Production-ready Workflows

In the previous chapters, we’ve explored strategies for supporting data operability across programming language. Now, we turn our attention to how to effectively integrate these tools and languages into a cohesive and scalable analysis workflow.

Productionization of Single-Cell Analysis Workflows

Productionization is the process of transforming research-oriented analysis pipelines into robust, scalable, and maintainable workflows that can be reliably executed in a production environment (Figure 1). This transition is essential for ensuring the reproducibility of results, facilitating collaboration among researchers, and enabling the efficient processing of large and complex single-cell datasets.

Figure 1: An example of the productionization process for single-cell analysis workflows. A) The research environment is characterized by scattered data, manual steps, and ad-hoc analysis pipelines. B) The production environment is streamlined, automated, and standardized, with reproducibility engines in place.

But how to ensure that your workflow is production-ready?

In this chapter, we will explore:

• Key qualities of workflows built to stand the test of time
• Which technologies and workflow frameworks contribute to these qualities
• Best practices to keep in mind during development