Case Study: Kayo using AWS Cloud.
Kayo Sports is an over-the-top video streaming subscription service available in Australia, owned by Streamotion. The service offers sports live and on demand from Fox Sports, ESPN, beIN Sports, and Racing.com.
Kayo Sports officially launched on 26 November 2018.As of February 2019, Kayo Sports had 115,000 subscribers of which 100,000 were paying and now As of 4 August 2020, there were 590,000 subscribers, of which 542,000 were paying.
So making customer experience better in march 2019 kayo using Amazon web services. Kayo Sports uses AWS services for media, compute, storage, and analysis to deliver 30,000 hours of live content and rich interactive user experiences.
Kayo Sports builds real-time view of the customer on AWS.
Kayo Sports was looking to create a unified database integrating internal and external sources of data, including customer behavior, preferences, profile information, and other interactions to provide a better experience across customer touchpoints. The company decided to build a cloud-native platform on AWS to collect, process, and manage customer engagement data in real time. This unified data platform has become a hub for machine learning and enables departments to manage their own reporting and analytics.
Kayo uses AWS like EKS, EMR, Athena, Glue, Redshift, Kinesis, and S3.
kayo uses AWS Elemental Live encoding on premises, Amazon Cloud Front, and other AWS services, to power new kinds of viewing experiences. This includes Kayo Split View, which offers up to four events or camera angles on one screen on selected devices. The same AWS workflow supports Kayo Key Moments, which captures highlights from matches, so sports fans can get straight to the action they want to watch.
Enabling viewers to watch how and when they want, the Kayo online sports service features pause, rewind, and replay functionality delivered by AWS Elemental Media Package in Apple HLS and MPEG DASH streams. To help deliver the best possible viewing experience, the end-to-end AWS Elemental live streaming workflow delivers broadcast-quality video content with much lower delay than traditional live streaming sports simulcasts.
Kayo’s video infrastructure is architected for availability, scalability, and low latency. Amazon Elastic Compute Cloud (EC2) provides elastic compute capacity based on demand, while AWS Elemental MediaPackage is supported across multiple AWS Availability Zones to reliably repackage and originate content for delivery to Amazon CloudFront.
Storage built on Amazon Elastic Compute Cloud and Amazon Simple Storage Service Glacier (Amazon S3 Glacier) is used to analyze live performance data to support continuous optimization. AWS Lambda and AWS Step Functions provide a serverless execution of sign-ups and user validation.
Data stream in real Time
Amazon Kinesis Services: easily collect, process, and analyze data streams in real time so you can get timely insights and react quickly to new information.
What is a data lake?
A data lake is a centralized repository that allows you to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data, and run different types of analytics — from dashboards and visualizations to big data processing, real-time analytics, and machine learning to guide better decisions.
Why did Kayo decide to build it’s data lake and streaming analytics on AWS?
Kayo was slated to grow rapidly due to the wide variety of partners and affiliate integration that it started with. So we wanted to opt for a platform that can keep up with this pace of growth without any significant spike on infrastructure budget and engineering effort as we face the four V’s of Big Data (volume, variety, velocity, and veracity).
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