Scaling Go Applications: Difference between revisions
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For this page we will be looking a the challenges around breaking an application in to several servers and following an architecture such as below | For this page we will be looking a the challenges around breaking an application in to several servers and following an architecture such as below | ||
[[File:Go Scale overview.png|700px]] | [[File:Go Scale overview.png|700px]] | ||
This not meant to be THE solution but a walkthrough on some of the challenges to scale. This will be split into | |||
*Initial Optimizations | |||
*Creating a Load Balancer | |||
*Caching | |||
*Centralized Logging | |||
AGAIN this is an approach and of course you can use third-party cloud solutions. This one will be confined to Docker and GO. | |||
Revision as of 11:51, 28 January 2021
Introduction
Resources
When we look at scaling we must consider the following resources.
- Network Bandwidth
- Processing Power
- Available Memory
- Data Storage
For this page we will be looking a the challenges around breaking an application in to several servers and following an architecture such as below
This not meant to be THE solution but a walkthrough on some of the challenges to scale. This will be split into
- Initial Optimizations
- Creating a Load Balancer
- Caching
- Centralized Logging
AGAIN this is an approach and of course you can use third-party cloud solutions. This one will be confined to Docker and GO.