Difference between revisions of "Edge++: Deployment"

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Basic building blocks of the architecture in terms of dockers are as follows:
 
Basic building blocks of the architecture in terms of dockers are as follows:
 
{| class="wikitable"
 
{| class="wikitable"
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!Name
 
!Docker Image
 
!Docker Image
 
!Purpose
 
!Purpose
 
|-
 
|-
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|redis
 
|redis:6.0.3-buster
 
|redis:6.0.3-buster
 
|Redis server
 
|Redis server
 
|-
 
|-
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|mongo
 
|mongo:4.2.7-bionic
 
|mongo:4.2.7-bionic
 
|MongoDB for master data caching
 
|MongoDB for master data caching
 
|-
 
|-
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|factory-server
 
|altizon/factory
 
|altizon/factory
 
|Factory Server to provide operator screens using FaasInfra
 
|Factory Server to provide operator screens using FaasInfra
 
|-
 
|-
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|sidekiq
 
|altizon/factory
 
|altizon/factory
 
|Sidekiq running asynchronous tasks
 
|Sidekiq running asynchronous tasks
 
|-
 
|-
|
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|factory-rake
|
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|altizon/factory
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|There will be N no of instances of this kind listening to their respective input queues.
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|-
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|factory-function-cache
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|altizon/factory
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|Function Task schedular to start master data caching like account and user preferences to local MongoDB from production
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|-
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|update_number_of_queues
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|altizon/factory
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|Updating __number_of_input_queues__ in Redis on boot
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|-
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|wget_call
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|altizon/factory
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|Calling first API request to server initiating asset compilation
 
|}
 
|}
  

Revision as of 11:10, 12 June 2020

Edge++ Deployment on Rails setup:

The configuration Github repository can be found here [1] This repository is a bunch of shell scripts that will help you orchestrate dockerized environment. This environment is served using docker-compose.

Basic building blocks of the architecture in terms of dockers are as follows:

Name Docker Image Purpose
redis redis:6.0.3-buster Redis server
mongo mongo:4.2.7-bionic MongoDB for master data caching
factory-server altizon/factory Factory Server to provide operator screens using FaasInfra
sidekiq altizon/factory Sidekiq running asynchronous tasks
factory-rake altizon/factory There will be N no of instances of this kind listening to their respective input queues.
factory-function-cache altizon/factory Function Task schedular to start master data caching like account and user preferences to local MongoDB from production
update_number_of_queues altizon/factory Updating __number_of_input_queues__ in Redis on boot
wget_call altizon/factory Calling first API request to server initiating asset compilation

Data Persistance:

  • The data being saved in MongoDB is a volume mounted on docker. Hence, it is safe to assume that your data will persist in MongoDB across boots of Edge++.
  • For Redis we use Redis Persistance to ensure Redis maintains its state across boots. We use .aof files for saving our state.

FAQs for runnning Edge++ on Ubuntu VM using Oracle VirtualBox

Oracle VirtualBox related FAQS