Install a Standalone Analytics Container
You can install a standalone deployment of the analytics container to set up your data files. The accuracy of the data files are important for a proper analysis of your entitlements.
The deployment uses the Docker deployer machine to set up a standalong analytics container on the target node. The analytics container is automatically installed at the node where the Spark master is running.
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Review the hardware and software specifications as outlined in the Release Notes (LINK)
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Ensure your deployers have the appropriate system access to the ForgeRock Google Cloud Repository repository site to access the Docker image. The fully qualified image is: gcr.io/forgerock-autoid//autoid/dev-compact:deployer-rel-31-spark2.4.4-analytics-19-elektra
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The image contains release 31 of the microservices
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Apache Spark 2.4.4
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Analytics container version 19
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On both the control and target nodes, make sure you have CentOS 7 and Python installed on all nodes. Python is packaged with CentOS 7. Autonomous Identity works with the following versions:
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CentOS 7 uses Python 2.7.5 in its base package repository.
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CentOS 7.7 uses Python 3.7.2 in its base package repository.
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Ensure that you have access to the ForgeRock git repository. The ForgeRock Git repository has some scripts that you can clone to your system.
Getting Started
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On the Target node, download the
registry_key.json
to access the Google Cloud Repository (gcr.io) from here. -
Access the Google Cloud Repository using the
registry_key.json
.$ [../../resources/install.bash:#access-gcr]
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Download the analytics container.
$ docker pull gcr.io/forgerock-autoid/analytics:v14
Start the Analytics Container
To start the analytics container, replace the following values for your environment:
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SPARK_MASTER_URL
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SPARK_HOST
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DB_HOST
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DB_PORT
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DB_CERT_PASSWORD
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DB_SSL_ENABLED
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DB_USER
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DB_PASSWORD
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CONFIGURATION_SERVICE_URL
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CONFIGURATION_SERVICE_USER
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CONFIGURATION_SERVICE_PASSWORD
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Run the analytics container with the variables for your environment.
$ [../../resources/install.bash:#start-standalone-analytics]
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Create a symlink to the Python runtime on the host.
$ sudo ln -s /opt/zoran/python-3.6/bin/python3.6 /usr/local/bin/python3.6
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Configure the Template
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Run the create-template function on the Analytics container. The command creates the
/data/conf/analytics_init_config.yml
.$ docker exec -it analytics bash analytics create-template
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Edit the
/data/conf/analytics_init_config.yml
file with the data directory and user column descriptions. -
Make sure the csv data files are placed in the path as specified in the
/data/conf/analytics_init_config.yml
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Apply the template.
$ docker exec -it analytics bash analytics apply-template
Run the Analytics Pipeline
Command | Description |
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analytics create-template |
When you run this command, the analytics container creates the |
analytics apply-template |
Make sure to copy the .csv files to the |
analytics create-ui-config |
Creates the |
analytics apply-ui-config |
Applies the |
analytics validate |
Runs data validation. |
analytics ingest |
Ingests data into Autonomous Identity. |
analytics audit |
Runs a data audit to ensure if meets the specifications. |
analytics train |
Runs an analytics training run. |
analytics predict-as-is |
Runs an as-is predictions. |
analytics predict-recommendation |
Runs recommendations. |
analytics publish |
Publishes the analytics. |
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Run the Analytics pipeline using one of the above commands.
$ docker exec -it analytics bash analytics <command>