Is it possible to deploy opensearch using docker-compose immediately with a set of data from a file?
The official documentation says that you need to deploy the docker image and then send a bulk request with data there. But nowhere does it say how to raise opensearch immediately with pre-prepared data.
Now I deploy opensearch like this
version: '3'
services:
opensearch-node1:
image: opensearchproject/opensearch:latest
container_name: opensearch-node1
environment:
- cluster.name=opensearch-cluster
- node.name=opensearch-node1
- discovery.type=single-node
- bootstrap.memory_lock=true
- "OPENSEARCH_JAVA_OPTS=-Xms1024m -Xmx1024m"
ulimits:
memlock:
soft: -1
hard: -1
nofile:
soft: 65536
hard: 65536
volumes:
- opensearch-data1:/usr/share/opensearch/data
ports:
- 9200:9200
- 9600:9600
opensearch-dashboards:
image: opensearchproject/opensearch-dashboards:latest
container_name: opensearch-dashboards
ports:
- 5601:5601
expose:
- "5601"
environment:
OPENSEARCH_HOSTS: '["https://opensearch-node1:9200"]'
volumes:
opensearch-data1:
Related
hi i want to connect to Elasticsearch inside my app which is defined as "cog-app" service in docker-compose.yml along with ditsro elasticsearch and kibana
i am not able to connect to elasticsearch when i run docker file, can you please tell me how i can connect elasticsearch service to app service
i have defined elasticsearch in cog-app service, and im getting connection failure with elasticsearch
version: "3"
services:
cog-app:
image: app:2.0
build:
context: .
dockerfile: ./Dockerfile
stdin_open: true
tty: true
ports:
- "7111:7111"
environment:
- LANG=C.UTF-8
- LC_ALL=C.UTF-8
- CONTAINER_NAME=app
volumes:
- /home/developer/app:/app
odfe-node1:
image: amazon/opendistro-for-elasticsearch:1.13.2
container_name: odfe-node1
environment:
- cluster.name=odfe-cluster
- node.name=odfe-node1
- discovery.seed_hosts=odfe-node1,odfe-node2
- cluster.initial_master_nodes=odfe-node1,odfe-node2
- bootstrap.memory_lock=true # along with the memlock settings below, disables swapping
- "ES_JAVA_OPTS=-Xms2g -Xmx2g" # minimum and maximum Java heap size, recommend setting both to 50% of system RAM
ulimits:
memlock:
soft: -1
hard: -1
nofile:
soft: 65536 # maximum number of open files for the Elasticsearch user, set to at least 65536 on modern systems
hard: 65536
volumes:
- odfe-data1:/usr/share/elasticsearch/data
ports:
- 9200:9200
- 9600:9600 # required for Performance Analyzer
odfe-node2:
image: amazon/opendistro-for-elasticsearch:1.13.2
container_name: odfe-node2
environment:
- cluster.name=odfe-cluster
- node.name=odfe-node2
- discovery.seed_hosts=odfe-node1,odfe-node2
- cluster.initial_master_nodes=odfe-node1,odfe-node2
- bootstrap.memory_lock=true
- "ES_JAVA_OPTS=-Xms2g -Xmx2g"
ulimits:
memlock:
soft: -1
hard: -1
nofile:
soft: 65536
hard: 65536
volumes:
- odfe-data2:/usr/share/elasticsearch/data
networks:
- odfe-net
kibana:
image: amazon/opendistro-for-elasticsearch-kibana:1.13.2
container_name: odfe-kibana
ports:
- 5601:5601
expose:
- "5601"
environment:
ELASTICSEARCH_URL: https://odfe-node1:9200
ELASTICSEARCH_HOSTS: https://odfe-node1:9200
networks:
- odfe-net
volumes:
odfe-data1:
odfe-data2:
networks:
odfe-net:
please tell me how two services can communicate with each other
As the elasticsearch service is running in another container, localhost is not valid. You should use odfe-node1:9200 as the url
I have a small app with a python backend where I'm streaming and classifying tweets in real-time.
I use elasticsearch to collect classified tweets and Kibana to make visualizations based on es data.
In my frontend, I just use kibana visualizations.
For the moment, I'm trying to run my application in a multi-node swarm as a services stack but I'm having problems with my compose file.
I tried to start with elastisearch and to use this info https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html but didn't help, and I didn'd succed to deploy my docker-compose file even with just elasticsearch serivce.
This is my yml file:
version: '3'
services:
elasticsearch:
image: docker.elastic.co/elasticsearch/elasticsearch:7.6.2
environment:
- cluster.name=docker-cluster
- bootstrap.memory_lock=true
- 'ES_JAVA_OPTS=-Xms512m -Xmx512m'
ulimits:
memlock:
soft: -1
hard: -1
ports:
- '9200:9200'
kibana:
image: docker.elastic.co/kibana/kibana:7.6.2
ports:
- '5601:5601'
Below is the docker-compose file which works for a single node in a development environment, which have disabled security and has discovery.type=single-node param to make sure elasticsearch production bootstrap checks are not kicked in.
version: '2.2'
services:
#Elasticsearch Docker Images: https://www.docker.elastic.co/
elasticsearch:
image: docker.elastic.co/elasticsearch/elasticsearch:7.6.0
container_name: elasticsearch
environment:
- xpack.security.enabled=false
- discovery.type=single-node
ulimits:
memlock:
soft: -1
hard: -1
nofile:
soft: 65536
hard: 65536
cap_add:
- IPC_LOCK
volumes:
- elasticsearch-data:/usr/share/elasticsearch/data
ports:
- 9200:9200
- 9300:9300
volumes:
elasticsearch-data:
driver: local
networks:
elastic:
external: true
Liferay is not able to recognize my Elasticsearch cluster when starting. Here is my docker-compose configuration:
version: '2.2'
services:
es01:
image: docker.elastic.co/elasticsearch/elasticsearch:7.1.1
container_name: es01
environment:
- node.name=es01
- discovery.seed_hosts=es02
- cluster.initial_master_nodes=es01,es02
- cluster.name=liferay-cluster
- bootstrap.memory_lock=true
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
ulimits:
memlock:
soft: -1
hard: -1
volumes:
- esdata01:/usr/share/elasticsearch/data
ports:
- "9299:9200"
- "9399:9300"
expose:
- "9299"
networks:
- esnet
es02:
image: docker.elastic.co/elasticsearch/elasticsearch:7.1.1
container_name: es02
environment:
- node.name=es02
- discovery.seed_hosts=es01
- cluster.initial_master_nodes=es01,es02
- cluster.name=liferay-cluster2
- bootstrap.memory_lock=true
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
ulimits:
memlock:
soft: -1
hard: -1
ports:
- "9298:9200"
- "9398:9300"
expose:
- "9298"
volumes:
- esdata02:/usr/share/elasticsearch/data
networks:
- esnet
volumes:
esdata01:
driver: local
esdata02:
driver: local
networks:
esnet:
com.liferay.portal.search.elasticsearch6.configuration.ElasticsearchConfiguration.config file content
transportAddresses="127.0.0.1:9299"
logExceptionsOnly="false"
operationMode="REMOTE"
indexNamePrefix="myprefix-"
clusterName="liferay-cluster"
When starting docker-compose, I'm able to access my two ES clusters on: http://127.0.0.1:9299/ and http://127.0.0.1:9298/
However, when liferay starts it is unable to access ES nodes:
NoNodeAvailableException[None of the configured nodes are available: [{#transport#-1}{vUNCF_HNRtu_tYUjkqhXvg}{127.0.0.1}{127.0.0.1:9299}]]
Anyone tried this configuration ? Any help would be appreciated. Thanks :-)
I've found a solution. It could help if someone is trying to do the same.
As, I said in my comment to #ibexit, I'm running two dockerized ES clusters and two separate Liferay portals (not in containers) on the same machine (development mode).
I changed th transport address in Liferay OSGi config file, since it must match the transport tcp port where ES is running:
transportAddresses="127.0.0.1:9301"
logExceptionsOnly="false"
operationMode="REMOTE"
indexNamePrefix="myprefix-"
clusterName="liferay-cluster"
I also added the property network.publish_host=127.0.0.1 in my ES clusters (without this property Liferay was not able to detect ES nodes)
Here is my docker-compose.yml:
Using ES 6.1.4
version: '2.2'
services:
es01:
image: docker.elastic.co/elasticsearch/elasticsearch:6.1.4
container_name: es01
environment:
- node.name=es01
- cluster.name=liferay-cluster
- bootstrap.memory_lock=true
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
- transport.tcp.port=9301
- network.publish_host=127.0.0.1
ulimits:
memlock:
soft: -1
hard: -1
volumes:
- esdata01:/usr/share/elasticsearch/data
ports:
- "9201:9200"
- "9301:9301"
networks:
- esnet
es02:
image: docker.elastic.co/elasticsearch/elasticsearch:6.1.4
container_name: es02
environment:
- node.name=es02
- cluster.name=liferay-cluster2
- bootstrap.memory_lock=true
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
- transport.tcp.port=9302
- network.publish_host=127.0.0.1
ulimits:
memlock:
soft: -1
hard: -1
ports:
- "9202:9200"
- "9302:9302"
volumes:
- esdata02:/usr/share/elasticsearch/data
networks:
- esnet
volumes:
esdata01:
driver: local
esdata02:
driver: local
networks:
esnet:
network.publish_host did the trick !
Per default, elasticsearch binds the transport and http ports to localhost (local) only. So your ports exposed by docker are not working. You need to bind to a specific ip or using 0.0.0.0 for all or site as explained here: https://www.elastic.co/guide/en/elasticsearch/reference/current/modules-network.html#network-interface-values
Please have in mind, that enabling this will startup the node in production mode followed by several bootstrap checks. Please see the docs if you need more informations on this topics or search SO.
My working local setup with docker compose and two elasticsearch nodes in docker containers and Liferay running on host. I am using elasticsearch 6.8.2 images modified according to Liferay docs available from docker hub with url: https://hub.docker.com/repository/docker/ktorek/liferay7-elasticsearch.
I am using gradle workspace. So I've configured: configs/local/osgi/configs/com.liferay.portal.search.elasticsearch6.configuration.ElasticsearchConfiguration.config:
operationMode=REMOTE
clusterName=docker-cluster
transportAddresses=127.0.0.1:9300,127.0.0.1:9301
I've killed a lot of time with transportAddresses configuration as it's documented to use square brackets and square quotes transportAddresses=["192.168.1.1:9300","192.168.1.2:9300"] but it does not work. Configuration listed above contains actual working configuration syntax.
My docker-compose.yml:
version: '3.7'
services:
es01:
container_name: "es01"
image: ktorek/liferay7-elasticsearch:latest
environment:
- node.name=es01
- node.data=true
- cluster.name=docker-cluster
- xpack.security.enabled=false
- bootstrap.memory_lock=true
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
- "discovery.zen.ping.unicast.hosts=es02"
ports:
- "9300:9300"
- "9200:9200"
networks:
- mynetwork
volumes:
- es01-data:/usr/share/elasticsearch/data
ulimits:
memlock:
soft: -1
hard: -1
es02:
container_name: "es02"
image: ktorek/liferay7-elasticsearch:latest
environment:
- node.name=es02
- node.data=true
- cluster.name=docker-cluster
- xpack.security.enabled=false
- bootstrap.memory_lock=true
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
- "discovery.zen.ping.unicast.hosts=es01"
ports:
- "9301:9300"
- "9201:9200"
networks:
- mynetwork
volumes:
- es02-data:/usr/share/elasticsearch/data
ulimits:
memlock:
soft: -1
hard: -1
networks:
mynetwork:
name: mynetwork
driver: bridge
ipam:
config:
- subnet: 172.30.29.0/24
I have an elasticsearch image that is being used as a base image for multiple containers. I am wondering if there is any way to pre-configure an ingest pipeline such that the process of creating the image and building a container also creates the pipeline for me? It'd be great if the base image comes with the pipeline that i want it to have, otherwise I'd have to docker exec into each container that uses this image and send a curl request in each one to create the pipeline.
Right now I'm thinking that I have to add a curl to the elasticsearch server (after it starts) in docker-entrypoint.sh, but i'm not sure if there's any other way
I can advice you to use docker-compose. I personally find it very convenient. With one file you can configure a whole stack.
Here is an example to help you start:
version: '2.2'
services:
elasticsearch:
image: docker.elastic.co/elasticsearch/elasticsearch:6.3.2
container_name: elasticsearch
environment:
- cluster.name=docker-cluster
- node.name=node-test1
- bootstrap.memory_lock=true
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
ulimits:
memlock:
soft: -1
hard: -1
volumes:
- node-test1data:/usr/share/elasticsearch/data
ports:
- 9200:9200
elasticsearch2:
image: docker.elastic.co/elasticsearch/elasticsearch:6.3.2
container_name: elasticsearch2
environment:
- cluster.name=docker-cluster
- node.name=node-test2
- bootstrap.memory_lock=true
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
- "discovery.zen.ping.unicast.hosts=elasticsearch"
ulimits:
memlock:
soft: -1
hard: -1
volumes:
- node-test2data:/usr/share/elasticsearch/data
kibana:
image: docker.elastic.co/kibana/kibana:6.3.2
container_name: kibana
ports:
- 5601:5601
environment:
ELASTICSEARCH_URL: http://elasticsearch:9200
depends_on:
- elasticsearch
logstash:
image: docker.elastic.co/logstash/logstash:6.3.2
container_name: logstash
ports:
- "5000:5000"
environment:
LS_JAVA_OPTS: "-Xmx256m -Xms256m"
volumes:
- ./logstash/config/logstash.yml:/usr/share/logstash/config/logstash.yml:ro
- ./logstash/pipeline:/usr/share/logstash/pipeline:ro
Elasticsearch's official docker image documentation provides this docker-compose.yml example:
version: '2'
services:
elasticsearch1:
image: docker.elastic.co/elasticsearch/elasticsearch:5.6.3
container_name: elasticsearch1
environment:
- cluster.name=docker-cluster
- bootstrap.memory_lock=true
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
ulimits:
memlock:
soft: -1
hard: -1
mem_limit: 1g
volumes:
- esdata1:/usr/share/elasticsearch/data
ports:
- 9200:9200
networks:
- esnet
elasticsearch2:
image: docker.elastic.co/elasticsearch/elasticsearch:5.6.3
environment:
- cluster.name=docker-cluster
- bootstrap.memory_lock=true
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
- "discovery.zen.ping.unicast.hosts=elasticsearch1"
ulimits:
memlock:
soft: -1
hard: -1
mem_limit: 1g
volumes:
- esdata2:/usr/share/elasticsearch/data
networks:
- esnet
volumes:
esdata1:
driver: local
esdata2:
driver: local
networks:
esnet:
However, it doesn't explain how to customize the password. It does direct us to a X-Pack documentation page, but I refuse to believe I have to go through all that trouble just to change a password. Is there any simpler, canonical way of configuring a custom password for elasticsearch on a Docker Compose file?
Starting from 6.0 elasticsearch docker images has the ability to configure the password using the following environment variable - ELASTIC_PASSWORD.
For example:
docker run -e ELASTIC_PASSWORD=MagicWord docker.elastic.co/elasticsearch/elasticsearch-platinum:6.1.3
See:
https://www.elastic.co/guide/en/elasticsearch/reference/6.1/docker.html