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deepphe-cr-release's Introduction

DeepPhe Stream Multi-Container Stack - release branch

Changes needed to make a release

  • 1: Place the source code zip file, for instance v0.4.0-cr-release.zip, to the directory dphe-stream. And this zip file will be used to build the dphe-stream docker image.
  • 2: Edit the dphe-stream/Dockerfile and specify to use the target release version, for instance 0.4.0.

Overview of components and architecture

This multi-container docker stack consists of the following 2 containers as shown in the diagram:

  • 1 : dphe-stream-nginx
  • 2 : dphe-stream

Components and architecture diagram

  • When the client makes an API call via HTTP request to the dphe-stream-nginx container, the request gets proxied via Nginx to the REST API server running within the upstream container dphe-stream, which fullfills the actual handling by calling the NLP pipeline.
  • As a requirement, we do not persist information anywhere except temporarily within the jvm of the dphe-stream container. We only use an embedded instance of neo4j for the system to read the static ontology graph.
  • The REST API in the dphe-stream container is just a thin wrapper that exposes the endpoints to accept requests of document and patient summarizations, and it is the backend NLP pipeline that does the heavy lifting as well as returns the extracted information.

Overview of tools

Note: Docker Compose requires Docker to be installed and running first.

Docker post-installation configurations: Linux only

The Docker daemon binds to a Unix socket instead of a TCP port. By default that Unix socket is owned by the user root and other users can only access it using sudo. The Docker daemon always runs as the root user.

If you're using Linux and you don't want to preface the docker command with sudo, you can add users to the docker group:

sudo usermod -aG docker $USER

Then log out and log back in so that your group membership is re-evaluated. If testing on a virtual machine, it may be necessary to restart the virtual machine for changes to take effect.

Note: the following instructions with docker commands are based on managing Docker as a non-root user.

These permissions do not appear to be a concern on OS X and Windows.

Build docker images

Specify auth token (optional)

Before starting building the child images, specify the auth token in dphe-stream/deepphe.properties. This auth token will be used later when interacting with the REST API calls via the standard HTTP request Authorization header with the Bearer scheme:

Authorization: Bearer <token>

This auth layer applies to all the REST API requests before they can reach to the actual API endpoints.

A default token is provided in the dphe-stream/deepphe.propertiers file. For greater security, it is strongly advised that you change this token to a new value for deployment instance.

Build dphe-stream-nginx and dphe-stream images

Next go back to the project root directory where you can find the docker-compose.yml:

docker-compose build --no-cache

Vulnerability scanning for local images (optional)

Vulnerability scanning for Docker local images allows us to review the security state of the container images and take actions to fix issues identified during the scan, resulting in more secure deployments. The scan command is available by default in Docker version 20.10.x and newer.

Note that you might have to login via

docker scan --login

Once logged in, you can run the scans as follows:

docker scan --dependency-tree --file ./dphe-stream/Dockerfile dphe-stream:0.4.0-cr
docker scan --dependency-tree --file ./dphe-stream-nginx/Dockerfile dphe-stream-nginx:0.4.0-cr

Start up services

There are two configurable environment variables to keep in mind before starting up the containers:

  • HOST_UID: the user id on the host machine to be mapped to all the containers. Default to 1000 if not set or null.
  • HOST_GID: the user's group id on the host machine to be mapped to all the containers. Default to 1000 if not set or null.

We can use the default values if the ouput of the below command is 1000 for both uid and gid of the current user who's going to spin up the containers.

id

In security practice, the processes within a running container should not run as root, or assume that they are root. The system user on the host machine should be in the docker group and it should also be the user who builds the images and starts the containers. That's why we wanted to use this user's UID and GID within the containers to avoid security holes and file system permission issues as well.

docker-compose up -d

This command spins up all the services (in the background as detached mode and leaves them running) defiened in the docker-compose.yml and aggregates the output of each container.

Note: Make sure the port 8080 and 8181 are not already allocated, otherwise the containers would fail to start.

Note: Container initialization takes some time, you can use the following command in another terminal window to monitor the progress:

docker-compose logs -f --tail="all" 

Once the containers are up, the dphe-stream-nginx checks agains the upstream dphe-stream service every 5 seconds to determine if the REST API is ready. You'll see the following logging message during the initialization:

dphe-stream-nginx    | The upstream 'dphe-stream' service is initializing and not ready yet - sleeping 5 seconds...

And once the upstream dphe-stream service is fully initialized and becomes available:

dphe-stream          | 2022-08-12 01:34:43.182  INFO 8 --- [           main] o.s.b.web.embedded.jetty.JettyWebServer  : Jetty started on port(s) 8080 (http/1.1) with context path '/'
dphe-stream          | 2022-08-12 01:34:43.235  INFO 8 --- [           main] o.h.d.stream.rest.StreamRestApplication  : Started StreamRestApplication in 31.873 seconds (JVM running for 33.429)
dphe-stream-nginx    | The upstream 'dphe-stream' service is ready :-)

Interact with the DeepPhe REST API

You will have the following API base URL for the REST API container:

  • dphe-stream: http://localhost:8080/deepphe

Note: You will need to send over the auth token, specified in dphe-stream/deepphe.properties, in the Authorization header for each HTTP request:

Authorization: Bearer <token>

Note, if desired, replace the <token> with your custom token value, the default is AbCdEf123456. And if the auth token is missing from request or an invalid token being used, you'll get the HTTP 401 Unauthorized response.

Submit a document, do not cache information

REST API Value
HTTP method GET
Resource pattern http://localhost:8080/deepphe/summarizeDoc/doc/<docId>
HTTP Headers Content-Type: text/plain
Authorization: Bearer <token>
HTTP request body Text content of document
Response JSON object of resuting data

Submit a document, cache information for patient summary

The patient ID is not used in document processing but is required for future patient summarization.

REST API Value
HTTP method PUT
Resource pattern http://localhost:8080/deepphe/summarizePatientDoc/patient/<patientId>/doc/<docId>
HTTP Headers Content-Type: text/plain
Authorization: Bearer <token>
HTTP request body Text content of document
Response JSON object of simple message

You can also queue up the process by using the following call:

REST API Value
HTTP method PUT
Resource pattern http://localhost:8080/deepphe/queuePatientDoc/patient/<patientId>/doc/<docId>
HTTP headers Content-Type: text/plain
Authorization: Bearer <token>
HTTP request body Text content of document
Response JSON object of simple message

For this call, you will just get back a simple JSON message since the text processing is queued up, for example:

{'name': 'Document Queued', 'value': 'Added patientX patientX_doc1_RAD.txt to the Text Processing Queue.'}

Note: The document information cache is automatically cleaned every 15 minutes, removing any document information that has not been accessed within the last 60 minutes.

Summarize a patient

A patient summary can only be created using document information that was cached. This call doesn't require a request body.

REST API Value
HTTP method GET
Resource pattern http://localhost:8080/deepphe/summarizePatient/patient/<patientId>
HTTP headers Authorization: Bearer <token>
HTTP request body Text content of document
Response JSON object of simple message

Manage the contaners

Shell into the running container (optional)

Sometimes you may want to shell into a running container to check more details, this can be done by:

docker exec -it <container-id> bash

Stop the running services

docker-compose stop

The above command stops all the running containers of this project without removing them. It preserves containers, volumes, and networks, along with every modification made to them. The stopped containers can be started again with docker-compose start.

Instead of stopping all the containers, you can also stop a particular service:

docker-compose stop <service-name>

Reset the status of our project

docker-compose down

This command stops both containers of this project and removes them as well the dphe-stream-network. All cached document information will be lost.

Note: At this time DeepPhe Stream could be run with a single container. The multi-container stack exists to facilitate addition future workflows that may require additional containers.

Integration tests (optional)

Once the containers are up running, we can execute some integration tests written in Python to verify the pipeline output by submitting some sample reports to the REST API. The tests will be executed against the dphe-stream-nginx container, which proxies the requests to the backend REST API service.

The test cases and configuration are located at dphe-stream-dock/dphe-stream-nginx/integration-test. If a different auth token is specified during the image creation phase, that same auth token should be specified int he test.cfg as well.

Run the tests manually within the container

docker exec -it dphe-stream-nginx bash
cd integration-test/
python3 test.py

Add more tests and run against the container

We can also add more test cases within the dphe-stream-nginx/integration-test directory to improve the coverage and run the tests against the running contianers. To do so, we can create a Python virtual environment and install the dependencies:

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Once the test changes are made, we can run it:

python3 test.py

Trigger the tests via docker healthcheck

In the docker-compose.yml file, uncomment the healthcheck section with configuration changes if you prefer the tests to be triggered automatically against the running container on a periodic basis.

# Uncommnet the healthcheck section with desired configuration settings to determine if the state of the container is healthy
# This healthcheck triggers the python tests based on the options: interval, timeout and start_period
# healthcheck:
#   test: ["CMD", "python3", "/usr/src/app/integration-test/test.py"]
#   interval: 5m30s
#   timeout: 30s
#   retries: 3
#   start_period: 30s

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