Docker Extension Quick Start

This tutorial guides you through the process of creating a simple Docker Application in PHP. As in the Custom Science Quick Start, the application logic is trivial: it takes a table with numbers as an input and creates another table with an extra column containing those numbers multiplied by two. A test in KBC is included.

Before You Start

  • Have a KBC project where you can test your code.
  • Get yourself acquainted with Docker. You must be able to run docker commands.
  • You should be able to send API requests. Although you can use the Apiary client console, we recommend using Postman as it is more convenient. A list of sample requests is available.

Step 1 – Preliminaries

Create a public git repository (Github or Bitbucket is recommended, although any other host should work as well).

Step 2 – Write Application Code

In the root of your repository, create a PHP script named main.php with the following contents:


$fhIn = fopen('/data/in/tables/source.csv', 'r');
$fhOut = fopen('/data/out/tables/destination.csv', 'w');

$header = fgetcsv($fhIn);
$numberIndex = array_search('number', $header);
fputcsv($fhOut, array_merge($header, ['double_number']));

while ($row = fgetcsv($fhIn)) {
    $row[] = $row[$numberIndex] * 2;
    fputcsv($fhOut, $row);

echo "All done";

As mentioned above, this script reads a CSV file, takes a column named number, multiplies its values by 2 and adds the new values as a new column. We take care to properly find the column index ($numberIndex), as the order of columns is unknown. Finally, the result is written to another CSV file. Note that we open both the input and output files simultaneously; as soon as a row is processed, it is immediately written to destination.csv. This approach keeps only a single row of data in the memory and is generally very efficient. It is recommended to implement the processing in this way because data files coming from KBC can by quite large (i.e., dozens of Gigabytes).

You can test the code with our sample table:

number someText double_number
10 ab 20
20 cd 40
25 ed 50
26 fg 52
30 ij 60

Step 3 – Wrap Application in Docker Image

You need to create a Docker Image containing your application.

Step 3.1 – Wrap Application in Image

Create a file named Dockerfile in the root of the repository:

FROM php:7
COPY . /code/
ENTRYPOINT php /code/main.php

The image inherits from the official PHP Image. The instruction COPY . /code/ copies the application code (only the main.php file in this simple application) from the build context (the same folder in which the Dockerfile resides) into the image. The ENTRYPOINT line specifies that when the image is run, the PHP application script is executed.

Step 3.2 – Build the Image

On the command line, navigate to the folder with your repository and run the following command (including the dot at the end):

docker build --tag=test .

It should produce output similar to the one below:

Sending build context to Docker daemon  3.072kB
Step 1/3 : FROM php:7
7: Pulling from library/php
85b1f47fba49: Already exists
66e22dddbf92: Pull complete
bf0df491fd2e: Pull complete
0cbe7899c5b5: Pull complete
515aeb1bd86c: Pull complete
842bd485599e: Pull complete
84f329bf46d9: Pull complete
Digest: sha256:9d847a120385a1181ffa8ba4d17f28968fb2285923a0ca690b169ee512c55cb1
Status: Downloaded newer image for php:7
---> c342f917459a
Step 2/3 : COPY . /code/
---> 0eecd670cb5f
Step 3/3 : ENTRYPOINT php /code/main.php
---> Running in 14c34dbe7b61
---> c9c00d6a99fd
Removing intermediate container 14c34dbe7b61
Successfully built c9c00d6a99fd
Successfully tagged test:latest

Out of that output, the most important thing is the Successfully built c9c00d6a99fd. It means that everything went ok, and we can use the tag of the image: test.

Step 4 – Obtaining Sample Data and Configuration

Data between KBC and your Docker image are exchanged using CSV files in designated directories; they will be injected into the image when we run it. To simulate this, download an archive containing the data files and configuration in the exact same format you get in the production environment.

To obtain the configuration, send a Sandbox API Request. You will receive an archive containing a /data/ folder with tables and files from the input mapping, and a configuration depending on the request body. A sample request to

    "config": "my-test-config",
    "configData": {
        "storage": {
            "input": {
                "tables": [
                        "source": "in.c-main.test",
                        "destination": "source.csv"
            "output": {
                "tables": [
                        "source": "destination.csv",
                        "destination": "out.c-main.test"
        "parameters": {

The sample request corresponds to the following setting in the UI (though the UI for your component will become available only after your extension has been completed and registered).

Configuration Screenshot

Alternatively – to quickly get the picture, download a random sample data folder, which can be used together with the above sample application.

Step 5 – Running Application with Sample Data

Once you have prepared the data folder with sample data and configuration, inject it into the Docker Image. In addition to the options shown in the example, there are many other options available.

When you run an image, a container is created in which the application is running isolated. Use the following command to run the image:

docker run --volume=physicalhostpath:/data/ imageTag

An Image tag can be either the tag you supplied in the --tag parameter for docker build (test in the above example) or the image hash you received when the image was built (c9c in the above example). The physical host path depends on the system you are running. If in doubt, see Setting up Docker. In our example image with default Windows installation of Docker, this would be:

docker run --volume=C:\Users\JohnDoe\data\:/data/ test

Where the contents of the sample data folder are put in the user’s home directory. If you have set everything correctly, you should see All done; and a destination.csv file will appear in the data/out/tables/ folder.

Step 5.1 – Debugging

Chances are that you received an ugly error message or warning. In that case, you might want to check the contents of the image; specifically, if all the files are where you expect them to be.

To work with the application container interactively, use the following command:

docker run --volume=physicalhostpath:/data/ -i -t --entrypoint=/bin/bash imageTag

For instance:

docker run --volume=C:\Users\JohnDoe\data\:/data/ -i -t --entrypoint=/bin/bash test

You can then inspect the container contents: ‘ls /data/’. For more details, see Howto.

Step 6 – Deployment

The easiest way to distribute the application image is by setting up an automated build on either (Dockerhub or Quay registry). However for deployment into KBC, we recommend that you use the repository provided by Developer Portal.

To deploy the application to production, it must first be registered. Once the application is registered with us, we will automatically pull the image and make it available in production.