One of the main limitations of the Python script developed by TESAF department was that it had to be manually executed in a custom computer. As a carbon emission measurement and analysis tool, an interesting feature we think about was to make it compatible with any cloud computing server so it could be executed on a cloud environment.
Information processed by Python script tool comes from some data logger devices connected to heavy duty machinery. As heavy duty vehicles are continuously sending this information to Amazon S3 repository, a feature that automatically executes the script and gets the data logger information every few minutes was an interesting feature to include into existing development.
In this task the TESAF tool was updated to make it compatible with Docker technology. Using Docker, you can quickly deploy and scale applications into a cloud environment and know your code will run.
Docker was combined with Cron, command-line utility job scheduler in Unix operative systems. On this way, the dockerized Python application could be set-up to run every few minutes on a cloud environment and avoid explained user computer lock-in. As part of transfer of knowledge task, a step by step documentation was delivered.