Add mlflow-kubeserve deployment

Closes #2

deployment.yaml

+apiVersion: kubeserve.sauerburger.dev/v1alpha1
+kind: ModelDeployment
+metadata:
+  name: movie-recommender
+spec:
+  model: models:/movie-recommender/1
+  s3:
+    url: https://s3.ds.sit-servers.net/
+    secretName: s3apikey
+  registry:
+    url: https://mlflow.ds.sit-servers.net/
+    secretName: mlflowbasicauth
+  docker:
+    imageBaseName: gitlab.sauerburger.com:5049/frank/movie-recommender
+    secretName: movie-recommender-token
+---
+apiVersion: v1
+kind: Service
+metadata:
+  name: movie-recommender-service
+spec:
+  ports:
+  - port: 8080
+    protocol: TCP
+    targetPort: 8080
+  selector:
+    app: kubeserve
+    modeldeployment_cr: movie-recommender
+---
+apiVersion: networking.k8s.io/v1
+kind: Ingress
+metadata:
+  annotations:
+    cert-manager.io/cluster-issuer: "letsencrypt-production"
+    kubernetes.io/ingress.class: nginx
+  name: "movie-recommender"
+spec:
+  rules:
+  - host: "movie-recommender.ds.sit-servers.net"
+    http:
+      paths:
+      - path: "/invocations"
+        pathType: Prefix
+        backend:
+          service:
+            name: "movie-recommender-service"
+            port:
+              number: 8080
+  tls:
+  - hosts:
+    - "movie-recommender.ds.sit-servers.net"
+    secretName: movie-recommender-tls-secret