chatbot-rag-app: adds Kubernetes manifest and instructions

Signed-off-by: Adrian Cole <[email protected]>

Author: codefromthecrypt

docker/docker-compose-elastic.yml

@@ -2,7 +2,7 @@ name: elastic-stack
 
 services:
   elasticsearch:
-    image: docker.elastic.co/elasticsearch/elasticsearch:8.17.0
+    image: docker.elastic.co/elasticsearch/elasticsearch:8.17.2
     container_name: elasticsearch
     ports:
       - 9200:9200
@@ -30,7 +30,7 @@ services:
     depends_on:
       elasticsearch:
         condition: service_healthy
-    image: docker.elastic.co/elasticsearch/elasticsearch:8.17.0
+    image: docker.elastic.co/elasticsearch/elasticsearch:8.17.2
     container_name: elasticsearch_settings
     restart: 'no'
     command: >
@@ -42,7 +42,7 @@ services:
       '
 
   kibana:
-    image: docker.elastic.co/kibana/kibana:8.17.0
+    image: docker.elastic.co/kibana/kibana:8.17.2
     container_name: kibana
     depends_on:
       elasticsearch_settings:
@@ -66,7 +66,7 @@ services:
       interval: 1s
 
   apm-server:
-    image: docker.elastic.co/apm/apm-server:8.17.0
+    image: docker.elastic.co/apm/apm-server:8.17.2
     container_name: apm-server
     depends_on:
       elasticsearch:

example-apps/chatbot-rag-app/README.md

@@ -69,6 +69,49 @@ Clean up when finished, like this:
 docker compose down
 ```
 
+### Run with Kubernetes
+
+Our Kubernetes manifest will run similar to Docker, using host networking by
+default to eliminate the need to forward ports or use special hostnames to
+access localhost. Unless you change [k8s-manifest.yml](k8s-manifest.yml), the
+app chatbot-rag-app will do the following:
+* The init-container named "ingest-data" ingests data into elasticsearch
+* The container named "api-frontend", listens on http://localhost:4000
+
+**Double-check you have a `.env` file with all your variables set first!**
+
+Then, import your .env file as a configmap like this:
+```bash
+kubectl create configmap chatbot-rag-app-env --from-env-file=.env
+```
+
+If you are using Vertex AI, make a secret for authentication:
+```bash
+kubectl create secret generic gcloud-credentials \
+  --from-file=application_default_credentials.json=$HOME/.config/gcloud/application_default_credentials.json
+```
+
+Now, apply the manifest:
+```bash
+kubectl apply -f k8s-manifest.yml
+```
+
+*Note*: First time creating the index can fail on timeout. You can verify that
+like this:
+```bash
+kubectl logs -l app=chatbot-rag-app -c ingest-data
+```
+
+If you need to retry, do a rolling restart like this:
+```bash
+kubectl rollout restart deployment/chatbot-rag-app
+```
+
+Clean up when finished, like this:
+```bash
+kubectl delete -f k8s-manifest.yml
+```
+
 ### Run locally
 
 If you want to run this example with Python and Node.js, you need to do a few

example-apps/chatbot-rag-app/k8s-manifest.yml

@@ -0,0 +1,61 @@
+---
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: chatbot-rag-app
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: chatbot-rag-app
+  template:
+    metadata:
+      labels:
+        app: chatbot-rag-app
+    spec:
+      # Simplify networking so that it can look for elasticsearch on localhost
+      hostNetwork: true
+      # The below will recreate your secret based on the gcloud credentials file
+      # kubectl create secret generic gcloud-credentials \
+      #  --from-file=application_default_credentials.json=$HOME/.config/gcloud/application_default_credentials.json
+      volumes:
+        - name: gcloud-credentials
+          secret:
+            secretName: gcloud-credentials
+      initContainers:
+      - name: ingest-data
+        image: &image ghcr.io/elastic/elasticsearch-labs/chatbot-rag-app:latest
+        imagePullPolicy: &imagePullPolicy IfNotPresent
+        args: ["flask", "create-index"]
+        env:
+          - name: FLASK_APP
+            value: api/app.py
+        # The below will recreate your configmap based on the .env file
+        # kubectl create configmap chatbot-rag-app-env --from-env-file=.env
+        envFrom: &envFrom
+          - configMapRef:
+              name: chatbot-rag-app-env
+        volumeMounts: &volumeMounts
+          - name: gcloud-credentials
+            mountPath: /root/.config/application_default_credentials.json
+            readOnly: true
+      containers:
+      - name: api-frontend
+        image: *image
+        imagePullPolicy: *imagePullPolicy
+        ports:
+          - containerPort: 4000
+        envFrom: *envFrom
+        volumeMounts: *volumeMounts
+---
+apiVersion: v1
+kind: Service
+metadata:
+  name: api
+spec:
+  selector:
+    app: chatbot-rag-app
+  ports:
+    - protocol: TCP
+      port: 4000
+      targetPort: 4000