5 verified briefings on GitLab. Each story includes a plain-English summary, why it matters, and the concrete action engineering teams should take.
Large language models can find security flaws in code that traditional pattern-based scanners miss. GitLab's analysis shows the best approach is using both, with LLMs for nuanced checks and SAST for broad, fast coverage.
GitLab's Secrets Manager now works with Terraform and Kubernetes via the External Secrets Operator. This lets teams stop managing separate secret stores, simplifying workflows and boosting security by having one central place for all credentials.
A new GitLab report finds AI code tools are turning developers into validators, not just writers. This shift creates new risks, as teams struggle to control the quality and security of code they didn't write.
GitLab has released version 19.0, a major update focused on strengthening its DevSecOps platform. The release aims to provide a more coordinated and comprehensive toolset for software development, security, and operations, with key enhancements to secrets management.
GitLab explains how AI coding agents like Codex can accelerate bug fixing. These tools operate within the terminal to read code, suggest solutions, and run commands. While AI speeds up the initial coding, the full development lifecycle—including reviews and CI/CD pipelines—still requires human oversight.