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Using Machine Learning to Make DevSecOps a Reality

edited Oct 31, 2018 12:51PM in Observability & Management 1 comment

Summary

Oracle OpenWorld 2018 | Developer Session DEV5059

Content

Moving toward continuous (or short-cycle) delivery? Constantly rewiring your apps with microservice and similar architectures? How are you planning to maintain visibility, maximize service levels, and counter threats and prevent data loss once this stuff gets into production? Coding instrumentation into your apps is time-consuming and error-prone. Instead, let machine learning do the work of adapting your monitoring and security regime to your fast-moving application environments. This session discusses different types of machine learning that are optimized for operational and security data and how they are leveraged to ensure that SecOps moves as fast as the rest of your DevOps

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