Platform Installation Instructions¶
This document is for developers / sysadmins who want to install Rasa Platform on premise or on a private cloud.
Note
Rasa uses docker compose to manage the lifecycle of the containers. The installation script should be used to provision a new server. If you want to run the application alongside other software on an existing server, you should consider installing docker compose manually.
Quickstart¶
1. copy the license file to the server. To get a license file, you need to buy a Rasa Platform subscription. If you don’t have one yet, please contact us.
$ scp rasa_platform.yml example.com:~/rasa_platform.yml
- Download and run the install script on the server:
$ curl -sSL -o install.sh https://storage.googleapis.com/rasa-releases/stable/install.sh
$ sudo bash ./install.sh
Replace stable
with a specific version number if you want to install a
specific version. You will be prompted to accept the terms and conditions.
Type YES
and hit return.
- Start the Platform
$ cd /etc/rasaplatform
$ sudo docker-compose up -d
- Create a Platform user you can use to log in
$ cd /etc/rasaplatform
$ sudo python rasa_commands.py create admin USER PASSWORD
replacing the USER
and PASSWORD
fields, for
example python rasa_commands.py create admin admin PasswOrd
.
Navigate to the hostname or IP where your server is reachable and log in via the interface. Once you are logged in you can start Setting Up Your Bot.
Detailed Setup¶
Rasa Platform is built as a collection of docker containers. Here we provide suggested hardware for running on a single server.
Hardware & OS Requirements¶
We recommend 8Gb RAM & 2-6 vCPUs for optimal performance. 4Gb RAM is the bare minimum. Your server should also have 100 Gb Disk space available. You will need a server running a modern Linux distribution that can run docker. The following OS’s work with the easy install script below:
- Debian 7.7+
- Ubuntu 14.04 / 15.10 / 16.04
For any other operating systems, please follow the manual installation instructions. As long as docker is available for your operating system, Rasa Platform should run fine.
The web interface aims to support browsers that meet the following criteria
- > 0.2% market share
- Not Internet Explorer
- Not Opera Mini
Firewall¶
Make sure the following ports are open:
Port | Service | Description |
---|---|---|
443 | HTTPS | Web application over HTTPS access. |
80 | HTTP | Web application access. |
22 | SSH | SSH access. |
If you install on Google Cloud this means:
- make sure to check “Allow HTTP traffic” as well as “Allow HTTPS traffic” in the firewall settings of the VM instance.
Prepare the installation¶
Before you can install Rasa Platform, you need to have a license file. We will
send you that file, it is named rasa_platform.yml
. It contains licensing
information as well as configuration parameters.
Make sure to upload the license file to the server, e.g. using
$ scp rasa_platform.yml HOSTNAME:~/rasa_platform.yml
where HOSTNAME
is the hostname or ip of your server.
Install Docker Compose¶
Rasa uses docker compose to spin up a collection of docker containers that
combined make up the Platform. You can either install a specific release,
or use latest
which corresponds to the most recent release (we recommend
pinning a specific version though).
Download the install script and run it. Make sure the current directory contains the license file:
$ curl -sSL -o install.sh https://storage.googleapis.com/rasa-releases/stable/install.sh
$ sudo bash ./install.sh
The installation script will install docker compose and ansible. ansible is a popular tool for automation - it will download the docker compose setup as well as prepare the environment for docker to run in.
The Platform-related files will be installed into /etc/rasaplatform
. This includes
credentials to login to the docker registry under /etc/rasaplatform/gcr_auth.json
.
Note
Although, this is the easiest way to get your server ready to run the Platform you can also follow the manual steps which will walk you through a few extra steps but will give you more control over the setup.
Accept the terms and conditions¶
To accept the terms and conditions, run echo "${USER} $(date)" > /etc/rasaplatform/terms/agree.txt
.
You can find the terms here.
Start the application¶
After you have successfully installed the Platform you can now start it:
$ cd /etc/rasaplatform
$ sudo docker-compose up -d
This will run the Platform in the background (due to -d
) and the
application will continue to run even if you log out of the server.
Create a User¶
To log in to the Platform, you need to create user accounts. At first, it is best to create at least one administrator account. To do so run:
$ cd /etc/rasaplatform
$ sudo python rasa_commands.py create admin USER PASSWORD
replacing the USER
and PASSWORD
fields, for
example python rasa_commands.py create admin admin PasswOrd
.
To create non-admin users, just replace admin
with user
:
$ sudo python rasa_commands.py create user USER PASSWORD
Note
The admin
role has access to all API endpoints. The user
role
can only send messages and view their own conversation with the bot.
For more information on account roles, head over to the docs on
Platform Account Roles.
Test Your Login¶
Visit http://HOSTNAME
in a web browser, and log in with the
username & password entered in the previous command.
Installing Updates¶
To see which version you are currently running, hit the /version
endpoint:
$ curl hostname/api/version
To install an update, fetch the install.sh
for your version, and run it:
$ curl -sSL -o install.sh https://storage.googleapis.com/rasa-releases/VERSION/install.sh
$ sudo bash ./install.sh
replacing VERSION
with the version you want to install.
After the installation is complete, login to the docker registry and pull the image:
$ cd /etc/rasaplatform
$ sudo docker login -u _json_key -p "$(cat /etc/rasaplatform/gcr-auth.json)" https://gcr.io
$ sudo docker-compose pull
Make sure that the docker environment file is updated by running:
$ cat .env
Start the updated version of the platform:
$ sudo docker-compose up -d
Once the platform is up and running, you can login using your user credentials and test it.
Warning
Be aware, that during the update the following files will be overwritten:
/etc/rasaplatform/docker-compose.yml
/etc/rasaplatform/.env
Make sure there are no changes in these files that you still need. E.g.
instead of directly modifying docker-compose.yml
you should rather
create a new file called docker-compose.override.yml
. Docker will
automatically take that file into account and override any attributes in
docker-compose.yml
with changes from the override file.
Next Steps¶
Now that you have the main pieces of the Platform installed, you can go ahead and Setting Up Your Bot.
Manual Installation¶
Make sure
python
,docker
, anddocker compose
are installed on your Platform. Detailed instructions can be found in the docker documentation. You should be able to run$ docker-compose --version
Create the project directory and switch to it:
$ mkdir /etc/rasaplatform $ cd /etc/rasaplatform
Download the Platform files (
docker-compose.yml
andrasa_commands.py
) that contain the containers and their setup (replacinglatest
with the version to install):$ wget -qO docker-compose.yml https://storage.googleapis.com/rasa-releases/stable/docker-compose.yml $ wget -qO rasa_commands.py https://storage.googleapis.com/rasa-releases/stable/rasa_commands.py
Create the authentication file to download containers from the docker registry. To authenticated with the registry that contains the Platform containers, you need to create a file in
/etc/rasaplatform/gcr-auth.json
that contains the JSON of the fielddocker_registry_license
from your license.Make sure to copy everything between the outer
"
of thedocker_registry_license
key to that file. The contents of/etc/rasaplatform/gcr-auth.json
should look like this:{ "type": "service_account", "project_id": "rasa-platform", "private_key_id": "sdferw234qadst423qafdgxhw", "private_key": "-----BEGIN PRIVATE KEY-----\nMIIEvfwrt423qwadsfghtzw0BAQEFAASCBKgwggSkAgEAAoIBAQCgt338FkWbW13dghtzew4easdf5wAi15jrA9t4uOk8dghrtze4weasfgdhtAFZNfrLgvr2\nPBTu1lAJDLo136ZGTdMKi+/TuRqrIMg/sr8q0Ungish8v6t5Jb4gsjBi9StytCT4\nhWXDL3qeadfsgeDOudl6c3iMzylBws+VffrFfaZWjDpGtxmlYwIUa2e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\nsjAsuAH4Iz1XdfdenzGnyBZH\n-----END PRIVATE KEY-----\n", "client_email": "company@rasa-platform.iam.gserviceaccount.com", "client_id": "114123456713428149", "auth_uri": "https://accounts.google.com/o/oauth2/auth", "token_uri": "https://accounts.google.com/o/oauth2/token", "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs", "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/company%40rasa-platform.iam.gserviceaccount.com" }
Login to the docker registry
$ sudo docker login -u _json_key -p "$(cat /etc/rasaplatform/gcr-auth.json)" https://gcr.io
Create the docker environment file in
/etc/rasaplatform/.env
with the following content:RASA_PLATFORM_VERSION=stable RASA_NLU_TOKEN=<random_string> RASA_CORE_TOKEN=<random_string> RASA_PLATFORM_TOKEN=<random_string> PASSWORD_SALT=<random_string> MONGO_PASSWORD=<random_string> JWT_SECRET=<random_string> RABBITMQ_PASSWORD=<random_string>
For
<random_string>
please use secure strings, e.g. randomly generated character sequences.For the token and password salt fields, enter any string of your choice. These will be used to hash passwords. Note that if you change these you will have to create new logins for everyone.
You will also need to set a Rasa NLU and Rasa Core Token. These are used to authorize the communication among the containers.
Note
Make sure to generate a different unique <random_string> for each field! E.g. running this multiple times:
$ openssl rand -base64 12
Create a credentials file at
/etc/rasaplatform/credentials.yml
containing:rasa: url: http://api:5002
where url corresponds to your RASA_PLATFORM_HOST, if defined.
Start up the Platform (
-d
will run the Platform in the background):$ sudo docker-compose up -d
Cluster Deployment (Kubernetes & Openshift)¶
Make sure
docker
, anddocker compose
andkompose
are installed on your server. Detailed instructions can be found in the Docker documentation and in the Kompose documentation. You should be able to run:$ docker-compose --version $ kompose version
Create a project directory and switch to it:
$ mkdir ~/rasaplatform $ cd ~/rasaplatform
Download the docker-compose file (
docker-compose.yml
) that contain the containers and their setup (replacinglatest
with the version to install):$ wget -qO docker-compose.yml https://storage.googleapis.com/rasa-releases/stable/docker-compose.yml
Create the authentication file to download containers from the docker registry. To be authenticated with the registry that contains the Platform containers, you need to create a file in
~/rasaplatform/gcr-auth.json
that contains the JSON of the fielddocker_registry_license
from your license.Make sure to copy everything between the outer
"
of thedocker_registry_license
key to that file. The contents of~/rasaplatform/gcr-auth.json
should look like this:{ "type": "service_account", "project_id": "rasa-platform", "private_key_id": "sdferw234qadst423qafdgxhw", "private_key": "-----BEGIN PRIVATE KEY-----\nMIIEvfwrt423qwadsfghtzw0BAQEFAASCBKgwggSkAgEAAoIBAQCgt338FkWbW13dghtzew4easdf5wAi15jrA9t4uOk8dghrtze4weasfgdhtAFZNfrLgvr2\nPBTu1lAJDLo136ZGTdMKi+/TuRqrIMg/sr8q0Ungish8v6t5Jb4gsjBi9StytCT4\nhWXDL3qeadfsgeDOudl6c3iMzylBws+VffrFfaZWjDpGtxmlYwIUa2e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\nsjAsuAH4Iz1XdfdenzGnyBZH\n-----END PRIVATE KEY-----\n", "client_email": "company@rasa-platform.iam.gserviceaccount.com", "client_id": "114123456713428149", "auth_uri": "https://accounts.google.com/o/oauth2/auth", "token_uri": "https://accounts.google.com/o/oauth2/token", "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs", "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/company%40rasa-platform.iam.gserviceaccount.com" }
Login to the docker registry. This will create a new entry in the docker config file.
$ sudo docker login -u _json_key -p "$(cat ~/rasaplatform/gcr-auth.json)" https://gcr.io
Create a new image pull secret. If you already have a
.dockercfg
file for the registry, you can create a secret from that file by running (if you are using Kubernetes replaceoc
withkubectl
):$ oc create secret generic <pull_secret_name> \ --from-file=.dockercfg=<path/to/.dockercfg> \ --type=kubernetes.io/dockercfg
Add the secret to your service account. The name of the service account in this example should match the name of the service account the pod uses; default is the default service account (if you are using Kubernetes replace
oc
withkubectl
):$ oc secrets link default <pull_secret_name> --for=pull
For more information please visit the OpenShift documentation.
Create the docker environment file
.env
with the following content:RASA_PLATFORM_VERSION=stable RASA_NLU_TOKEN=<random_string> RASA_CORE_TOKEN=<random_string> RASA_PLATFORM_TOKEN=<random_string> PASSWORD_SALT=<random_string> MONGO_PASSWORD=<random_string> JWT_SECRET=<random_string> RABBITMQ_PASSWORD=<random_string>
For
<random_string>
please use secure strings, e.g. randomly generated character sequences.For the token and password salt fields, enter any string of your choice. These will be used to hash passwords. Note that if you change the password salt you will have to create new logins for everyone.
You will also need to set a Rasa NLU and Rasa Core token. These are used to authorize the communication among the containers.
Note
Make sure to generate a different unique <random_string> for each field! E.g. running this multiple times:
$ openssl rand -base64 12
Create certificate files which are required by NGINX to establish HTTPS connections.
$ openssl dhparam -out dh.pem $DH_SIZE 4096 $ openssl req -x509 -newkey rsa:4086 \ -subj "/C=XX/ST=XXXX/L=XXXX/O=XXXX/CN=localhost" \ -keyout "privkey.pem" \ -out "fullchain.pem" \ -days 3650 -nodes -sha256
Once the files are created, create a secret called
nginx-certs
. The secret will have three entries:dh
: copy here the content of thedh.pem
file.fullchain
: copy here the content of thefullchain.pem
file.privkey
: copy here the content of theprivkey.pem
file.
This secret will be later mounted by the
nginx
pod.Create a file called
agreement.yml
with the following content to accept the terms and conditions.apiVersion: v1 data: agree: openshift kind: ConfigMap metadata: name: agreement
Create a file called
configuration-files.yml
with the following content:apiVersion: v1 data: core-credentials: | rasa: url: http://api:5002 core-endpoints: | models: url: ${RASA_CORE_MODEL_SERVER} token: ${RASA_PLATFORM_TOKEN} wait_time_between_pulls: ${RASA_CORE_MODEL_PULL_INTERVAL} nlu: url: ${RASA_NLU_HOST} token: ${RASA_NLU_TOKEN} nlg: url: ${RASA_NLG_ENDPOINT_URL} token: ${RASA_PLATFORM_TOKEN} tracker_store: store_type: mongod url: ${MONGO_HOST} username: ${MONGO_USERNAME} password: ${MONGO_PASSWORD} db: ${MONGO_DB} event_broker: url: ${RABBITMQ_HOST} username: ${RABBITMQ_USERNAME} password: ${RABBITMQ_PASSWORD} action_endpoint: url: ${RASA_USER_APP}/webhook token: "" nlu-endpoints: | model: url: ${RASA_NLU_MODEL_SERVER} token: ${RASA_PLATFORM_TOKEN} environments: | core: production: url: http://core:5005 token: ${RASA_CORE_TOKEN} db: nlu-backend development: url: http://core-development:5005 token: ${RASA_CORE_TOKEN} db: core-development worker: url: http://core-worker:5005 token: ${RASA_CORE_TOKEN} db: core-development nlu: production: url: http://nlu:5000 token: ${RASA_NLU_TOKEN} development: url: http://nlu-development:5000 token: ${RASA_NLU_TOKEN} worker: url: http://nlu-worker:5000 token: ${RASA_NLU_TOKEN} kind: ConfigMap metadata: name: configuration-files
Generate the deployment files by running
$ docker-compose config > docker-compose.config.yml
Set the used docker-compose file specification in
docker-compose.config.yml
to version3
:version: '3' services: ...
Update the NGINX service to use the short-hand syntax to expose ports. The NGINX service should look like this:
nginx: restart: always image: "gcr.io/rasa-platform/nginx:${RASA_PLATFORM_VERSION:-stable}" ports: - "80:8080" - "443:8443" volumes: - ./certs:/opt/bitnami/nginx/conf/bitnami/certs - ./terms:/opt/bitnami/nginx/conf/bitnami/terms depends_on: - nlu - core - api - platform-ui - event-service - app
Convert
docker-compose.config.yml
with (if you are using Kubernetes replace--provider OpenShift
with--provider Kubernetes
):$ kompose convert -f docker-compose.config.yml --provider OpenShift
This will create all files needed for the deployment.
Change the volumes in the
api-deploymentconfig.yaml
file. ThevolumeMounts
section should look like this:volumeMounts: - mountPath: /app/nlu-models name: api-claim0 - mountPath: /app/core-models name: api-claim1 - mountPath: /logs name: api-claim2 - mountPath: /app name: environment_config
and the
volumes
section should look like this:volumes: - name: api-claim0 persistentVolumeClaim: claimName: api-claim0 - name: api-claim1 persistentVolumeClaim: claimName: api-claim1 - name: api-claim2 persistentVolumeClaim: claimName: api-claim2 - name: environment_config configMap: name: configuration-files items: - key: environments path: environments.yml
You can then remove the volume claim file which was used to mount
environments.yml
.Change the volumes in the following files
nlu-deploymentconfig.yaml
,nlu-development-deploymentconfig.yaml
andnlu-worker-deploymentconfig.yaml
. ThevolumeMounts
section should look like this:volumeMounts: - mountPath: /app/nlu-models name: {pod_name}-claim0 - mountPath: /app/config name: config
and the
volumes
sections should look like this:volumes: - name: {pod_name}-claim0 persistentVolumeClaim: claimName: {pod_name}-claim0 - name: config configMap: name: configuration-files items: - key: nlu-endpoints path: endpoints.yml
Where
{pod_name}
will depend on the deployment that is getting updated. The correct values arenlu
,nlu-development
,nlu-worker
for their respective files. You can then remove the volume claim files which were used for the mounts ofendpoints.yml
.Change the volumes in the following files
core-deploymentconfig.yaml
,core-development-deploymentconfig.yaml
andcore-worker-deploymentconfig.yaml
. ThevolumesMounts
section should look like this:volumeMounts: - mountPath: /app/models name: {pod_name}-claim0 - mountPath: /app/default name: {pod_name}-claim0 - mountPath: /app/config name: config
and the
volumes
section should look like this:volumes: - name: {pod_name}-claim0 persistentVolumeClaim: claimName: {pod_name}-claim0 - name: config configMap: name: configuration-files items: - key: core-endpoints path: endpoints.yml - key: core-credentials path: credentials.yml
Where
{pod_name}
will depend on the deployment that is getting updated. The correct values arecore
,core-development
,core-worker
for their respective files. You can then remove the volume claim files which were used for the mounts ofendpoints.yml
andcredentials.yml
.Remove the volume claim files which were used for the mounts of
endpoints.yml
.Change the volumes in
nginx-deploymentconfig.yaml
. ThevolumeMounts
section should look like this:volumeMounts: - mountPath: /opt/bitnami/certs name: nginx-certs-secret - mountPath: /opt/bitnami/nginx/conf/bitnami/terms name: agreement
and the
volumes
sections should look like this:volumes: - configMap: items: - key: agree path: agree.txt name: agreement name: agreement - name: nginx-certs-secret secret: items: - key: dh path: dh.pem - key: fullchain path: fullchain.pem - key: privkey path: privkey.pem secretName: nginx-certs
The previously generated NGINX volume claim files can now be removed since they were replaced by the configMap and secret.
Now you can use the generated files to deploy Rasa Platform, either using the OpenShift / Kubernetes CLI or the web console.
Create the required services:
- nginx
- platform-ui
- api
- mongo
- app
- core
- core-development
- core-worker
- nlu
- nlu-development
- nlu-worker
- rabbit
To access the platform expose the
nginx
service with (if you are using Kubernetes replaceoc
withkubectl
):$ oc expose service/nginx
Alternatively create your own route from the web console.
Using the terminal of the
API
pod create the first user by running:$ cd scripts $ python manage_users.py create [username] [password] [role]
Possible values for
role
areadmin
,user
, andannotator
.
Environment Variables¶
Global environment variables¶
This group of variables is mainly used by docker-compose. All the variables get interpolated when starting the services
with docker-compose up
and then are passed to services. It is possible to see the docker-compose.yml
file with the substituted variables by using docker-compose config
.
Variable | Explanation |
---|---|
PLATFORM_UI_VERSION | The compatible UI version for the Platform. |
PLATFORM_DEMO_VERSION | Custom Action Server version. |
CORE_VERSION | The version of Rasa Core used by the Platform. |
CORE_SDK_VERSION | The SDK version used by the Custom Action Server. |
NLU_VERSION | The version of Rasa NLU used by the Platform. |
SPACY_VERSION | The version of Spacy used by Rasa NLU. |
SPACY_ENGLISH_MODEL_BASE | English language model used by Spacy. |
SPACY_ENGLISH_MODEL_VERSION | Version of the English language model used by Spacy. |
SPACY_GERMAN_MODEL_BASE | German language model used by Spacy. |
SPACY_GERMAN_MODEL_VERSION | Version of the German language model used by Spacy. |
TENSORFLOW_VERSION | The version of Tensorflow used. |
RASA_NLU_TOKEN | Authentication token for the NLU service. This is used by other services to communicate with NLU. |
RASA_CORE_TOKEN | Authentication token for the Core service. This is used by other services to communicate with Core. |
JWT_SECRET | JWT token for authentication between services and the API. |
The Core variables group¶
These variables define the behaviour of Rasa Core and how the other services connect to it. This group of variables is used by the following services:
api
core
Variable | Explanation |
---|---|
RASA_CORE_HOST | URL of the Core service. |
RASA_CORE_MODEL_DIR | The directory in which Core models are stored. |
RASA_CORE_MODEL_PULL_INTERVAL | Pull interval for Core, in seconds. |
RASA_CORE_MODEL_SERVER | URL of the model server (API). |
RASA_NLG_ENDPOINT_URL | Natural Language Generation endpoint. |
RASA_REMOTE_CORE_ENDPOINT_URL | Must be the same as RASA_CORE_HOST . |
RASA_USER_APP | URL of the custom action server. |
RASA_CORE_WORKER_TOKEN | Set equal to RASA_CORE_TOKEN . |
The MongoDB variables group¶
These variables define the behaviour of MongoDB and how the other services connect to it. For more information please visit https://github.com/bitnami/bitnami-docker-mongodb. This group of variables is used by the following services:
api
core
event-service
Variable | Explanation |
---|---|
MONGO_INITDB_ROOT_USERNAME | This variable is used to create the root user during the startup of MongoDB. |
MONGO_INITDB_ROOT_PASSWORD | This variable is used to create the root password during the startup of MongoDB. |
MONGO_DB | The name of the database used by the services. |
MONGO_HOST | URL of the MongoDB database. It should use the mongodb protocol. |
MONGO_PASSWORD | This variable is used by other services to access MongoDB.
It should be equal to MONGO_INITDB_ROOT_PASSWORD . |
MONGO_USERNAME | This variable is used by other services to access MongoDB.
It should be equal to MONGO_INITDB_ROOT_USERNAME . |
The NLU variables group¶
These variables define the behaviour of NLU and how the other services connect to it. This group of variables is used by the following services:
api
core
nlu
Variable | Explanation |
---|---|
RASA_DUCKLING_HTTP_URL | URL of Duckling, used for entity extraction. |
RASA_NLU_HOST | URL of Rasa NLU. This is used by other services to connect to Rasa NLU. |
RASA_NLU_MODEL_DIR | The path where the NLU models are stored. |
RASA_NLU_MODEL_SERVER | The URL used by other services to request NLU models. |
RASA_NLU_WORKER_TOKEN | Set equal to RASA_NLU_TOKEN |
The Platform API variables group¶
These variables define the behaviour of the Platform API and how the other services connect to it. This group of variables is used by the following services:
api
core
nlu
Variable | Explanation |
---|---|
PASSWORD_SALT | Salt used to securely store the users passwords. |
PLATFORM_USER_ANALYTICS | Flag used to show/hide the analytics tab. |
RASA_PLATFORM_HOST | The URL of the API services. This is used by other services to connect to the API. |
RASA_PLATFORM_TOKEN | The token used for authentication between other services and the API. |
SANIC_RESPONSE_TIMEOUT | General timeout for request (seconds). |
SELF_PORT | Port used by the API service. |
The RabbitMQ variables group¶
These variables define the behaviour of the RabbitMQ and how the other services connect to it. For more information please visit https://github.com/bitnami/bitnami-docker-rabbitmq#configuration. This group of variables is used by the following services:
api
core
event-service
Variable | Explanation |
---|---|
RABBITMQ_DEFAULT_PASS | This variable is used to create the password for the default user during startup. |
RABBITMQ_DEFAULT_USER | This variable is used to create the username for the default user during startup. |
RABBITMQ_HOST | Hostname of the container hosting RabbitMQ. |
RABBITMQ_PASSWORD | This is used by other services to access RabbitMQ. Must be
equal to RABBITMQ_DEFAULT_PASS . |
RABBITMQ_USERNAME | This is used by other services to access RabbitMQ. Must be
equal to RABBITMQ_DEFAULT_USER . |
The UI file¶
This file is used by the following services:
platform-ui
Variable | Explanation |
---|---|
REACT_APP_API_URL | The URL used by the application as the base for API calls. |