Kubernetes
Make sure to set your desired Weaviate version.
This can be done through either explicitly setting it as part of the values.yaml
or through overwriting the default as outlined in the deployment step below.
If you are looking for a complete end-to-end tutorial on the topic, please the Weaviate Academy course on Weaviate on Kubernetes. The tutorial covers an end-to-end scenario of deploying Weaviate on Kubernetes with Minikube.
Requirements
- A recent Kubernetes Cluster (at least version 1.23).
- If you are in a development environment, consider using the kubernetes cluster that is built into Docker desktop. For more information, see the Docker documentation.
- The cluster needs to be able to provision
PersistentVolumes
throughPersistentVolumeClaims
. - No special file systems are required. Any file system that has a
ReadWriteOnce
access mode is sufficient. - Helm. To use Helm chart version
"v17.0.0"
, you must have Helm v3 or higher.
Weaviate Helm chart
To obtain and install the Weaviate chart on your Kubernetes cluster, take the following steps:
Verify tool setup and cluster access
# Check if helm is installed
helm version
# Make sure `kubectl` is configured correctly and you can access the cluster.
# For example, try listing the pods in the currently configured namespace.
kubectl get pods
Obtain the Helm Chart
Add the Weaviate helm repo that contains the Weaviate helm chart
helm repo add weaviate https://weaviate.github.io/weaviate-helm
Get the default values.yaml
configuration file from the Weaviate helm chart:
helm show values weaviate/weaviate > values.yaml
Modify values.yaml (as necessary)
The default values in values.yaml
may be sufficient. However, we recommend reviewing:
- The Weaviate version
- Modules to enable
- gRPC service configuration
In the values.yaml
file you can tweak the configuration to align it with your
setup. The yaml file is extensively documented to help you align the
configuration with your setup.
Out of the box, the configuration file is setup for:
- 1 Weaviate replica.
- Local models, such as
text2vec-transformers
,qna-transformers
orimg2vec-neural
are disabled by default. They can be enabled by setting the respectiveenabled
flag totrue
. grpcService
is disabled by default. If you want to use the gRPC API, set theenabled
flag totrue
and thetype
to the required type, such asLoadBalancer
. This decision to disable the gRPC service by default is made for backward compatibility, and as different setups might require different configurations.
See the resource requests and limits in the example values.yaml
. You can
adjust them based on your expected load and the resources available on the
cluster.
Authentication and authorization
An example configuration for authentication is shown below.
authentication:
apikey:
enabled: true
allowed_keys:
- readonly-key
- secr3tk3y
users:
- readonly@example.com
- admin@example.com
anonymous_access:
enabled: false
oidc:
enabled: true
issuer: https://auth.wcs.api.weaviate.io/auth/realms/SeMI
username_claim: email
groups_claim: groups
client_id: wcs
authorization:
admin_list:
enabled: true
users:
- someuser@weaviate.io
- admin@example.com
readonly_users:
- readonly@example.com
In this example, the key readonly-key
will authenticate a user as the readonly@example.com
identity, and secr3tk3y
will authenticate a user as admin@example.com
.
OIDC authentication is also enabled, with WCS as the token issuer/identity provider. Thus, users with WCS accounts could be authenticated. This configuration sets someuser@weaviate.io
as an admin user, so if someuser@weaviate.io
were to authenticate, they will be given full (read and write) privileges.
For further, general documentation on authentication and authorization configuration, see:
Deploy (install the Helm chart)
You can deploy the helm charts as follows:
# Create a Weaviate namespace
kubectl create namespace weaviate
# Deploy
helm upgrade --install \
"weaviate" \
weaviate/weaviate \
--namespace "weaviate" \
--values ./values.yaml
The above assumes that you have permissions to create a new namespace. If you
have only namespace-level permissions, you can skip creating a new
namespace and adjust the namespace argument on helm upgrade
according to the
name of your pre-configured namespace.
Optionally, you can provide the --create-namespace
parameter which will create the namespace if not present.
Updating the installation after the initial deployment
The above command (helm upgrade...
) is idempotent. In other words, you can run it multiple times after adjusting your desired configuration without causing any unintended changes or side effects.
Upgrading to 1.25
or higher from pre-1.25
To upgrade to 1.25
or higher from a pre-1.25
version, you must delete the deployed StatefulSet
, update the helm chart to version 17.0.0
or higher, and re-deploy Weaviate.
See the 1.25 migration guide for Kubernetes for more details.
Additional Configuration Help
- Cannot list resource "configmaps" in API group when deploying Weaviate k8s setup on GCP
- Error: UPGRADE FAILED: configmaps is forbidden
Using EFS with Weaviate
In some circumstances, you may wish, or need, to use EFS (Amazon Elastic File System) with Weaviate. And we note in the case of AWS Fargate, you must create the PV (persistent volume) manually, as the PVC will NOT create a PV for you.
To use EFS with Weaviate, you need to:
- Create an EFS file system.
- Create an EFS access point for every Weaviate replica.
- All of the Access Points must have a different root-directory so that Pods do not share the data, otherwise it will fail.
- Create EFS mount targets for each subnet of the VPC where Weaviate is deployed.
- Create StorageClass in Kubernetes using EFS.
- Create Weaviate Volumes, where each volume has a different AccessPoint for VolumeHandle(as mentioned above).
- Deploy Weaviate.
This code is an example of a PV for weaviate-0
Pod:
apiVersion: v1
kind: PersistentVolume
metadata:
name: weaviate-0
spec:
capacity:
storage: 8Gi
volumeMode: Filesystem
accessModes:
- ReadWriteOnce
persistentVolumeReclaimPolicy: Delete
storageClassName: "efs-sc"
csi:
driver: efs.csi.aws.com
volumeHandle: <FileSystemId>::<AccessPointId-for-weaviate-0-Pod>
claimRef:
namespace: <namespace where Weaviate is/going to be deployed>
name: weaviate-data-weaviate-0
For more, general information on running EFS with Fargate, we recommend reading this AWS blog.
Troubleshooting
If you see
No private IP address found, and explicit IP not provided
, set the pod subnet to be in an valid ip address range of the following:10.0.0.0/8
100.64.0.0/10
172.16.0.0/12
192.168.0.0/16
198.19.0.0/16
Questions and feedback
If you have any questions or feedback, let us know in the user forum.