Security scans generate hundreds of findings. Security teams manually triage each one while developers wait for approval to deploy. Most findings are false positives or low-risk issues, but identifying the real threats requires expertise and time. AI can prioritize findings by actual exploitability and auto-remediate common vulnerabilities, allowing security teams to focus on the threats that matter.
10 AI prompts to speed your team’s software delivery…Rutvik Shah Michael Friedrich AI tutorial DevSecOps DevSecOps platform features Generative AI marks a monumental shift in the software development industry, making it easier to develop, secure, and operate software. Our new…
…Diagnosing incidents : We can figure out which services are performing outside their normal bounds quickly and reduce the average time it takes to detect an incident (MTTD) , bringing about a faster resolution…
…After that came incident root-cause, architecture drift, flaky-pipeline diagnosis, and tracing a CVE across repositories. None of that is random. Engineers ask these questions constantly and answer them poorly because…
…Prevent operations and security issues in Git history by detecting them before they occur (e.g. performance, crashes, security vulnerabilities). Think of the most boring - or most hated - coding task, and add…
…Rapid deployment cycles mean we can respond to customer feedback within hours, ship security patches immediately, and validate new features in production before scaling them. For our customers: Every deployment to GitLab…
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