How CI/CD is different for data science
Agile programming is the most-used methodology that enables development teams to release their software into production, frequently to gather feedback and refine the underlying requirements. For agile to work in practice, however, processes are needed that allow the revised application to be built and released into production automatically—generally known as continuous integration/continuous deployment, or CI/CD. CI/CD enables software teams to build complex applications without running the risk of missing the initial requirements by regularly involving the actual users and iteratively incorporating their feedback.To read this article in full, please click here
Agile programming is the most-used methodology that enables development teams to release their software into production, frequently to gather feedback and refine the underlying requirements. For agile to work in practice, however, processes are needed that allow the revised application to be built and released into production automatically—generally known as continuous integration/continuous deployment, or CI/CD. CI/CD enables software teams to build complex applications without running the risk of missing the initial requirements by regularly involving the actual users and iteratively incorporating their feedback.