Netflix is the world’s leading internet television network, with more than 100 million members worldwide enjoying 125 million hours of TV shows and movies each day, including original series, documentaries, and feature films. Members can watch as much as they want, anytime, anywhere, on nearly any Internet-connected screen.

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KDS (KINESIS DATA STREAMS)

Amazon Kinesis Data Streams (KDS) is a massively scalable and durable real-time data streaming service. KDS can continuously capture gigabytes of data per second from hundreds of thousands of sources such as website clickstreams, database event streams, financial transactions, social media feeds, IT logs, and location-tracking events. The data collected is available in milliseconds to enable real-time analytics use cases such as real-time dashboards, real-time anomaly detection, dynamic pricing, and more.

Introduction to KDS
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KDS with AUTO SCALING

As your streaming information increases, you require a scaling solution to accommodate all requests. If you have a decrease in streaming information, you might use scaling to reduce costs. Currently, you scale an Amazon Kinesis Data Stream shard programmatically. Alternatively, you can use the Amazon Kinesis Scaling Utilities. To do so, you can use each utility manually, or automated with an AWS Elastic Beanstalk environment

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LIMITATIONS

Application Auto Scaling can scale up and down continuously to make sure that you can meet your demand. However, Kinesis Data Streams have some limitations to consider when configuring Application Auto Scaling. With Kinesis Data Streams, you can’t do the following:

  • Scale up to more than double your current shard count for a stream
  • Scale down below half your current shard count for a stream
  • Scale up to more than 10000 shards in a stream
  • Scale a stream with more than 10000 shards down unless the result is less than 10000 shards
  • Scale up to more than the shard limit for your account

Conclusion

Written by

ARTH Learner at LinuxWorld Informatics Pvt Ltd & AL ML Developer

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