36 Quickstart for Docker and PEcAn.

This is a short documentation on how to start with Docker and PEcAn. This will not go into much detail about about how to use docker.

36.1 Install Docker

You will need to install docker first. See https://www.docker.com/community-edition#/download

36.2 Running PEcAn

We will use a yaml file to describe the containers that we make up, This yaml file is called docker-compose.yml. Before you get started you will need to download this file first. Place this file somewhere on your machine and cd to the folder that contains this file.

Next we will start the docker containers to start Docker. Since both BETY and PEcAn depend on a populated database we will first start the database and populate it with some data. This only needs to be done once, if this is done already, you can skip this step and go to the next step

If this is finished (or you had done this in the past), we can start the full stack:

This will start all the containers marked green in the architecture diagram. Once this is done you have a working instance of PEcAn. Following is a list of URL’s you can visit

URL Service
http://localhost:8000/pecan/ PEcAn web GUI
http://localhost:8000/bety/ BETY web application
http://localhost:8000/minio/ File browser (username carya, password illinois)
http://localhost:8000/ RabbitMQ (username guest, password guest)
http://localhost:8001/ Træfik, webserver shows mapping from url to container

36.3 Testing PEcAn

To test PEcAn you can use the following curl statement, or use the webpage to submit a request:

This should return some text with in there Location: this is shows the workflow id, you can prepend http://localhost:8000/pecan/ to the front of this, for example: http://localhost:8000/pecan/05-running.php?workflowid=99000000001. Here you will be able to see the progress of the workflow.

To see what is happening behind the scenes you can use look at the log file of the specific docker containers, once of interest are pecan_executor_1 this is the container that will execute a single workflow and pecan_sipnet_1 which executes the sipnet mode. To see the logs you use docker logs pecan_executor_1 Following is an example output:

2018-06-13 15:50:37,903 [MainThread     ] INFO    : pika.adapters.base_connection - Connecting to
2018-06-13 15:50:37,924 [MainThread     ] INFO    : pika.adapters.blocking_connection - Created channel=1
2018-06-13 15:50:37,941 [MainThread     ] INFO    : root -  [*] Waiting for messages. To exit press CTRL+C
2018-06-13 19:44:49,523 [MainThread     ] INFO    : root - b'{"folder": "/data/workflows/PEcAn_99000000001", "workflowid": "99000000001"}'
2018-06-13 19:44:49,524 [MainThread     ] INFO    : root - Starting job in /data/workflows/PEcAn_99000000001.
2018-06-13 19:45:15,555 [MainThread     ] INFO    : root - Finished running job.

This shows that the executor connects to RabbitMQ, waits for messages. Once it picks up a message it will print the message, and execute the workflow in the folder passed in with the message. Once the workflow (including any model executions) is finished it will print Finished. The log file for pecan_sipnet_1 is very similar, in this case it runs the job.sh in the run folder.

To run multiple executors in parallel you can duplicate the executor section in the docker-compose file and just rename it from executor to executor1 and executor2 for example. The same can be done for the models. To make this easier it helps to deploy the containers using kubernetes allowing to easily scale up and down the containers.