This chart uses a standard Docker image of Elasticsearch version 8.5.1 and uses a service pointing to the master's transport port for service discovery. Elasticsearch does not communicate with the Kubernetes API, hence no need for RBAC permissions.
If you are currently using an earlier version of this Chart you will need to redeploy your Elasticsearch clusters. The discovery method used here is incompatible with using RBAC. If you are upgrading to Elasticsearch 6 from the 5.5 version used in this chart before, please note that your cluster needs to do a full cluster restart. The simplest way to do that is to delete the installation (keep the PVs) and install this chart again with the new version. If you want to avoid doing that upgrade to Elasticsearch 5.6 first before moving on to Elasticsearch 6.0.
- Kubernetes 1.20+
- PV provisioner support in the underlying infrastructure
- Kanister controller version 0.111.0 installed in your cluster
- Kanctl CLI installed (https://docs.kanister.io/tooling.html#install-the-tools)
This chart will do the following:
- Implement a dynamically scalable elasticsearch cluster using Kubernetes StatefulSets/Deployments and also add the kanister blueprint to be used with it.
- Multi-role deployment: master, client (coordinating) and data nodes
- Statefulset Supports scaling down without degrading the cluster
For basic installation, you can install using the provided Helm chart that will install an instance of Elasticsearch as well as a Kanister blueprint to be used with it.
Prior to install you will need to have the Elastic Helm repository added to your local setup.
$ helm repo add elastic https://helm.elastic.co
$ helm repo update
Then install the sample Elasticsearch application with the release name
elasticsearch
in its own namespace es-test
using the command below.
Make sure you have the kanister controller running in namespace kanister
which is the default setting in Elasticsearch charts. Otherwise, you will also
have to set the kanister.controller_namespace
parameter value to the
respective kanister controller namespace in the following command:
$ helm install --namespace es-test elasticsearch elastic/elasticsearch \
--set antiAffinity=soft --create-namespace
The command deploys Elasticsearch on the Kubernetes cluster with the default configuration.
In case, if you don't have Kanister
installed already, you can use following
commands to do that.
Add Kanister Helm repository and install Kanister operator
$ helm repo add kanister https://charts.kanister.io
$ helm install kanister --namespace kanister --create-namespace \
kanister/kanister-operator --set image.tag=0.111.0
Create Profile CR if not created already
$ kanctl create profile s3compliant --access-key <aws-access-key> \
--secret-key <aws-secret-key> --namespace es-test \
--bucket <s3-bucket-name> --region <region-name>
NOTE:
The command will configure a location where artifacts resulting from Kanister
data operations such as backup should go. This is stored as a
profiles.cr.kanister.io
CustomResource (CR) which is then referenced in
Kanister ActionSets. Every ActionSet requires a Profile reference to complete
the action. This CR (profiles.cr.kanister.io
) can be shared between
Kanister-enabled application instances.
NOTE: v2 Blueprints are experimental and are not supported with standalone Kanister.
In order to perform backup, restore, and delete operations on the running elasticsearch, we need to create a blueprint.
$ kubectl create -f ./elasticsearch-blueprint.yaml -n kanister
Once Elasticsearch is running, you can populate it with some data. Follow the
instructions that get displayed by running command
helm status elasticsearch -n es-test
to connect to the application.
# Log in into elasticsearch container and get shell access
$ kubectl exec -it elasticsearch-master-0 -n es-test -c elasticsearch -- bash
# Create index called customer
$ curl -X PUT "https://elastic:${ELASTIC_PASSWORD}@localhost:9200/customer?pretty" -k
{
"acknowledged" : true,
"shards_acknowledged" : true,
"index" : "customer"
}
# Add a customer named John Smith
$ curl -X PUT "https://elastic:${ELASTIC_PASSWORD}@localhost:9200/customer/_doc/1?pretty" \
-H 'Content-Type: application/json' -d '{"name": "John Smith"}' -k
{
"_index" : "customer",
"_id" : "1",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 2,
"failed" : 0
},
"_seq_no" : 0,
"_primary_term" : 1
}
# View the data
$ curl -X GET "https://elastic:${ELASTIC_PASSWORD}@localhost:9200/_cat/indices?v" -k
health status index uuid pri rep docs.count docs.deleted store.size pri.store.size
green open customer YmIH-p0DRD--KzIA6i4Ayg 1 1 0 0 450b 225b
$ curl -X GET "https://elastic:${ELASTIC_PASSWORD}@localhost:9200/customer/_search?q=*&pretty" -k
{
"took" : 867,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "customer",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name" : "John Smith"
}
}
]
}
}
You can now take a backup of the Elasticsearch data using an ActionSet defining
backup for this application. Create an ActionSet in the same namespace as the
controller using kanctl
, a command-line tool that helps create ActionSets as
shown below:
$ kubectl get profile -n es-test
NAME AGE
s3-profile-4dxn8 7m25s
$ kanctl create actionset --action backup --namespace kanister \
--blueprint elasticsearch-blueprint \
--statefulset es-test/elasticsearch-master \
--profile es-test/s3-profile-4dxn8
actionset backup-kmms4 created
# View the status of the actionset
$ kubectl --namespace kanister get actionsets.cr.kanister.io
NAME PROGRESS LAST TRANSITION TIME STATE
backup-kmms4 100.00 2023-01-04T09:45:22Z complete
Let's say someone with fat fingers accidentally deleted the customer index using the following command:
# Log in into elasticsearch container and get shell access
$ kubectl exec -it elasticsearch-master-0 -n es-test -c elasticsearch -- bash
# Delete the index
$ curl -X DELETE "https://elastic:${ELASTIC_PASSWORD}@localhost:9200/customer?pretty" -k
{
"acknowledged" : true
}
# Get the index
$ curl -X GET "https://elastic:${ELASTIC_PASSWORD}@localhost:9200/_cat/indices?v" -k
health status index uuid pri rep docs.count docs.deleted store.size pri.store.size
To restore the missing data, we want to use the backup created earlier in the
steps above. An easy way to do this is to leverage kanctl
, a command-line tool
that helps create ActionSets that depend on other ActionSets:
$ kanctl create actionset --action restore --namespace kanister --from backup-kmms4
actionset restore-backup-kmms4-rp89l created
# View the status of the ActionSet
$ kubectl --namespace kanister get actionsets.cr.kanister.io restore-backup-kmms4-rp89l
NAME PROGRESS LAST TRANSITION TIME STATE
restore-backup-kmms4-rp89l 100.00 2023-01-04T09:54:11Z complete
You should now see that the data has been successfully restored to Elasticsearch!
# Log in into elasticsearch container and get shell access
$ kubectl exec -it elasticsearch-master-0 -n es-test -c elasticsearch -- bash
$ curl -X GET "https://elastic:${ELASTIC_PASSWORD}@localhost:9200/_cat/indices?v" -k
health status index uuid pri rep docs.count docs.deleted store.size pri.store.size
green open customer VtP3QddrTdq69mvq3NwCuQ 1 1 1 0 9.2kb 4.5kb
$ curl -X GET "https://elastic:${ELASTIC_PASSWORD}@localhost:9200/customer/_search?q=*&pretty" -k
{
"took" : 34,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "customer",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name" : "John Smith"
}
}
]
}
}
The artifacts created by the backup action can be cleaned up using the following command:
$ kanctl create actionset --action delete --namespace kanister \
--from backup-kmms4 --namespacetargets kanister
actionset delete-backup-kmms4-sd6tj created
# View the status of the ActionSet
$ kubectl --namespace kanister get actionsets.cr.kanister.io delete-backup-kmms4-sd6tj
NAME PROGRESS LAST TRANSITION TIME STATE
delete-backup-kmms4-sd6tj 100.00 2023-01-04T09:59:53Z complete
If you run into any issues with the above commands, you can check the logs of the controller using:
$ kubectl --namespace kanister logs -l app=kanister-operator
$ helm delete elasticsearch -n es-test
release "elasticsearch" uninstalled
Deletion of the StatefulSet doesn't cascade to deleting associated PVCs. To delete them:
$ kubectl delete pvc -l app=elasticsearch-master -n es-test
persistentvolumeclaim "elasticsearch-master-elasticsearch-master-0" deleted
persistentvolumeclaim "elasticsearch-master-elasticsearch-master-1" deleted
persistentvolumeclaim "elasticsearch-master-elasticsearch-master-2" deleted
Remove Blueprint, Profile CR and ActionSet
$ kubectl delete blueprints.cr.kanister.io elasticsearch-blueprint -n kanister
blueprint.cr.kanister.io "elasticsearch-blueprint" deleted
$ kubectl get profiles.cr.kanister.io -n es-test
NAME AGE
s3-profile-4dxn8 93m
$ kubectl delete profiles.cr.kanister.io s3-profile-4dxn8 -n es-test
profile.cr.kanister.io "s3-profile-4dxn8" deleted
$ kubectl delete actionset backup-kmms4 delete-backup-kmms4-sd6tj \
restore-backup-kmms4-rp89l -n kanister
actionset.cr.kanister.io "backup-kmms4" deleted
actionset.cr.kanister.io "delete-backup-kmms4-sd6tj" deleted
actionset.cr.kanister.io "restore-backup-kmms4-rp89l" deleted
If you're on a single node cluster, you'd need to set the antiAffinity to soft
while installing the helm chart by running --set antiAffinity=soft
so that
pods are not stuck in the pending state. For other configurations of
elasticsearch helm chart, please refer
https://github.com/elastic/helm-charts/blob/master/elasticsearch/README.md