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An MLOps implementation to build and deploy an ML-model assessing the efficiency of a manufacturing machine using jenkins (CI), argoCD (CD), gitOps with webHooks for automatic push of code and GCP virtual machine (VM) as remote server.

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WeOnlyLiveOnce13/MLOps-machine-efficiency

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Manufacturing machine efficiency 📈 MLOPs

A machine learning operation implementation to predict and deploy an ML-model assessing the efficiency of a manufacturing machine.

Use cases:

  • Predicting the efficiency of a manufacturing machine.
  • Cost management
  • Predictive maintenance

Technologies:

  • github as a version control system
  • jenkins as a CI tool
  • argoCD as a CD tool
  • docker for containerization
  • kubernetes for orchestration
  • Google Cloud as a cloud provider with VM and GKE
  • github Webhooks for triggering CI/CD pipelines

Snapshots

Docker in GCP VM: Docker in GCP

argoCD in GCP VM: argoCD

Successful build and CI with Jenkins: Successful build and CI with Jenkins

successful deployment with argoCD: Successful deployment with argoCD

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An MLOps implementation to build and deploy an ML-model assessing the efficiency of a manufacturing machine using jenkins (CI), argoCD (CD), gitOps with webHooks for automatic push of code and GCP virtual machine (VM) as remote server.

Topics

jenkins webhooks mlflow argocd gcp-automation-gitops gcp-vm

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