Elasticsearch Single Node with Kibana
In this scenario, you'll learn how to deploy a Elasticsearch and Kibana as a Docker Container.
Elasticsearch single is recommended for dev and monitoring but not for the production or primary store.
If we have a proper backup strategy still we can risk running a single node in the production too but we don't get all the feature set like fault tolerance and distributed cluster, this is at high risk.
Let us understand how we can start the single node container in this scenario, expecting that you are familiar with docker
and docker-compose
commands.
Agenda
- Create the docker-compose
- Understand the properties used in Elasticsearch and Kibana
- Health check with
- Kibana Console UI
-
curl
Command
- Create a simple document with
- mappings
- settings
- Insert Data into the created index
Create the docker-compose
Create the docker-compose.yml
with the following
version: "3"
services:
elasticsearch:
image: docker.elastic.co/elasticsearch/elasticsearch:7.7.0
container_name: elasticsearch
environment:
- discovery.type=single-node
- ES_JAVA_OPTS="-Xms1g -Xmx1g"
volumes:
- vibhuviesdata:/usr/share/elasticsearch/data
ports:
- 9200:9200
networks:
- elastic
labels:
- co.elastic.logs/module=elasticsearch
- co.elastic.metrics/module=elasticsearch
kibana:
image: docker.elastic.co/kibana/kibana:7.7.0
container_name: kibana
ports:
- 5601:5601
depends_on:
- elasticsearch
environment:
ELASTICSEARCH_URL: http://elasticsearch:9200
ELASTICSEARCH_HOSTS: http://elasticsearch:9200
networks:
- elastic
networks:
elastic:
driver: bridge
volumes:
vibhuviesdata:
driver: local
Check the content of docker-compose.yml
file
cat docker-compose.yml
Understands the Environment and Run the container
As mentioned in the intro hope you are familiar with the docker container commands, expecting that we proceed with the environment we have configured for the elasticsearch.
In the docker-compose we have defined two services elasticsearch
and kibana
. Let's look at the other properties defined.
Elasticsearch
-
image: docker.elastic.co/elasticsearch/elasticsearch:7.7.0
- Image of version7.7.0
-
container_name
- Custom name of the container -
environment
- To run the single need we need to set the container environment withdiscovery.type: single-node
and Optional but important when we are running in dev machineES_JAVA_OPTS: "-Xms512m -Xmx1024m"
-
volumes
to maintain the persistancy on restarting the container else we loose the data when we restart the container. Here we have host volumevibhuviesdata
and container volume/usr/share/elasticsearch/data
. Host Volume maintains the data for multiple restarts of the container. -
ports
- Elasticsearch will use port 9200 for requests and port 9300 for communication between nodes within the cluster. -
networks
- To maintain the security from the other networks in the docker we have created a common network for both kibana and elasticsearch
Kibana
-
image: docker.elastic.co/kibana/kibana:7.7.0
- We have to use the same version as elasticsearch after4.6.*
. Check the Kibana Compatibility with Elasticsearch Matrix -
container_name
- Custom name of the container -
environment
- Kibana is connecting to the container elasticsearch with teh service name and port. -
ports
- Kibana will use port 9200 for visualising the elasticsearch -
depends_on
- The property tell the Kibana service to run after elasticsearch
Run the container
docker-compose up -d
Docker Commands
- Check the status of the container
docker container ls -a
- Check the logs of the Elasticsearch
docker logs elasticsearch
- Check the logs of the Kibana
docker logs kibana
-
Output contains
- Elasticsearch -
"message": "Cluster health status changed from [YELLOW] to [GREEN]
- Kibana -
"message":"http server running at http://0:5601"
- Elasticsearch -
This means that both containers are running successfully
Interaction with Elasticsearch Cluster API
We have Elasticsearch running, let's try to interact with elaticsearch APIs
We have two options to intearct with Elasticsearch curl
and Kibana Console UI
Curl
-
Cluster health API
curl -X GET "localhost:9200/_cluster/health?pretty"
-
Cluster state API
curl -X GET "localhost:9200/_cluster/state/_all?pretty"
-
Cluster Stats API
curl -X GET "localhost:9200/_cluster/stats"
-
Cluster Settings API
curl -X GET "localhost:9200/_cluster/settings"
Kibana UI
Cluster health API - GET /_cluster/health
Cluster state API - GET /_cluster/state/_all
Cluster Stats API - GET /_cluster/stats
Cluster Settings API - GET /_cluster/settings
Frequently used commands
Check the status of the Elasticsearch
Check the health status of the Elasticsearch
curl -X GET "localhost:9200/_cat/health"
- Get the number of nodes of the Elasticsearch Cluster
curl -X GET "localhost:9200/_cat/nodes"
- Check with the shards with
curl -X GET "localhost:9200/_cat/shards"
- Get list of indices
curl -X GET "localhost:9200/_cat/indices?v"
- Get list of indices with specific column, we want to the column index, which will list the index names
curl -X GET "localhost:9200/_cat/indices?v&h=index"
- Get the list of indices sort by column
curl -X GET "localhost:9200/_cat/indices?v&s=docs.count:desc"
curl -X GET "localhost:9200/_cat/indices?v&s=docs.count:asc"
curl -X GET "localhost:9200/_cat/indices?v&s=index"
curl -X GET "localhost:9200/_cat/indices?v&s=docs.count:desc"
curl -X GET "localhost:9200/_cat/indices?v&s=docs.count:desc"
Create Index
Let's get into the actual dev stuff required for any developer to use elasticsearch with any client. Lets create a index using Index API.
- Create index
curl -X PUT "localhost:9200/twitter?pretty"
- Create the index with settings
curl -sXPUT 'http://localhost:9200/customer/?pretty' -d '{
"settings" : {
"index" : {
"number_of_shards" : 5,
"number_of_replicas" : 0
}
}
}'
- Insert bulk data into the index created
for i in `seq 1 500`; do
curl -sXPUT "localhost:9200/customer/external/$i?pretty" -d "
{
\"number\": $i,
\"name\": \"John Doe - $i\"
}"
done
- Create student entity with 1000 records
curl -sXPUT 'http://localhost:9200/student/?pretty' -d '{
"settings" : {
"index" : {
"number_of_shards" : 5,
"number_of_replicas" : 0
}
}
}'
for i in `seq 1 20`; do
curl -sXPUT "localhost:9200/student/external/$i?pretty" -d "
{
\"number\": $i,
\"name\": \"Ram - $i\"
}"
done
- Create index with mappings and settings
curl -X PUT "localhost:9200/school?pretty" -H 'Content-Type: application/json' -d'
{
"settings" : {
"number_of_shards" : 3,
"number_of_replicas" : 2
},
"mappings" : {
"properties" : {
"name" : { "type" : "text" }
}
}
}
'
Delete index
curl -X DELETE "localhost:9200/school?pretty"
Get Index
- Get the mappings and setting with the following
curl -X GET "localhost:9200/school?pretty"
curl -X GET "localhost:9200/school/_mapping?pretty"
curl -X GET "localhost:9200/school/_settings?pretty"
- Checks if an index exists
curl -I "localhost:9200/twitter?pretty"
- Get the count of Index
curl -I "localhost:9200/twitter/_count?pretty"
- Update index settings API
curl -X PUT "localhost:9200/school/_settings?pretty" -H 'Content-Type: application/json' -d'
{
"index" : {
"number_of_replicas" : 2
}
}
'
- Get the Statistics of the index
curl -X GET "localhost:9200/school/_stats?pretty"
curl -X GET "localhost:9200/_stats?pretty"
curl -X GET "localhost:9200/index1,index2/_stats?pretty"
Congratulations! We successfully completed the basics in elasticsearch.
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