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Using Kubernetes

The following section covers running Dgraph with Kubernetes. We have tested Dgraph with Kubernetes versions 1.14 to 1.16 on GKE and versions 1.14 to 1.17 on EKS.

Note These instructions are for running Dgraph alpha service without TLS configuration. Instructions for running Dgraph alpha service with TLS refer TLS instructions.
  • Install kubectl which is used to deploy and manage applications on kubernetes.
  • Get the Kubernetes cluster up and running on a cloud provider of your choice.
    • For Amazon EKS, you can use eksctl to quickly provision a new cluster. If you are new to this, Amazon has an article Getting started with eksctl.
    • For Google Cloud GKE, you can use Google Cloud SDK and the gcloud container clusters create command to quickly provision a new cluster.

Verify that you have your cluster up and running using kubectl get nodes. If you used eksctl or gcloud container clusters create with the default options, you should have 2-3 worker nodes ready.

On Amazon EKS, you would see something like this:

➜  kubernetes git:(master) ✗ kubectl get nodes
NAME                                          STATUS   ROLES    AGE   VERSION
<aws-ip-hostname>.<region>.compute.internal   Ready    <none>   1m   v1.15.11-eks-af3caf
<aws-ip-hostname>.<region>.compute.internal   Ready    <none>   1m   v1.15.11-eks-af3caf

On Google Cloud GKE, you would see something like this:

➜  kubernetes git:(master) ✗ kubectl get nodes
NAME                                       STATUS   ROLES    AGE   VERSION
gke-<cluster-name>-default-pool-<gce-id>   Ready    <none>   41s   v1.14.10-gke.36
gke-<cluster-name>-default-pool-<gce-id>   Ready    <none>   40s   v1.14.10-gke.36
gke-<cluster-name>-default-pool-<gce-id>   Ready    <none>   41s   v1.14.10-gke.36

Single Server

Once your Kubernetes cluster is up, you can use dgraph-single.yaml to start a Zero, Alpha, and Ratel UI services.

Deploy Single Server

From your machine, run the following command to start a StatefulSet that creates a single Pod with Zero, Alpha, and Ratel UI running in it.

kubectl create --filename https://raw.githubusercontent.com/dgraph-io/dgraph/master/contrib/config/kubernetes/dgraph-single/dgraph-single.yaml

Output:

service/dgraph-public created
statefulset.apps/dgraph created

Verify Single Server

Confirm that the pod was created successfully.

kubectl get pods

Output:

NAME       READY     STATUS    RESTARTS   AGE
dgraph-0   3/3       Running   0          1m
Tip You can check the logs for the containers in the pod using kubectl logs --follow dgraph-0 <container_name>. For example, try kubectl logs --follow dgraph-0 alpha for server logs.

Test Single Server Setup

Port forward from your local machine to the pod

kubectl port-forward pod/dgraph-0 8080:8080
kubectl port-forward pod/dgraph-0 8000:8000

Go to http://localhost:8000 and verify Dgraph is working as expected.

Remove Single Server Resources

Delete all the resources

kubectl delete --filename https://raw.githubusercontent.com/dgraph-io/dgraph/master/contrib/config/kubernetes/dgraph-single/dgraph-single.yaml
kubectl delete persistentvolumeclaims --selector app=dgraph

HA Cluster Setup Using Kubernetes

This setup allows you to run 3 Dgraph Alphas and 3 Dgraph Zeros. We start Zero with --replicas 3 flag, so all data would be replicated on 3 Alphas and form 1 alpha group.

Note Ideally you should have at least three worker nodes as part of your Kubernetes cluster so that each Dgraph Alpha runs on a separate worker node.

Validate Kubernetes Cluster for HA

Check the nodes that are part of the Kubernetes cluster.

kubectl get nodes

Output for Amazon EKS:

NAME                                          STATUS   ROLES    AGE   VERSION
<aws-ip-hostname>.<region>.compute.internal   Ready    <none>   1m   v1.15.11-eks-af3caf
<aws-ip-hostname>.<region>.compute.internal   Ready    <none>   1m   v1.15.11-eks-af3caf
<aws-ip-hostname>.<region>.compute.internal   Ready    <none>   1m   v1.15.11-eks-af3caf

Output for Google Cloud GKE

NAME                                       STATUS   ROLES    AGE   VERSION
gke-<cluster-name>-default-pool-<gce-id>   Ready    <none>   41s   v1.14.10-gke.36
gke-<cluster-name>-default-pool-<gce-id>   Ready    <none>   40s   v1.14.10-gke.36
gke-<cluster-name>-default-pool-<gce-id>   Ready    <none>   41s   v1.14.10-gke.36

Once your Kubernetes cluster is up, you can use dgraph-ha.yaml to start the cluster.

Deploy Dgraph HA Cluster

From your machine, run the following command to start the cluster.

kubectl create --filename https://raw.githubusercontent.com/dgraph-io/dgraph/master/contrib/config/kubernetes/dgraph-ha/dgraph-ha.yaml

Output:

service/dgraph-zero-public created
service/dgraph-alpha-public created
service/dgraph-ratel-public created
service/dgraph-zero created
service/dgraph-alpha created
statefulset.apps/dgraph-zero created
statefulset.apps/dgraph-alpha created
deployment.apps/dgraph-ratel created

Verify Dgraph HA Cluster

Confirm that the pods were created successfully.

It may take a few minutes for the pods to come up.

kubectl get pods

Output:

NAME                  READY   STATUS    RESTARTS   AGE
dgraph-alpha-0        1/1     Running   0          6m24s
dgraph-alpha-1        1/1     Running   0          5m42s
dgraph-alpha-2        1/1     Running   0          5m2s
dgraph-ratel-<pod-id> 1/1     Running   0          6m23s
dgraph-zero-0         1/1     Running   0          6m24s
dgraph-zero-1         1/1     Running   0          5m41s
dgraph-zero-2         1/1     Running   0          5m6s
Tip You can check the logs for the containers in the pod using kubectl logs --follow dgraph-alpha-0 and kubectl logs --follow dgraph-zero-0.

Test Dgraph HA Cluster Setup

Port forward from your local machine to the pod

kubectl port-forward service/dgraph-alpha-public 8080:8080
kubectl port-forward service/dgraph-ratel-public 8000:8000

Go to http://localhost:8000 and verify Dgraph is working as expected.

Note You can also access the service on its External IP address.

Delete Dgraph HA Cluster Resources

Delete all the resources

kubectl delete --filename https://raw.githubusercontent.com/dgraph-io/dgraph/master/contrib/config/kubernetes/dgraph-ha/dgraph-ha.yaml
kubectl delete persistentvolumeclaims --selector app=dgraph-zero
kubectl delete persistentvolumeclaims --selector app=dgraph-alpha

Using Helm Chart

Once your Kubernetes cluster is up, you can make use of the Helm chart present in our official helm repository here to bring up a Dgraph cluster.

Note The instructions below are for Helm versions >= 3.x.

Installing the Chart

To add the Dgraph helm repository:

helm repo add dgraph https://charts.dgraph.io

To install the chart with the release name my-release:

helm install my-release dgraph/dgraph

The above command will install a recent version of the dgraph docker image. You can set the version an explicit version, such as:

helm install my-release dgraph/dgraph --set image.tag="v1.2.6"
Warning When configuring dgraph image tag, be careful not to use latest or master in a production environment. These tags may have the dgraph version change, causing a mixed version dgraph cluster that can lead to an outage and potential data loss.

Dgraph Configuration Files

You can supply a dgraph config files (see Config) for alpha and zero with Helm chart configuration values:

# my-config-values.yaml
alpha:
  configFile:
    config.yaml: |
      alsologtostderr: true
      badger:
        compression_level: 3
        tables: mmap
        vlog: mmap
      postings: /dgraph/data/p
      wal: /dgraph/data/w
      lru_mb: 2048
zero:
  configFile:
    config.yaml: |
      alsologtostderr: true
      wal: /dgraph/data/zw

And then install with alpha and zero configuration using this:

helm install my-release dgraph/dgraph --values my-config-values.yaml

Exposing Alpha and Ratel Services

By default zero and alpha services are exposed only within the kubernetes cluster as kubernetes service type ClusterIP.

In order to expose the alpha service and ratel service publicly you can use kubernetes service type LoadBalancer or an Ingress resource.

LoadBalancer (Public Internet)

To use an external load balancer, set the service type to LoadBalancer.

Note For security purposes we recommend limiting access to any public endpoints, such as using a white list.

You can expose alpha service to the Internet as follows:

helm install my-release dgraph/dgraph --set alpha.service.type="LoadBalancer"

Similarly, you can expose alpha and ratel service to the Internet as follows:

helm install my-release dgraph/dgraph --set alpha.service.type="LoadBalancer" --set ratel.service.type="LoadBalancer"
LoadBalancer (Private Internal Network)

An external load balancer can be configured to face internally to a private subnet rather the public Internet. This way it can be accessed securely by clients on the same network, through a VPN, or from a jump server. In Kubernetes, this is often configured through service annotations by the provider. Here’s a small list of annotations from cloud providers:

Provider Documentation Reference Annotation
AWS Amazon EKS: Load Balancing service.beta.kubernetes.io/aws-load-balancer-internal: "true"
Azure AKS: Internal Load Balancer service.beta.kubernetes.io/azure-load-balancer-internal: "true"
Google Cloud GKE: Internal Load Balancing cloud.google.com/load-balancer-type: "Internal"

As an example, using Amazon EKS as the provider, you could create a Helm chart configuration values like this below:

# my-config-values.yaml
alpha:
  service:
    type: LoadBalancer
    annotations:
      service.beta.kubernetes.io/aws-load-balancer-internal: "true"
ratel:
  service:
    type: LoadBalancer
    annotations:
      service.beta.kubernetes.io/aws-load-balancer-internal: "true"

And then expose alpha and ratel services privately:

helm install my-release dgraph/dgraph --values my-config-values.yaml
Ingress Resource

You can expose alpha and ratel using an ingress resource that can route traffic to service resources. Before using this option you may need to install an ingress controller first, as is the case with AKS and EKS, while in the case of GKE, this comes bundled with a default ingress controller. When routing traffic based on the hostname, you may want to integrate an addon like ExternalDNS so that DNS records can be registered automatically when deploying dgraph.

As an examples, you can configure a single ingress resource that uses ingress-nginx for alpha and ratel services, by creating Helm chart configuration values like this below:

# my-config-values.yaml
global:
  ingress:
    enabled: false
    annotations:
      kubernetes.io/ingress.class: nginx
    ratel_hostname: "ratel.<my-domain-name>"
    alpha_hostname: "alpha.<my-domain-name>"

And then expose alpha and ratel services through an ingress:

helm install my-release dgraph/dgraph --values my-config-values.yaml

Afterward you can run kubectl get ingress to see the status and access these through their hostname, such as http://alpha.<my-domain-name> and http://ratel.<my-domain-name>

Tip Ingress controllers will likely have an option to configure access for private internal networks. Consult documentation from the ingress controller provider for further information.

Upgrading the Chart

You can update your cluster configuration by updating the configuration of the Helm chart. Dgraph is a stateful database that requires some attention on upgrading the configuration carefully in order to update your cluster to your desired configuration.

In general, you can use helm upgrade to update the configuration values of the cluster. Depending on your change, you may need to upgrade the configuration in multiple steps following the steps below.

Upgrade to HA cluster setup

To upgrade to an HA cluster setup, ensure that the shard replication setting is more than 1. When zero.shardReplicaCount is not set to an HA configuration (3 or 5), follow the steps below:

  1. Set the shard replica flag on the Zero node group. For example: zero.shardReplicaCount=3.
  2. Next, run the Helm upgrade command to restart the Zero node group:

    helm upgrade my-release dgraph/dgraph [options]
    
  3. Now set the Alpha replica count flag. For example: alpha.replicaCount=3.

  4. Finally, run the Helm upgrade command again:

    helm upgrade my-release dgraph/dgraph [options]
    

Deleting the Chart

Delete the Helm deployment as normal

helm delete my-release

Deletion of the StatefulSet doesn’t cascade to deleting associated PVCs. To delete them:

kubectl delete pvc --selector release=my-release

Configuration

The latest configuration settings can be found:

Monitoring in Kubernetes

Dgraph exposes prometheus metrics to monitor the state of various components involved in the cluster, this includes dgraph alpha and zero.

Below are instructions to setup Prometheus monitoring for your cluster. This solution has the following parts:

  • prometheus-operator - a Kubernetes operator to install and configure Prometheus and Alert Manager.
  • Prometheus - the service that will scrape Dgraph for metrics
  • AlertManager - the service that will trigger alerts to a service (Slack, PagerDuty, etc) that you specify based on metrics exceeding threshold specified in Alert rules.
  • Grafana - optional visualization solution that will use Prometheus as a source to create dashboards.

Installation through Manifests

Follow the below mentioned steps to setup prometheus monitoring for your cluster.

Install Prometheus operator

kubectl apply --filename https://raw.githubusercontent.com/coreos/prometheus-operator/release-0.34/bundle.yaml

Ensure that the instance of prometheus-operator has started before continuing.

$ kubectl get deployments prometheus-operator
NAME                  DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
prometheus-operator   1         1         1            1           3m

Install Prometheus

  • Apply prometheus manifest present here.

    $ kubectl apply --filename prometheus.yaml
    
    serviceaccount/prometheus-dgraph-io created
    clusterrole.rbac.authorization.k8s.io/prometheus-dgraph-io created
    clusterrolebinding.rbac.authorization.k8s.io/prometheus-dgraph-io created
    servicemonitor.monitoring.coreos.com/alpha.dgraph-io created
    servicemonitor.monitoring.coreos.com/zero-dgraph-io created
    prometheus.monitoring.coreos.com/dgraph-io created
    

To view prometheus UI locally run:

kubectl port-forward prometheus-dgraph-io-0 9090:9090

The UI is accessible at port 9090. Open http://localhost:9090 in your browser to play around.

Registering Alerts and Installing Alert Manager

To register alerts from dgraph cluster with your prometheus deployment follow the steps below:

  • Create a kubernetes secret containing alertmanager configuration. Edit the configuration file present here with the required reciever configuration including the slack webhook credential and create the secret.

You can find more information about alertmanager configuration here.

$ kubectl create secret generic alertmanager-alertmanager-dgraph-io \
    --from-file=alertmanager.yaml=alertmanager-config.yaml

$ kubectl get secrets
NAME                                            TYPE                 DATA   AGE
alertmanager-alertmanager-dgraph-io             Opaque               1      87m
  • Apply the alertmanager along with alert-rules manifest to use the default configured alert configuration. You can also add custom rules based on the metrics exposed by dgraph cluster similar to alert-rules manifest.

    $ kubectl apply --filename alertmanager.yaml
    alertmanager.monitoring.coreos.com/alertmanager-dgraph-io created
    service/alertmanager-dgraph-io created
    
    $ kubectl apply --filename alert-rules.yaml
    prometheusrule.monitoring.coreos.com/prometheus-rules-dgraph-io created
    

Install Using Helm Chart

There are Helm chart values that will install Prometheus, Alert Manager, and Grafana.

You will first need to add the prometheus-operator Helm chart:

$ helm repo add stable https://kubernetes-charts.storage.googleapis.com

Afterward you will want to copy the Helm chart values present here and edit them as appropriate, such as adding endpoints, adding alert rules, adjusting alert manager configuration, adding Grafana dashboard, etc.

Once ready, install this with the following:

$ helm install my-prometheus-release \
  --values dgraph-prometheus-operator.yaml \
  --set grafana.adminPassword='<put-secret-password-here>' \
  stable/prometheus-operator

NOTE: For security best practices, we want to keep secrets, such as the Grafana password outside of general configuration, so that it is not accidently checked into anywhere. You can supply it through the command line, or create a seperate secrets.yaml that is never checked into a code repository:

grafana:
  adminPassword: <put-secret-password-here>

Then you can install this in a similar fashion:

$ helm install my-prometheus-release \
  --values dgraph-prometheus-operator.yaml \
  --values secrets.yaml \
  stable/prometheus-operator

Adding Dgraph Kubernetes Grafana Dashboard

You can use the Grafana dashboard present here. You can import this dashboard and select the Prometheus data source installed earlier.

This will visualize all Dgraph Alpha and Zero Kubernetes Pods, using the regex pattern "/dgraph-.*-[0-9]*$/. This can be changed by through the dashboard configuration and selecting the variable Pod. This might be desirable when you have had multiple releases, and only want to visualize the current release. For example, if you installed a new release my-release-3 with the Dgraph helm chart, you can change the regex pattern to "/my-release-3.*dgraph-.*-[0-9]*$/" for the Pod variable.

Kubernetes Storage

The Kubernetes configurations in the previous sections were configured to run Dgraph with any storage type (storage-class: anything). On the common cloud environments like AWS, GCP, and Azure, the default storage type are slow disks like hard disks or low IOPS SSDs. We highly recommend using faster disks for ideal performance when running Dgraph.

Local storage

The AWS storage-optimized i-class instances provide locally attached NVMe-based SSD storage which provide consistent very high IOPS. The Dgraph team uses i3.large instances on AWS to test Dgraph.

You can create a Kubernetes StorageClass object to provision a specific type of storage volume which you can then attach to your Dgraph pods. You can set up your cluster with local SSDs by using Local Persistent Volumes. This Kubernetes feature is in beta at the time of this writing (Kubernetes v1.13.1). You can first set up an EC2 instance with locally attached storage. Once it is formatted and mounted properly, then you can create a StorageClass to access it.:

apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: <your-local-storage-class-name>
provisioner: kubernetes.io/no-provisioner
volumeBindingMode: WaitForFirstConsumer

Currently, Kubernetes does not allow automatic provisioning of local storage. So a PersistentVolume with a specific mount path should be created:

apiVersion: v1
kind: PersistentVolume
metadata:
  name: <your-local-pv-name>
spec:
  capacity:
    storage: 475Gi
  volumeMode: Filesystem
  accessModes:
  - ReadWriteOnce
  persistentVolumeReclaimPolicy: Delete
  storageClassName: <your-local-storage-class-name>
  local:
    path: /data
  nodeAffinity:
    required:
      nodeSelectorTerms:
      - matchExpressions:
        - key: kubernetes.io/hostname
          operator: In
          values:
          - <node-name>

Then, in the StatefulSet configuration you can claim this local storage in .spec.volumeClaimTemplate:

kind: StatefulSet
...
 volumeClaimTemplates:
  - metadata:
      name: datadir
    spec:
      accessModes:
      - ReadWriteOnce
      storageClassName: <your-local-storage-class-name>
      resources:
        requests:
          storage: 500Gi

You can repeat these steps for each instance that’s configured with local node storage.

Non-local persistent disks

EBS volumes on AWS and PDs on GCP are persistent disks that can be configured with Dgraph. The disk performance is much lower than locally attached storage but can be sufficient for your workload such as testing environments.

When using EBS volumes on AWS, we recommend using Provisioned IOPS SSD EBS volumes (the io1 disk type) which provide consistent IOPS. The available IOPS for AWS EBS volumes is based on the total disk size. With Kubernetes, you can request io1 disks to be provisioned with this config with 50 IOPS/GB using the iopsPerGB parameter:

kind: StorageClass
apiVersion: storage.k8s.io/v1
metadata:
  name: <your-storage-class-name>
provisioner: kubernetes.io/aws-ebs
parameters:
  type: io1
  iopsPerGB: "50"
  fsType: ext4

Example: Requesting a disk size of 250Gi with this storage class would provide 12.5K IOPS.

Removing a Dgraph Pod

In the event that you need to completely remove a pod (e.g., its disk got corrupted and data cannot be recovered), you can use the /removeNode API to remove the node from the cluster. With a Kubernetes StatefulSet, you’ll need to remove the node in this order:

  1. On the Zero leader, call /removeNode to remove the Dgraph instance from the cluster (see More about Dgraph Zero). The removed instance will immediately stop running. Any further attempts to join the cluster will fail for that instance since it has been removed.
  2. Remove the PersistentVolumeClaim associated with the pod to delete its data. This prepares the pod to join with a clean state.
  3. Restart the pod. This will create a new PersistentVolumeClaim to create new data directories.

When an Alpha pod restarts in a replicated cluster, it will join as a new member of the cluster, be assigned a group and an unused index from Zero, and receive the latest snapshot from the Alpha leader of the group.

When a Zero pod restarts, it must join the existing group with an unused index ID. The index ID is set with the --idx flag. This may require the StatefulSet configuration to be updated.

Kubernetes and Bulk Loader

You may want to initialize a new cluster with an existing data set such as data from the Dgraph Bulk Loader. You can use Init Containers to copy the data to the pod volume before the Alpha process runs.

See the initContainers configuration in dgraph-ha.yaml to learn more.