https://github.com/deepaksinghvi/catalogwf
Catalog processing using workflow orchestration for workflow execution in a Kubernetes pods using Argo Workflow.
https://github.com/deepaksinghvi/catalogwf
argo-workflow argo-workflows cli cobra go-gin golang katacoda kubernetes kubernetes-cluster minikube restful-webservices
Last synced: 6 months ago
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Catalog processing using workflow orchestration for workflow execution in a Kubernetes pods using Argo Workflow.
- Host: GitHub
- URL: https://github.com/deepaksinghvi/catalogwf
- Owner: deepaksinghvi
- License: apache-2.0
- Created: 2021-07-25T14:55:09.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2021-09-10T04:17:11.000Z (almost 5 years ago)
- Last Synced: 2023-09-13T09:12:20.992Z (almost 3 years ago)
- Topics: argo-workflow, argo-workflows, cli, cobra, go-gin, golang, katacoda, kubernetes, kubernetes-cluster, minikube, restful-webservices
- Language: Go
- Homepage:
- Size: 9.05 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.MD
- License: LICENSE
Awesome Lists containing this project
README
## Catalog Management System
[](https://circleci.com/gh/deepaksinghvi/catalogwf/?branch=main)
Catalog Management System for e-commerce users (B2B or B2C), helps users to procurement items.
A complete catalog management solution would have consumer-like shopping with a sophisticated procurement process.
This example is primarily focusing on the catalog processing using workflow orchestration for workflow execution in a Kubernetes pods.
Catalog Workflow App Developed in GoLang.
High-level design for the Catalog Management App is as follows:
It works as the cli app as well as Restful WebService.
* ClI App is built using [Cobra](https://github.com/spf13/cobra) Library
* Restful WebService is built using [Gin Web Framework](https://github.com/gin-gonic/gin)
Catalog Workflow has been integrated with [Argo Workflow](https://argoproj.github.io/workflows).
Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes.
### Pre-Requisites
* Run Catalog Workflow App [Local or Remote](#build-&-run).
* Run Argo-Workflow (Local or Remote)
### Build & Run
```
go build
go mod
go vendor
./catalogwf catalogservice
```
#### Build Docker Image
```
docker build -t catalogwf .
docker run -p 8080:8080 -it --name catalogprocesslocal catalogwf catalogservice
```
Access application at http://localhost:8080/swagger/index.html
#### To push image to docker-hub
```
docker tag catalogwf deepaksinghvi/catalogwf:latest
docker push deepaksinghvi/catalogwf:latest
```
### Run Argo Workflow in Kubernetes Cluster
#### Run Argo Locally
```
minikube start
minikube dashboard
kubectl create ns argo
kubectl apply -n argo -f https://raw.githubusercontent.com/argoproj/argo-workflows/release-2.12.1/manifests/quick-start-minimal.yaml
//verify pods are up and running
kubectl -n argo get pods
// access argo server (previously known as argo-ui)
kubectl -n argo port-forward svc/argo-server 2746:2746
```
#### Run Argo on Katacoda (free)
Create Kubernetes cluster via Katacoda in browser
https://www.katacoda.com/courses/kubernetes/launch-single-node-cluster
Run only Step1 of Step4 and run the commands below
```
kubectl create ns argo
kubectl apply -n argo -f https://raw.githubusercontent.com/argoproj/argo-workflows/release-2.12.1/manifests/quick-start-minimal.yaml
kubectl patch svc argo-server -n argo -p '{"spec": {"type": "LoadBalancer", "externalIPs":["192.1.1.1"]}}'
kubectl get svc -n argo argo-server
```
Use externalIPs as your machine's IP Address
Resuls for argo-server service
```
$ kubectl get svc -n argo argo-server
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
argo-server LoadBalancer 111.22.33.44 192.1.1.1 2746:31513/TCP 42s
```
Click on plus (+) icon and Click "Select port to view on Host 1"
Set 31513 as the port in page "Web Preview Port Selector" and Click on "Display Port"
https://2886795277-31513-ollie07.environments.katacoda.com/
This would open argo-server.
### Create Workflow Template
Publish Catalog Workflow Template
Copy contents from [catalogworkflow.yaml](resources/catalogworkflow.yaml) and create template as follows:
### Initiate A Catalog Workflow via API
Run CatalogWF App
Run Argo-Workflow (local or remote)
Find base url of Argo Server (Argo UI) for e.g. http://localhost:2746
Execute Initiate Catalog Workflow Request as follows
```
{
"baseurl": "http://localhost:2746",
"workflowtemplate": {
"namespace": "argo",
"resourceKind": "WorkflowTemplate",
"resourceName": "catalog-workflow-step-g9rv6",
"submitOptions": {
"entryPoint": "catalogprocess",
"parameters": [
"catalogname=test-workflow-name"
]
}
}
}
```
User would need to change resourceName as for my current deployment name of the template is
"catalog-workflow-step-g9rv6"
#### Submit Workflow request directly to Argo Workflow APIs using CURL
```
curl 'http://localhost:2746/api/v1/workflows/argo/submit' \
-H 'Content-Type: application/json' \
-H 'Accept: */*' \
--data-raw '{"namespace":"argo","resourceKind":"WorkflowTemplate","resourceName":"catalog-workflow-step-g9rv6","submitOptions":{"entryPoint":"catalogprocess","parameters":["catalogname=test-workflow-name"]}}'
```
#### Submit Workflow request directly to Argo Workflow APIs using Argo Server (Argo UI)
### Generate/Update Swaggo Document
```
swag init
```