The adoption of machine learning is being used more & more to improve DevOps practices. Examples include: troubleshooting and triage analytics; preventing production failures; ensuring application delivery; managing production and alert storms.
Discover best practices when implementing ML tools to DevOps, including the preparation & monitoring phases, to ultimately deliver more value to your business through better automation, more efficient problem solving, reduced operational complexity, and increased collaboration.
A unique opportunity to interact with industry leaders, developers, data scientists, DevOps specialists & IT decision makers leading the ML revolution. Learn from & connect with 200+ industry innovators sharing best practices to implement machine learning into DevOps.