DevOps

As cloud environments get more complex, app security needs an AI-powered upgrade

May 26, 2021
Huma Abidi of Intel speaks at the Artificial Intelligence Conference in San Francisco three years ago. Today’s columnist, Dave Anderson of Dynatrace, says AI-powered risk and impact analysis and remediation can deliver the visibility developers need to more effectively manage vulnerabilities. O'ReillyConferences CreativeCommons CC BY-NC 2.0
  • Increased responsibility on developers to ensure their code remains vulnerability-free.
  • Manual processes that produce vulnerability assessments, which are imprecise in their risk and impact analysis.
  • Too much time spent chasing down false positives.
  • Little to no time available to manually assess risks because of a lack of automatic and continuous vulnerability scans. Consequently, even the most common vulnerabilities can end up slipping past their notice.
  • Real-time, continuous runtime application self-protection features for cloud-native applications in preproduction and production environments.
  • Real-time topology mapping and distributed tracing with code-level analysis that can help precisely identify vulnerabilities in preproduction and production environments, and ensure DevSecOps teams understand each vulnerability’s true impact on the business.
  • Automatic, continuous discovery and instrumentation that provides complete vulnerability coverage, so that DevSecOps never misses a code change or new deployment.
  • AI-powered risk and impact analysis and remediation, for continuous visibility into identifying changes, prioritizing alerts, and generating precise answers about the root cause, nature, and severity of any given vulnerability – ensuring that software developers can quickly and effectively remediate each vulnerability.
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