Back-end Essentials: Architecture for High Capacity Service with Redis – Coloso

Get the course Back-end Essentials: Architecture for High Capacity Service with Redis – Coloso free download links through Mega.nz and Google Drive.

  • Total 39 videos In this class, you’ll learn about the essentials for building a high capacity service as well as Redis technology with the top-class developer in distributed cache technology Redis, Daemyeong Kang.
  • Intermediate Level Requires a basic understanding of Linux or Mac, Python 3(3.8.6), Ansible, Terraform, AWS Account, and Access Key

“Didn’t you ever wonder how giant IT companies that have a huge amount of users like Kakao and Naver are able to provide stable services for 100 thousand or even 1 million people without failure?”

There’s no place to learn how to build a high capacity service other than large companies that have built high capacity services.

So I’ve brought all my experiences gained from developing Naver Mail at Naver and KakaoStory at Kakao, by a developer from Naver, Kakao, and Udemy

Faults happen anytime, anywhere. So the key is not to prevent failure in a service, but to quickly find the cause of the failure when it occurs, or how quickly the failure is recovered.

Large-scale service development ultimately depends on how easily the service is scaled, and building a structure that could easily respond to failures.
However, it’s difficult to apply this just by listening to the class once and simply learning.

So in this class, as I show you the basic knowledge that’s necessary for large-scale service development, and the parts that actually affect performance through exercises, I’ll help you improve your understanding and apply it to practical work.

Class Highlights

Let’s have a sneak peek of Daemyeong Kang’s
“Multi-Write Read One” method of Redis exercise.

When a Hot Key occurs, even a high-performance cache server cannot receive data over its capacity.

To deal with this, did you know that you can solve this problem using the Multi-Write, Read One method that writes cache in a few locations and reads data randomly?

The problem is solved through the following process.

– Setting up Redis
– Cache Write stores in 2 locations.
– Cache Read reads from 1 location.

Sales Page: _coloso.us/programming/softwareengineer-kangdaemyeong-us

MEGA and Google Drive Links available

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