Traditionally, logging was most commonly associated with the post-deployment part of the software development lifecycle, or SDLC. Logs typically served first and foremost to help IT engineers find and troubleshoot problems that arose in production. Today, however, logging can help teams optimize much more than just production-environment application management. And indeed, logging needs to be leveraged across all stages of the SDLC in order to ensure the reliable, continuous delivery of software. Developers, testing teams, and anyone else involved in software delivery must make use of logs and log analysis as one way to ensure the smooth flow of code across the entire SDLC. With that reality in mind, we’ve prepared this guide to showcase practical approaches to log analytics at different stages of the SDLC.
In our series of eBooks, you’ll find an explanation of why logging across the SDLC is essential in modern software delivery chains, as well as real-world examples of how teams can use LogDNA to streamline three distinct stages in the SDLC: Development, QA and staging, and production troubleshooting. This eBook is focused on logging during QA and Staging.