Neo4j is a popular graph database that is well-suited for storing and querying connected data. Google Kubernetes Engine (GKE) is a managed Kubernetes service that makes it easy to deploy and manage containerized applications. In this article, we’ll walk through the steps involved in deploying a Neo4j cluster on GKE.
What is Google Kubernetes Engine (GKE)?
GKE provides a managed environment for deploying, managing, and scaling your containerized applications using Kubernetes. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. GKE simplifies the process of setting up and maintaining a Kubernetes cluster by handling the underlying infrastructure and providing features like:
- Automated cluster provisioning: GKE automatically provisions and manages the underlying virtual machines and networking required for your Kubernetes cluster.
- Scalability and high availability: GKE allows you to easily scale your applications up or down based on demand and ensures high availability through features like auto-scaling and node auto-repair.
- Integration with other Google Cloud services: GKE integrates seamlessly with other Google Cloud services like Cloud Logging, Cloud Monitoring, and Cloud Storage.
What are Helm Charts?
Helm is a package manager for Kubernetes that simplifies the deployment and management of applications. Helm Charts are packages of pre-configured Kubernetes resources that can be easily deployed with a single command. They provide a templating engine that allows you to customize the deployment based on your specific needs.
Prerequisites
- A Google Cloud Project with billing enabled
- A GKE cluster with at least 3 nodes
- Basic understanding of Kubernetes concepts like pods, deployments, and services
Configure the Neo4j Helm chart repository
Add the Neo4j Helm chart repository.
helm repo add neo4j https://helm.neo4j.com/neo4j
Update the repository:
helm repo update
Check for the available Neo4j Helm charts
helm search repo neo4j/ --versions | grep 5.26.1
The output should be similar to the following:
neo4j/neo4j 5.26.1 5.26.1 Neo4j is the world's leading graph database
neo4j/neo4j-admin 5.26.1 5.26.1 Neo4j is the world's leading graph database
neo4j/neo4j-headless-service 5.26.1 - Neo4j is the world's leading graph database
neo4j/neo4j-persistent-volume 5.26.1 - Sets up persistent disks suitable for a Neo4j H...
neo4j/neo4j-reverse-proxy 5.26.1 5.26.1 Sets up an http server and a reverse proxy for ...
Deploy a standalone instance
This quickstart guide walks through the basics of deploying a Neo4j standalone instance to a cloud or a local Kubernetes cluster using the Neo4j Helm chart.
Environment-specific prerequisites
On the GCP console open the Cloud Shell and click on Authorise:
All the shell commands in this guide assume that the GCP Project, compute zone, and region to use have been set using the CLOUDSDK_CORE_PROJECT, CLOUDSDK_COMPUTE_ZONE, and CLOUDSDK_COMPUTE_REGION environment variables, for example:
export CLOUDSDK_CORE_PROJECT="my-neo4j-project"
export CLOUDSDK_COMPUTE_ZONE="europe-west2-a"
export CLOUDSDK_COMPUTE_REGION="europe-west2"
If you do not have a Google Kubernetes Engine (GKE) cluster, you can create a single-node one using:
gcloud container clusters create my-neo4j-gke-cluster --num-nodes=1 --machine-type "e2-standard-2"
e2-standard-2 is the minimum instance type required for running the examples of this startup guide on GKE.
Configure kubectl to use your GKE cluster using:
gcloud container clusters get-credentials my-neo4j-gke-cluster
Fetching cluster endpoint and auth data.
kubeconfig entry generated for my-neo4j-gke-cluster.
Create a values.yaml file
Select the tab as per your Kubernetes environment and using the provided example, create a YAML file for your standalone instance.
neo4j:
name: my-standalone
resources:
cpu: "0.5"
memory: "2Gi"
# Uncomment to set the initial password
#password: "my-initial-password"
# Uncomment to use enterprise edition
#edition: "enterprise"
#acceptLicenseAgreement: "yes"
volumes:
data:
mode: "dynamic"
dynamic:
# In GKE;
# * premium-rwo provisions SSD disks (recommended)
# * standard-rwo provisions balanced SSD-backed disks
# * standard provisions HDD disks
storageClassName: premium-rwo
Install a Neo4j standalone instance
Install Neo4j using the deployment values.yaml file, created in Create a value.yaml file, and the neo4j/neo4j Helm chart:
Create a neo4j namespace and configure it to be used in the current context:
kubectl create namespace neo4j
kubectl config set-context --current --namespace=neo4j
Install the Neo4j standalone server:
helm install my-neo4j-release neo4j/neo4j --namespace neo4j -f my-neo4j.values.yaml
Example output
LAST DEPLOYED: Wed Oct 26 15:19:17 2022
NAMESPACE: neo4j
STATUS: deployed
REVISION: 1
TEST SUITE: None
NOTES:
Thank you for installing neo4j.
Your release "my-neo4j-release" has been installed in namespace "neo4j".
The neo4j user's password has been set to "my-password".To view the progress of the rollout try:
$ kubectl --namespace "neo4j" rollout status --watch --timeout=600s statefulset/my-neo4j-release
Once rollout is complete you can log in to Neo4j at "neo4j://my-neo4j-release.neo4j.svc.cluster.local:7687". Try:
$ kubectl run --rm -it --namespace "neo4j" --image "neo4j:5.1.0" cypher-shell \
-- cypher-shell -a "neo4j://my-neo4j-release.neo4j.svc.cluster.local:7687" -u neo4j -p "my-password"
Graphs are everywhere!
Run the kubectl rollout command provided in the output of helm install to watch the Neo4j’s rollout until it is complete.
kubectl rollout status --watch --timeout=600s statefulset/my-neo4j-release
Verify the installation
kubectl get statefulsets
NAME READY AGE
my-neo4j-release 1/1 2m11s
Check that the pod is Running:
kubectl get pods
NAME READY STATUS RESTARTS AGE
my-neo4j-release-0 1/1 Running 0 16m
Check that the pod logs look OK:
kubectl exec my-neo4j-release-0 -- tail -n50 /logs/neo4j.log
2022-10-26 14:19:51.728+0000 INFO Command expansion is explicitly enabled for configuration
2022-10-26 14:19:51.733+0000 WARN Unrecognized setting. No declared setting with name: server.panic.shutdown_on_panic.
2022-10-26 14:19:51.749+0000 INFO Starting...
2022-10-26 14:19:53.062+0000 INFO This instance is ServerId{cb9f2f3c} (cb9f2f3c-cd70-40b1-ac8e-13d9c4d26173)
2022-10-26 14:19:54.970+0000 INFO ======== Neo4j 5.1.0 ========
2022-10-26 14:19:59.528+0000 INFO Bolt enabled on 0.0.0.0:7687.
2022-10-26 14:20:01.523+0000 INFO Remote interface available at http://localhost:7474/
2022-10-26 14:20:01.530+0000 INFO id: EF772BAFBDCD3C4921D00A5707C88D6EDE514915DBCC7134E8704AFA15DC19C8
2022-10-26 14:20:01.530+0000 INFO name: system
2022-10-26 14:20:01.531+0000 INFO creationDate: 2022-10-26T14:19:56.631Z
2022-10-26 14:20:01.531+0000 INFO Started.
Check that the services look OK:
kubectl get services
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/my-neo4j-release-lb-neo4j LoadBalancer 10.36.5.34 34.105.179.172 7474:30288/TCP,7687:30584/TCP 14m
service/kubernetes ClusterIP 10.36.0.1 443/TCP 22h
service/my-neo4j-release ClusterIP 10.36.11.18 7687/TCP,7474/TCP 14m
service/my-neo4j-release-admin ClusterIP 10.36.3.238 6362/TCP,7687/TCP,7474/TCP 14m
Use the external IP of the LoadBalancer to access Neo4j from an application outside the Kubernetes cluster. For more information, see Applications accessing Neo4j from outside Kubernetes.
- In a web browser, open the Neo4j Browser at http://EXTERNAL_IP:7474/browser.
- Use the automatically-generated password (as printed in the output of the helm install command) or the one you have configured in the my-neo4j.values.yaml file.
Conclusion
Deploying Neo4j on GKE provides a scalable and reliable platform for running your graph database. By using Helm, you can simplify the deployment process and manage your Neo4j cluster with ease.
Additional Resources
- Neo4j Helm Chart: https://github.com/neo4j/neo4j-helm
- Neo4j Documentation: https://neo4j.com/docs/
- Google Kubernetes Engine Documentation: https://cloud.google.com/kubernetes-engine/docs/