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Compose-Services

Docker-compose setup for experimental commons, small commons, or local development of the Gen3 stack. Production use should use cloud-automation.

Introduction

This setup uses Docker containers for postgres, indexd, fence, peregrine, sheepdog, data-portal and nginx. Images for the cdis microservices will be pulled from quay.io (master), while postgres (9.5) and nginx (1.14) images will be pulled from Docker Hub. Nginx will be used as a reverse proxy to each of the services. Config file formats were copied from cloud-automation and stored in the api_configs directory and modified for local use with Docker Compose. Setup scripts for some of the containers are kept in the scripts directory.

Some Database Info

Database setup only has to occur the very first time you setup your local gen3 Docker Compose environment, as this docker-compose environment is configured to create a persistent volume for postgres. The environment configuration is set up to automatically run setup scripts for the postgres container and set up the following:

  1. 3 databases
    • metadata_db
    • fence_db
    • indexd_db
  2. 4 users with passwords and superuser access
    • fence_user
    • peregrine_user
    • sheepdog_user
    • indexd_user

Setup

Dependencies

  • openssl
  • Docker and Docker Compose

Docker Setup

The official Docker installation page can be found here. If you've never used Docker before, it may be helpful to read some of the Docker documentation to familiarize yourself with containers.

Docker Compose Setup

If you are using Linux, then the official Docker installation does not come with Docker Compose. The official Docker Compose installation page can be found here. You can also read an overview of what Docker Compose is here if you want some extra background information. Go through the steps of installing Docker Compose for your platform, then proceed to setting up credentials.

Setting up Credentials

Setup credentials for fence, a custom root CA and SSL certs with the provided script by running either:

bash creds_setup.sh
OR
bash creds_setup.sh YOUR CUSTOM DOMAIN

This script will create temp_creds and temp_keys directories with the credential files in it. The script by default generate SSL cert for localhost, if you are running this in a remote server with an actual domain, you can run bash creds_setup.sh YOUR_DOMAIN. This will create SSL cert signed by the custom CA so that the microservices can talk to each other without bypassing SSL verification. If you are setting this up on AWS, ensure that you use an Elastic IP address BEFORE you set up and use that as your domain.On an EC2 instance for example, this would be your ec2-YOUR-Elastic-IP-Addr.us-region-number.compute.amazonaws.com. This will save a lot of time and avoid editing the individual files to set up the hostname(fence_creds.json, peregrine_creds.json, and sheepdog_creds.json) when the machine is rebooted. This is because each of the microservices can be configured to run on separate machines and thus have their respective configuration files. You will still need to bypass SSL verification when you hit the services from the browser. If you have real certs for your domain, you can copy to temp_creds/service.key and temp_creds/service.crt to overwrite our dev certs.

If you are using MacOS, you may run into an error with the default MacOS OpenSSL config not including the configuration for v3_ca certificate generation. You can refer to the solution on this Github issue on a related issue on Jetstack's cert-manager.

This Docker Compose setup also requires Google API Credentials in order for the fence microservice to complete its authentication. If you have Google API credentials set up already that you would like to use with the local gen3 Docker Compose setup, simply add https://localhost/user/login/google/login/ OR https://YOUR_REMOTE_MACHINE_DOMAIN/user/login/google/login/ to your Authorized redirect URIs in your credentials. Make a note of your Google Client Id and Client Secret. Make a copy of the env.properties.template in the api_configs folder and call it env.properties. An AWS Policy and an AWS User with the AWS policy attached to the AWS User would need to be created. The AWS Policy should allow full access to the S3 Bucket which would store the raw image and other files and the ability to assume a role (STS) to access that bucket are required. Store the Access Key and Secret Access Key securely and note the ARN of the policy created.

ICDCHOST=YOUR HOST NAME (e.g. ICDCHOST=ec2-xx-yy-ww-zzz.us-west-2.compute.amazonaws.com) GOOGLE_C_SECRET=YOUR_GOOGLE_CLIENT_ SECRET GOOGLE_C_ID=YOUR_GOOGLE_CLIENT_ ID AWS_ACCESS_KEY_ID=YOUR_AWS_ACCESS_KEY_ID AWS_SECRET_ACCESS_KEY=YOUR_AWS_SECRET_ACCESS_KEY AWS_ROLE_ARN=arn:aws:iam::ACCOUNT_ID:role/SAMPLE_POLICY_ARN (Remember to escape the backslash) S3_BUCKET_NAME=S3_BUCKET_NAME_TO_STORE_RAW_FILES (i.e. Bucket name to store BAM/Image Files)

After updating env.properties, go ahead and execute ./setup_env.sh . This will copy that info to all the desired setting files for fence, indexd, peregrine and sheepdog.

If you do not already have Google API Credentials, follow the steps below to set them up. See image below for example on a sample Google account.

Redirection Set up

Setting up Google+ API and Google API Credentials for Fence

Fence uses the Google+ API to log users in using their Google Accounts. In order for fence to work properly, the Google+ API must be enabled for the Google Account your are creating Google API Credentials with. To enable the Google+ API, go the library page of the Google Developer Console and search for Google+ API. Click on the card and follow the instructions to enable it.

To set up Google API Credentials, go to the credentials page of the Google Developer Console and click the 'Create Credentials' button. Follow the prompts to create a new OAuth Client ID for a Web Application. Add https://localhost/user/login/google/login/ OR https://YOUR_REMOTE_MACHINE_DOMAIN/user/login/google/login/ to your Authorized redirect URIs in the Credentials. Then copy your client ID and client secret and use them to fill in the 'google_client_secret' and 'google_client_id' fields in the api_configs/fence_creds.json JSON file.

Setting up Users

To set up user privileges for the services, please edit the apis_configs/user.yaml file, following the example format shown in the file. The fence container will automatically sync this file to the fence_db database on startup. If you wish to update user privileges while the containers are running (without restarting the container), just edit the apis_configs/user.yaml file and then run

docker exec -it fence_container_name fence-create sync --yaml user.yaml

This command will enter the fence container to run the fence-create sync command, which will update your user privileges.

Start running your local gen3 Docker Compose environment

Now that you are done with the setup, all Docker Compose features should be available. Here are some useful commands:

The basic command of Docker Compose is

docker-compose up

which can be useful for debugging errors. To detach output from the containers, run

docker-compose up -d

When doing this, the logs for each service can be accessed using

docker logs

To stop the services use

docker-compose down

As the Docker images are pulled from quay.io, they do not update automatically. To update your Docker images, run

docker-compose pull
docker image prune -f

These commands may take a while, and they also may fail. If they do fail, simply rerun them, or just update/remove images one at a time manually.

Dev Tips

When developing, you can have local repositories of the services you are working on and use volumes to mount your local repository files onto the containers to override the containers' code (which is built from GitHub using quay.io). Then, you can restart a single container with

docker-compose restart [CONTAINER_NAME]

after you update some code in order to see changes without having to rebuild all the microservices. Keep in mind that running docker-compose restart does not apply changes you make in the docker-compose file. Look up the Docker documentation for more information about volumes.

Running Docker Compose on a Remote Machine

To run Docker Compose on a remote machine, modify the hostname field in fence_creds.json, peregrine_creds.json, and sheepdog_creds.json in the apis_configs directory.


Environent Details

The sandbox ecosystem deployed thus architecturally looks as shown below: Sandbox

All the microservices communicate with the Postgres Container based on the configuration specified above. Once the services are up and running, the environment can be visualized using the windmill microservice running on port 80 by typing the URL of the machine on which the containers are deployed. Please see example screenshot below as an example:

Launch Portal

Upon clicking 'Login from Google' and providing Google Credentials(if the same Google Account is used where the developer credentials came from), the system redirects the user to their landing page as shown below:

Logged Into Portal

Using the Data Commons

For some general information about Gen3 Data Commons and how they work (such as how to access and submit data), visit the official site. The section below will go over some useful technical aspects of Gen3.

Programs and Projects

In a Gen3 Data Commons, programs and projects are two administrative nodes in the graph database that serve as the most upstream nodes. A program must be created first, followed by a project. Any subsequent data submission and data access, along with control of access to data, is done through the project scope.

To create a program, visit the url where your Gen3 Commons is hosted and append /_root. If you are running the Docker Compose setup locally, then this will be localhost/_root. Otherwise, this will be whatever you set the hostname field to in the creds files for the services with /_root added to the end. Here, you can choose to either use form submission or upload a file. I will go through the process of using form submission here, as it will show you what your file would need to look like if you were using file upload. Search for "program," and then fill in the "dbgap_accession_number" and "name" fields, and hit "Submit". If the message is green ("succeeded:200"), that indicates success, while a grey message indicates failure. More details can be viewed by clicking on the "DETAILS" button.

To create a project, visit the url where your Gen3 Commons is hosted and append the name of the program you want to create the project under. For example, if you are running the Docker Compose setup locally and would like to create a project under the program "Program1", the url you will visit will be localhost/Program1. You will see the same options to use form submission or upload a file. This time, search for "project," and then fill in the fields and hit "Submit." Again, a green message indicates success while a grey message indicates failure, and more details can be viewed by clicking on the "DETAILS" button.

Once you've created a program and a project, you're ready to start submitting data for that project! Please note that Data Submission refers to meta data regarding the file(s) (Image, Sequencing files etc.)that are to be uploaded. Please refer to the Gen3 website for additional details .

Controlling access to data

Access to data and admin privileges in Gen3 are controlled using fence through the user.yaml file found in the apis_configs directory. Admin privileges are required to create administrative nodes, which include programs and projects. For each user, you can control admin status as well as specific per-project permissions. The format of the user.yaml file is shown below:

users:
  user_email_1:
    admin: True
    projects:
    - auth_id: project1
      privilege: ['create', 'read', 'update', 'delete', 'upload', 'read-storage']

Refer to Setting up Users to review how to apply the changes made in the user.yaml file to the database

Changing the data dictionary

For an introduction to the data model and some essential information for modifying a data dictionary, please read this before proceeding.

The data dictionary the commons uses is dictated by either the DICTIONARY_URL or the PATH_TO_SCHEMA_DIR environment variable in both sheepdog and peregrine. The default value for DICTIONARY_URL is set to https://s3.amazonaws.com/dictionary-artifacts/datadictionary/develop/schema.json and the default value for PATH_TO_SCHEMA_DIR is set to the example-schemas directory which is downloaded as part of the compose-services repo (from here). Both correspond to the developer test data dictionary, as one is on AWS and one is a local data dictionary setup. To override this default, edit the environment fields in the peregrine section of the docker-compose.yml file. This will change the value of the environment variable in both sheepdog and peregrine. An example, where the DICTIONARY_URL and PATH_TO_SCHEMA_DIR environment variables is set to the default values, is provided in the docker-compose.yml.

NOTE: Only one of the two environment variables can be active at a time. The data commons will prefer DICTIONARY_URL over PATH_TO_SCHEMA_DIR. To reduce confusion, keep the variable you're not using commented out.

In addition to changing the DICTIONARY_URL or PATH_TO_SCHEMA_DIR field, it may also be necesary to change the APP environment variable in data-portal. This will only be the case if the alternate dictionary deviates too much from the default dev dictionary.

As this is a change to the Docker Compose configuration, you will need to restart the Docker Compose to apply the changes.

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Repository to store the ICDC Dockerized Ecosystem

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