OpenCTI could be deployed using the docker-compose command.
For production deployment, we advise you to deploy
Grakn
andElasticSearch
manually in a dedicated environment and then to start the other components usingDocker
.
$ mkdir /path/to/your/app && cd /path/to/your/app
$ git clone https://github.com/OpenCTI-Platform/docker.git
$ cd docker
Before running the docker-compose
command, don't forget to change the admin token (this token must be a valid UUID) and the password in the file .env
. There is a file .env.example
with a preset of variables for a demonstration purpose only.
If you cannot or don't want to use the .env
, please edit the file docker-compose.yml
with:
- APP__ADMIN__PASSWORD=ChangeMe
- APP__ADMIN__TOKEN=ChangeMe
And change the variable OPENCTI_TOKEN
(for the worker
and all connectors) according to the value of APP__ADMIN__TOKEN
- OPENCTI_TOKEN=ChangeMe
As OpenCTI has a dependency to ElasticSearch and Grakn, you have to set the vm.max_map_count
before running the containers, as mentioned in the ElasticSearch documentation.
$ sysctl -w vm.max_map_count=1048575
To make this parameter persistent, please update your file /etc/sysctl.conf
and add the line:
$ vm.max_map_count=1048575
In order to have the best experience with Docker, we recommend to use the Docker stack feature. In this mode we will have the capacity to easily scale your deployment.
$ env $(cat .env | grep ^[A-Z] | xargs) docker stack deploy --compose-file docker-compose.yml opencti
In some configuration, Grakn could fail to start with the following error:
Starting Storage.....FAILED!
You can restart it by using the command$ docker service update --force opencti_grakn
.
You can also deploy with the standard Docker command:
$ docker-compose --compatibility up
You can now go to http://localhost:8080 and log in with the credentials configured in your environment variables.
$ docker service update --force service_name
$ docker stack rm opencti
If you want to use OpenCTI behind a reverse proxy with a context path, like https://myproxy.com/opencti
, please change the base_path configuration.
- APP__BASE_PATH=/opencti
By default OpenCTI use Websockets so dont forget to configure your proxy for this usage.
If you wish your OpenCTI data to be persistent in production, you should be aware of the volumes
section for Grakn
, ElasticSearch
and MinIO
services in the docker-compose.yml
.
Here is an example of volumes configuration:
volumes:
grakndata:
driver: local
driver_opts:
o: bind
type: none
esdata:
driver: local
driver_opts:
o: bind
type: none
s3data:
driver: local
driver_opts:
o: bind
type: none
OpenCTI default docker-compose.yml
file does not provide any specific memory configuration. But if you want to adapt some dependencies configuration, you can find some links below.
OpenCTI platform is based on a NodeJS runtime, with a memory limit of 512MB by default. We do not provide any option to change this limit today. If you encounter any OutOfMemory
exception, please open a Github issue.
OpenCTI workers and connectors are Python processes. If you want to limit the memory of the process we recommend to directly use Docker to do that. You can find more information in the official Docker documentation.
If you do not use Docker stack, think about
--compatibility
option.
Grakn is a JAVA process that rely on Cassandra (also a JAVA process). In order to setup the JAVA memory allocation, you can use the environment variable SERVER_JAVAOPTS
and STORAGE_JAVAOPTS
.
The current recommendation is
-Xms4G
for both options.
You can find more information in the official Grakn documentation.
ElasticSearch is also a JAVA process. In order to setup the JAVA memory allocation, you can use the environment variable ES_JAVA_OPTS
.
The minimal recommended option today is
-Xms512M -Xmx512M
.
You can find more information in the official ElasticSearch documentation.
Redis has a very small footprint and only provides an option to limit the maximum amount of memory that can be used by the process. You can use the option --maxmemory
to limit the usage.
You can find more information in the Redis docker hub.
MinIO is a small process and does not require a high amount of memory. More information are available for Linux here on the Kernel tuning guide.
The RabbitMQ memory configuration can be find in the RabbitMQ official documentation. Basically RabbitMQ will consumed memory until a specific threshold. So it should be configure along with the Docker memory limitation.