Source: devops.com
AI Everywhere Requires MLOps and NetDevOps to IntersectCategory: Data, automation, artificial-intelligence
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As xOps workflows become more prevalent in IT, it’s inevitable to see overlap and intersection between them.
The goal is to reduce errors in production configuration deployment, reduce time to production and create a collaborative workflow across cross-functional teams and network team members.
NetDevOps evolved out of DevOps, applying lessons learned from software development workflows and applying them to network development.
ML engineers tend to use existing datasets for this exact reason, but the problem is, few of these datasets exist today in the networking realm.
As xOps workflows become more prevalent in IT, it’s inevitable to see overlap and intersection between them.
The goal is to reduce errors in production configuration deployment, reduce time to production and create a collaborative workflow across cross-functional teams and network team members.
NetDevOps evolved out of DevOps, applying lessons learned from software development workflows and applying them to network development.
ML engineers tend to use existing datasets for this exact reason, but the problem is, few of these datasets exist today in the networking realm.
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