This repository contains code samples and how-to for Control-M Automation API.
- Download Workbench for Docker - the latest development Control-M environment.
- Download Automation API CLI (ctm-cli.tgz).
- Installation instructions.
You can find the latest Control-M Automation API documentation, including a programming guide, on the project web page.
To contribute, please follow these guidelines.
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Every sample and its associated files must be contained in its own folder. Name this folder something that describes what your sample does. Usually this naming pattern looks like level-sample-purpose (e.g. 201-automate-corrective-flow). Numbering should start at 101. 100 is reserved for things that need to be at the top.
For consistent categorization, please comply to the following folder structure:
- 1-general-examples
- 2-cicd-tooling-integration
- 3-infrastructure-as-code-examples
- 4-ai-job-type-examples
- 5-bots-and-dashboard-examples
- 6-ide-integrations
- 7-api-gateway-integrations
- 8-jobs-as-code
- 9-aws-integrations
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For consistent ordering create all folders in lowercase.
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Include a README.md file that explains the sample. A good description helps other community members to understand your sample. The README.md uses Github Flavored Markdown for formatting text. If you want to add images to your README.md file, store the images in the images folder. Reference the images in the README.md with a relative path (e.g.
). This ensures the link will reference the target repository if the source repository is forked.
Please use issues on GitHub for questions or feedback about the examples included in this repository.