Cloudhub Digital takes care of all components that a good streaming service would require to fulfill. While there are too many things from an architecture perspective that go into the building of a streaming app, we cover all main foundation elements., like
Edge Computing and CDNs:
Content is delivered to devices through CDNs, which act as the cache for the content. Edge computing uses the power of the cloud and takes computing power close to the end device. This is the first layer of logic that interacts with devices, and it links the request to the appropriate API within the services architecture. It also provides the abstraction layer to the mid-tier services.
Load Balancing: This helps the streaming service manage peaks in the load by implementing throttling mechanisms that reject the extra incoming requests and diverting them to other servers when the traffic crosses a threshold.
The entire backend application is split into hundreds of independent services. These services implement specific business logic, hence encapsulating one service from another. This enables the entire service to function without the risk of one flaw bringing the whole application down to its knees. These services provide functions such as authentication, licensing, playback, artwork, etc.
Encoding and Content Delivery:
Every media file is broken into chunks and transcoded into different bit rates. This is done to provide the best possible quality to different devices at varying bandwidths. Every media content demands its quality standards. A fast-moving video will require transcoding at a higher quality than a video, which is relatively slow-moving. Adaptive streaming is used to push the most appropriate bit rate segment of the video. Local caching is used to serve subscribers. Push fill methodology is used to load the content in a regional CDN based on the popularity of the content in that region.
Data is created at an enormous scale since billions of events take place in a day and millions in a second. A data pipeline must be designed to enable the cloud storage of the video viewings and UI activities. This data is used for big data analytics. This, along with device error logs and diagnostic events, is also used for monitoring and debugging operations.