https://github.com/kumarvikas1/deploy-service
https://github.com/kumarvikas1/deploy-service
Last synced: 8 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/kumarvikas1/deploy-service
- Owner: kumarvikas1
- Created: 2022-06-28T14:55:03.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2022-07-02T14:29:10.000Z (almost 4 years ago)
- Last Synced: 2025-03-05T01:35:32.906Z (over 1 year ago)
- Language: Python
- Size: 16.6 KB
- Stars: 0
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# deploy-service
The service fetches the model artifact from model artifactory service[https://github.com/kumarvikas1/model-artifactory]
Run Locally
```
minikube start
eval $(minikube docker-env)
docker build -t deploy-service:1 .
cd kubernetes
kubectl apply -f rbac.yaml
kubectl apply -f deployment.yaml
```
Test-
You will need to update your hosts file for below host name
```
http://dev.xgboostdemo.com/deploy-service/xgboost-demo
```
You should have your model ready to be served using a random feature values
```
curl http://dev.xgboostdemo.com/sampling-service/xgboost-demo/predict
```
You can also send model input feature values
```
curl --location --request POST 'http://dev.xgboostdemo.com/sampling-service/xgboost-demo/predict' \
--header 'Content-Type: application/json' \
--data-raw '{
"features": [[0.4886530794542341, 0.9931183497579041, 0.5521141503801427]]
}'
```