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```{toctree} | ||
:maxdepth: 1 | ||
./start_small | ||
./own_docker | ||
./debugging | ||
``` | ||
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source/content/embrace_automation/considerations/start_small.md
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### Start Small! | ||
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{% if page %} | ||
CI/CD functionalities in **GitLab** and **GitHub** are excellent tools for speeding up, standardizing, and streamlining a variety of tasks. | ||
However, adding complexity through pipelines or workflows can quickly increase the intricacy of your scripts. | ||
Before you know it, you may find yourself navigating a maze of dependencies, conditions, and edge cases that can consume a significant amount of time to resolve and manage. | ||
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Therefore, before implementing any automation procedures, evaluate your workflow design and ensure it is as simple and straightforward as possible. | ||
The fewer dependencies, the better! | ||
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Another important consideration is to avoid having multiple "sources of truth." | ||
This concept may seem unusual at first, but adhering to the principle that any parameterization (such as the version of a dependency) should be defined in only one location—especially when used across multiple stages in a workflow or pipeline—can greatly simplify management. | ||
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Finally, even when starting small, it's essential to evaluate the structure of your project or repository before embarking on your automation journey. | ||
The various features and configurations offered by remote services are designed to work well with standard project structures for languages like Python, R, Scala, etc. | ||
Following typical project setups is likely to facilitate the use of automation functionalities, while maintaining custom folder structures and dependency patterns may lead to complications. | ||
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{% else %} | ||
**Complex pipelines and workflows** can quickly increase the intricacy of your automation scripts. | ||
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- **Starting with simple, toy-like pipelines** allows you to experiment and learn without overwhelming complexity. | ||
- **Simplicity in workflow design** is crucial; ensure it is as straightforward as possible. | ||
- **Fewer dependencies** lead to easier management and maintenance. | ||
- **Avoiding multiple sources of truth** helps simplify management. | ||
- **Parameterization** (like dependency versions) should be defined in only one location, especially when used across multiple stages in a workflow or pipeline. | ||
- **Evaluating project structure** before automation is essential. | ||
- **Standard project setups** for languages like Python, R, and Scala facilitate the use of automation functionalities, while custom structures may lead to complications. | ||
{% endif %} | ||
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