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Kubernetes
LangStream container images are available on the Github packages registry. A LangStream cluster is made up of the following images:
Connect to your GCP cluster:
gcloud container clusters get-credentials <langstream-cluster> --region us-east1 --project <project-name>
Fetching cluster endpoint and auth data.
Kubernetes v1.21.0-alpha+eabdbc0a40fe7efda92e10270f27b0a3485fb743
kubeconfig entry generated for langstream-cluster.
Connect to your Azure cluster:
az account set --subscription <subscription-name>
az aks get-credentials --resource-group k8s-resource-group --name dev
Merged "dev" as current context in /Users/mendon.kissling/.kube/config
Connect to your EKS cluster:
aws eks update-kubeconfig --region="us-east-2" --name="langstream-cluster"
Added new context arn:aws:eks:us-east-2:423019603865:cluster/langstream-cluster to /Users/mendon.kissling/.kube/config
Create a minikube cluster:
minikube start cpu="4"
Done! kubectl is now configured to use "minikube" cluster and "default" namespace by default
Add the LangStream chart repo to your Helm installation and update it to the latest version:
helm repo add langstream https://langstream.ai/charts
helm repo update langstream
This component stores the state of LangStream applications in an S3 API-compatible bucket or Azure blob.
Modify the values.yaml file you'll be deploying with to configure the external codeStorage component.
These values can be found in your storage provider's dashboard.
Azure:
codeStorage:
type: azure
configuration:
endpoint: https://<storage-account>.blob.core.windows.net
container: langstream
storage-account-name: <storage-account>
storage-account-key: <storage-account-key>
S3:
codeStorage:
type: s3
configuration:
access-key: <aws-access-key>
secret-key: <aws-secret-key>
Minio:
codeStorage:
type: s3
configuration:
endpoint: http://minio.minio-dev.svc.cluster.local:9000
access-key: minioadmin
secret-key: minioadmin
If you're using GKE Cloud Storage, see Simple migration from Amazon S3 to Cloud Storage for using the Cloud Storage API to interact with an S3 bucket.
kubectl apply -f https://raw.githubusercontent.com/LangStream/langstream/main/helm/examples/minio-dev.yaml
Install the LangStream Helm chart:
helm install langstream \
-n langstream \
--create-namespace \
--values values.yaml \
langstream/langstream
Result:
NAME: langstream
LAST DEPLOYED: Tue Nov 7 11:38:05 2023
NAMESPACE: langstream
STATUS: deployed
REVISION: 1
TEST SUITE: None
In your Kubernetes cluster, you should see four new pods deploy in the
langstream namespace. For more configuration options, see the Helm charts documentation.Install the Strimzi Kafka operator.
helm repo add strimzi https://strimzi.io/charts/
helm install strimzi-kafka strimzi/strimzi-kafka-operator
kubectl apply -f https://strimzi.io/examples/latest/kafka/kafka-persistent-single.yaml -n langstream
kafka.kafka.strimzi.io/my-cluster created
The Strimzi operator will create and watch a single-ZooKeeper Kafka cluster.
In your LangStream application's instance.yaml file, point the
bootstrap.servers to your new Kafka bootstrap server's address.instance:
streamingCluster:
type: "kafka"
configuration:
admin:
bootstrap.servers: my-cluster-kafka-bootstrap.langstream.svc.cluster.local:9092
For production deployments, set the bootstrap server address as a secret value for KAFKA_BOOTSTRAP_SERVERS. For more, see Secrets.
Control plane:
kubectl -n langstream port-forward svc/langstream-control-plane 8090:8090 &
API gateway:
kubectl -n langstream port-forward svc/langstream-api-gateway 8091:8091 &
You can instead open the control plane and API gateway ports in your Helm chart.
This example uses traefik for ingress.
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: control-plane
annotations:
kubernetes.io/ingress.class: "traefik"
spec:
rules:
- host: langstream.yourdomain.local # Replace with your actual domain or host
http:
paths:
backend:
service:
name: langstream-control-plane
port:
number: 8090
---
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: api-gateway
annotations:
kubernetes.io/ingress.class: "traefik"
spec:
rules:
- host: ws.langstream.yourdomain.local # Replace with your actual domain or host
http:
paths:
backend:
service:
name: langstream-api-gateway
port:
number: 8091
Run a sample application to test your new environment. For more on building LangStream applications, see Set up your development environment.
langstream apps deploy test -app sample-app/application -s sample-app/secrets.yaml -i sample-app/instance.yaml
packaging app: /Users/mendon.kissling/Documents/GitHub/LS Application/sample-app/application
app packaged
deploying application: test (1 KB)
application test deployed
To monitor deployment from the CLI, use
langstream apps get <app-name>.langstream-app-setup and langstream-runtime-deployer pods will deploy in the langstream-default namespace in your Kubernetes cluster. When these pods reach a Completed state, your application pod(s) will deploy.For integrating LangStream and your remote cluster into VSCode workflows, Install the VSCode extension and use the provided starter applications & agent snippets.