy-boto3-buider 1. More information can be found on boto3-stubs page. Make sure you have mypy installed and activated in your IDE. Fully automated builder carefully generates type annotations for each service, patiently waiting for boto3 updates.

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