The rise of real-time data analytics has enabled business systems to read and react to events most compellingly and accurately. It has proved to be a boon for companies to implement needs that require quick attention, such as preventive maintenance, cross-selling, recognizing potential cyber threats, customer behavior, media sharing, etc. In this article we will talk about Live streaming architecture on AWS & Amazon Solutions.
What is the State of Real-time Live Streaming?
There has been a significant rise among businesses to experiment with live streaming analytics to analyze the data as and when it is generated. For instance, Alibaba uses event-driven solutions to leverage real-time streaming analytics to improve the personalization of products and search relevance of the product on the company’s eCommerce site.
Similarly, many other companies rely on a live streaming architecture that adequately addresses the requirement for each element for particular use-cases. At its core, many businesses are now realizing that real-time or near real-time data analytics is the need of the hour, rather than delayed or stored data.
This is precisely also the reason why video streaming architecture on AWS is grabbing attention all over. The video streaming market is estimated to grow at a compound annual rate of 20.4% to reach a size of whopping $184.3 billion by 2027.
Video live streaming on AWS aids in capturing data, which in this case can be audio-video or any media data, and broadcast/publish them to the audience in real-time. The concept is similar to event-streaming, where an event triggers a domino effect of capturing, extracting, and publishing data in near real-time.
AWS Live Streaming Architecture Implementation
Live streaming architecture essentially consists of two layers- storage and a processing layer. Since the storage layer enables fast and repeatable reads and writes of huge data streams, it needs to record and order real-time data with proper consistency and accuracy. The processing layer is where the data from the storage layers are consumed and processed using various computations.
Both the layers work in liaison to create a seamless flow of real-time data in a way that fits your business needs. Implementing such architecture from scratch can be an exhausting and risky task, as you will need to take care of its scalability, data durability, and fault tolerance.
Live streaming platforms like Kafka on AWS help you in building live streaming architecture for a multitude of event-driven applications. It provides cost-effective over-the-top (OTT) video streaming solutions for businesses to deliver media in real-time with an impeccable real-time viewing experience.
To understand the live streaming architecture implementation, you need to know the five APIs, Kafka uses to perform the live streaming:
- Producer API -Sends data streams to Kafka topics.
- Consumer API- Reads and sieves relevant data streams from Kafka topics.
- Streams API – Transforms input data streams to output topics.
- Connect API- Implements connectors that continually pull from some source system or application into Kafka or push from Kafka into some sink system or application.
- AdminClient API- Manages and inspects topics, brokers, and other Kafka objects.
Popular companies like Netflix, Pinterest, Uber have implemented the Kafka architecture for live streaming applications. While Netflix implements Kafka’s live streaming architecture along with Apache Flink for distributed streaming, Pinterest relies on the Kafka event-streaming benefits for content indexing, recommendations, spam detection, etc.
Every business is unique in its goals and rendition. Therefore, choosing a live streaming architecture empowers your company to improve overall agility and imbibes data-driven dynamics into various business processes.
Implementing live streaming architecture on AWS for your business can be an intimidating process at first. However, with the right strategy and the right tools, live streaming can help your company grow beyond leaps and bounds.