JP aks deployment fix (#388)

* Change AKS deployment configuration

Deployment config changed from 1CPU/4GB to 0.5CPU/2GB so it fits a AKS created with default parameters

* Update custom_model.md

Co-authored-by: João Pedro Martins <lokijota@users.noreply.github.com>

diabetes_regression/scoring/deployment_config_aks.yml

@@ -7,8 +7,8 @@ autoScaler:
     targetUtilization: 70
 authEnabled: True
 containerResourceRequirements:
-    cpu: 1
-    memoryInGB: 4
+    cpu: 0.5
+    memoryInGB: 2
 appInsightsEnabled: True
 scoringTimeoutMs: 5000
 maxConcurrentRequestsPerContainer: 2

docs/custom_model.md

@@ -97,6 +97,7 @@ If you want to keep scoring:
 1. Update or replace `[project name]/scoring/score.py`
 1. Add any dependencies required by scoring to `[project name]/conda_dependencies.yml`
 1. Modify the test cases in the `ml_service/util/smoke_test_scoring_service.py` script to match the schema of the training features in your data
+1. Check and modify [project name]/scoring/deployment_config_aks.yml if AKS deployment is planned. The deployment configuration shall suit custom model as well as AKS cluster size.
 
 # Configure Custom Batch Scoring