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Update dockercomposefiles with additional release notes changes in 2.12.0 release #4464

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4 changes: 2 additions & 2 deletions docker/release/dockercomposefiles/docker-compose-1.x.yml
100755 → 100644
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@ services:
- discovery.seed_hosts=opensearch-node1,opensearch-node2
- cluster.initial_master_nodes=opensearch-node1,opensearch-node2
- bootstrap.memory_lock=true # along with the memlock settings below, disables swapping
- OPENSEARCH_JAVA_OPTS=-Xms512m -Xmx512m # minimum and maximum Java heap size, recommend setting both to 50% of system RAM
- OPENSEARCH_JAVA_OPTS=-Xms512m -Xmx512m # minimum and maximum Java heap size, recommend setting both to 50% of system RAM
ulimits:
memlock:
soft: -1
Expand Down Expand Up @@ -54,7 +54,7 @@ services:
expose:
- '5601'
environment:
OPENSEARCH_HOSTS: https://opensearch-node1:9200
OPENSEARCH_HOSTS: '["https://opensearch-node1:9200","https://opensearch-node2:9200"]'
networks:
- opensearch-net

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4 changes: 2 additions & 2 deletions docker/release/dockercomposefiles/docker-compose-2.x.yml
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@ services:
- discovery.seed_hosts=opensearch-node1,opensearch-node2
- cluster.initial_cluster_manager_nodes=opensearch-node1,opensearch-node2
- bootstrap.memory_lock=true # along with the memlock settings below, disables swapping
- OPENSEARCH_JAVA_OPTS=-Xms512m -Xmx512m # minimum and maximum Java heap size, recommend setting both to 50% of system RAM
- OPENSEARCH_JAVA_OPTS=-Xms512m -Xmx512m # minimum and maximum Java heap size, recommend setting both to 50% of system RAM
- OPENSEARCH_INITIAL_ADMIN_PASSWORD=${OPENSEARCH_INITIAL_ADMIN_PASSWORD} # Sets the demo admin user password when using demo configuration, required for OpenSearch 2.12 and higher
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ulimits:
memlock:
Expand Down Expand Up @@ -56,7 +56,7 @@ services:
expose:
- '5601'
environment:
OPENSEARCH_HOSTS: https://opensearch-node1:9200
OPENSEARCH_HOSTS: '["https://opensearch-node1:9200","https://opensearch-node2:9200"]'
networks:
- opensearch-net

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68 changes: 68 additions & 0 deletions docker/release/dockercomposefiles/docker-compose-default.x.yml
Original file line number Diff line number Diff line change
@@ -0,0 +1,68 @@
---
version: '3'
services:
opensearch-node1:
image: opensearchproject/opensearch:latest
container_name: opensearch-node1
environment:
- cluster.name=opensearch-cluster
- node.name=opensearch-node1
- discovery.seed_hosts=opensearch-node1,opensearch-node2
- cluster.initial_cluster_manager_nodes=opensearch-node1,opensearch-node2
- bootstrap.memory_lock=true # along with the memlock settings below, disables swapping
- OPENSEARCH_JAVA_OPTS=-Xms512m -Xmx512m # minimum and maximum Java heap size, recommend setting both to 50% of system RAM
- OPENSEARCH_INITIAL_ADMIN_PASSWORD=${OPENSEARCH_INITIAL_ADMIN_PASSWORD} # Sets the demo admin user password when using demo configuration, required for OpenSearch 2.12 and higher
ulimits:
memlock:
soft: -1
hard: -1
nofile:
soft: 65536 # maximum number of open files for the OpenSearch user, set to at least 65536 on modern systems
hard: 65536
volumes:
- opensearch-data1:/usr/share/opensearch/data
ports:
- 9200:9200
- 9600:9600 # required for Performance Analyzer
networks:
- opensearch-net
opensearch-node2:
image: opensearchproject/opensearch:latest
container_name: opensearch-node2
environment:
- cluster.name=opensearch-cluster
- node.name=opensearch-node2
- discovery.seed_hosts=opensearch-node1,opensearch-node2
- cluster.initial_cluster_manager_nodes=opensearch-node1,opensearch-node2
- bootstrap.memory_lock=true
- OPENSEARCH_JAVA_OPTS=-Xms512m -Xmx512m
- OPENSEARCH_INITIAL_ADMIN_PASSWORD=${OPENSEARCH_INITIAL_ADMIN_PASSWORD}
ulimits:
memlock:
soft: -1
hard: -1
nofile:
soft: 65536
hard: 65536
volumes:
- opensearch-data2:/usr/share/opensearch/data
networks:
- opensearch-net
opensearch-dashboards:
image: opensearchproject/opensearch-dashboards:latest
container_name: opensearch-dashboards
ports:
- 5601:5601
expose:
- '5601'
environment:
OPENSEARCH_HOSTS: '["https://opensearch-node1:9200","https://opensearch-node2:9200"]'
networks:
- opensearch-net

volumes:
opensearch-data1:
opensearch-data2:

networks:
opensearch-net:
2 changes: 1 addition & 1 deletion release-notes/opensearch-release-notes-2.12.0.md
Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,6 @@ OpenSearch 2.12.0 includes a number of features designed to increase performance
<ul>
<li>Integration with Apache Spark lets you analyze all of your operational data in a single place using OpenSearch in combination with Apache Spark. </li>
<li>Conversational search is generally available, providing comprehensive functionality to build conversational experiences using OpenSearch’s lexical, vector, and hybrid search features.</li>
<li>A new workflow engine lets you automate configurations for ML Commons resources, allowing you to set up machine learning resources to support AI use cases without the need to manually create resources or write custom scripts.</li>
<li>New default processors for Amazon Bedrock text embedding connectors can reduce the effort required to build AI connectors.</li>
<li>You can now represent long documents as multiple vectors in a nested field with built-in chunking, eliminating the need to build custom processing logic in order to query documents represented as vector chunks.</li>
<li>Concurrent segment search is now generally available, giving you the option to query index segments in parallel at the shard level. This can deliver improved latency for many types of search queries.</li>
Expand All @@ -26,6 +25,7 @@ OpenSearch 2.12.0 includes a number of features designed to increase performance
<li>The OpenSearch Assistant Toolkit helps developers build generative AI experiences inside of OpenSearch Dashboards. With integrated natural language processing and context-aware features, developers can use this toolkit to apply generative AI to create interactive user experiences and extract insights from OpenSearch data.</li>
<li>A new agent framework added to ML Commons uses remote large language learning models (LLMs) for step-by-step problem-solving and can coordinate machine learning tools using LLMs. The framework includes a flow agent and a conversational agent in this release.</li>
<li>Users can now query multiple clusters with cross-cluster monitors through the Alerting plugin.</li>
<li>A new workflow engine lets you automate configurations for ML Commons resources, allowing you to set up machine learning resources to support AI use cases without the need to manually create resources or write custom scripts.</li>
</ul>

<h2>DEPRECATION NOTICE</h2>
Expand Down
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