Deploying

The Brazil Data Cube STAC implementation depends essentially on Flask, SQLAlchemy, JSONSchema and the Brazil Data Cube Database Module.

There is a Dockerfile for quick deployment. This section explains how to get the STAC service up and running with Docker. If you do not have Docker installed, take a look at this tutorial on how to install it in your system.

Requirements

Besides Docker, you will need an instance of a PostgreSQL DBMS with a database prepared with the schema for Image and Data Cube collections from the Brazil Data Cube Database Module.

Building the Docker Image

On the command line use the docker build command to create the docker image for the service:

$ docker build --no-cache -t bdc-stac:0.8.0-0 .

The above command will create a Docker image named bdc-stac and tag 0.8.0-0, as one can see with the docker images command:

$ docker images

REPOSITORY                                          TAG                 IMAGE ID            CREATED             SIZE
bdc-stac                                            0.8.0-0             44651ac917e4        16 hours ago        333MB

Preparing the Network for Containers

If you have the PostgreSQL server running in a Docker container and you want to have it accesible to the STAC service, you can create a Docker network and attach your PostgreSQL container to it 1.

To create a new network, you ca use the docker network command: .. code-block:: shell

$ docker network create bdc_net

The above command will create a network named bdc_net. Now, it is possible to attach your database container in this network:

$ docker network connect bdc_net bdc_pg

In the above command, we are supposing that your database container is named bdc_pg.

Launching the Docker Container with the STAC Service

The docker run command can be used to launch a container from the image bdc-stac:0.8.0-0. The command below shows an example on how to accomplish the launch of a container:

$ docker run --detach \
             --name bdc-stac \
             --publish 127.0.0.1:8080:5000 \
             --network=bdc_net \
             --env DB_HOST="bdc_pg:5432" \
             --env DB_USER="postgres" \
             --env DB_PASS="secret" \
             --env DB_NAME="bdcdb" \
             --env BASE_URI="http://localhost:8080" \
             --env API_VERSION="0.8.0" \
             --env FILE_ROOT="http://localhost:8081" \
             bdc-stac:0.8.0-0

Let’s take a look at each parameter in the above command:/

• --detach: tells Docker that the container will run in background (daemon).

• --name bdc-stac: names the container.

• --publish 127.0.0.1:8080:5000: by default the STAC service will be running on port 5000 of the container. You can bind a host port, such as 8080 to the container port 5000.

• --network=bdc_net: if the container should connect to the database server through a docker network, this parameter will automatically attach the container to the bdc_net. You can ommit this parameter if the database server address can be resolved directly from a host address.

• --env DB_HOST="bdc_pg:5432": set the database host address that will be used by the STAC service. In this example, the name bdc_pg is the name of a PostgreSQL container in the same network as the STAC service.

• --env DB_USER="postgres": the user name for connecting to the database server.

• --env DB_PASS="secret": the user password for connecting to the database server.

• --env DB_NAME="bdcdb": the name of the database containing the image and data cube collections 2.

• --env BASE_URI="http://localhost:8080": Base URI of the service.

• --env API_VERSION="0.8.0": STAC Version used in the service.

• --env FILE_ROOT="http://localhost:8081": File root for the Assets.

• bdc-stac:0.8.0-0: the name of the base Docker image used to create the container.

If you have launched the container, you can check if the service has initialized:

$ docker logs bdc-stac

* Environment: production
   WARNING: This is a development server. Do not use it in a production deployment.
   Use a production WSGI server instead.
 * Debug mode: off
 * Running on http://0.0.0.0:5000/ (Press CTRL+C to quit)

Finally, to test if it is listening, use the curl command:

$ curl localhost:8080

[{"href":"http://localhost:5000/","rel":"self"},{"href":"http://localhost:5000/docs","rel":"service"},{"href":"http://localhost:5000/conformance","rel":"conformance"},{"href":"http://localhost:5000/collections","rel":"data"},{"href":"http://localhost:5000/stac","rel":"data"},{"href":"http://localhost:5000/stac/search","rel":"search"}]

Footnotes

1

If you have a valid address for the PostgreSQL DBMS you can skip this section.

2

Make sure you have a database prepared with the schema for Image and Data Cube collections from the Brazil Data Cube Database Module