Document version: 228. Automatically generated.
RedisAI is a Redis module for executing Deep Learning/Machine Learning models and managing their data. Its purpose is to be a "workhorse" for model serving, by providing out-of-the-box support for popular DL/ML frameworks and unparalleled performance.
RedisAI platform is designed to run inside the Kubernetes cluster.
- Kubernetes cluster
- Helm (version 3 or higher)
- Access to Automate HELM Charts repository charts.sentione.com is granted
- Access to harbor-vm-proxy.sentione.com docker images repository is granted
- Local-path-provisioner (this is optional, but highly reccomended for data persistence. It may also be replaced with other dynamic PV provisioner like OpenEBS)
To add the helm repository, use:
helm repo add sentione-hub https://charts.sentione.com/repository/helm --username USERNAME --password PASSWORD
and fetch repository data:
helm repo update
The chart is based on images available on harbor-vm-proxy.sentione.com which requires authorization. Secret should be created by;
kubectl create secret \ docker-registry sec-harbor-vm-proxy.sentione.com \ --docker-server=<PRIVATE_REPO_ADDRESS> \ --docker-username=<USER> \ --docker-password=<PASSOWRD> \ --docker-email=<EMAIL> \ --namespace <NAMESPACE>
Before deploying the chart prepare
values.yaml file, according to this minimal template:
clusterDomain: cluster.local persistence: # set to false in order to disable data persistence enabled: true # may be changed to other storageClass names if not using local-path-provisioner storageClass: "local-path"
Redis cluster size
The default deployment creates a 6-node cluster (3 masters and 3 replica nodes), this may be changed by using:
cluster: nodes: n
n must be an even number
RedisAI holds the results of NLU training. This data may be "regenerated" by running the NLU training again.
We recommend not turning off persistence as it causes the need to retrain in case of RedisAI restart/failure.
In order to deploy the chart run, while replacing
$REDIS_AI_NAMESPACE with the desired namespace in Kubernetes:
helm -n $REDIS_AI_NAMESPACE upgrade --install redis-ai sentione-hub/redis-cluster --values values.yaml --create-namespace --version 1.0.1
After RedisAI is deployed the NLU config should be adjusted, see (installation guide 5.3)[installation].
Updated 6 days ago