Production Monitoring

Learn how to monitor deployed projects and API services in production.

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About this course

Curriculum75 min

  • Production Monitoring Foundations
  • Concept | Process governance for MLOps
  • Concept | Model comparisons
  • Concept | Model evaluation stores
  • Concept | Monitoring model performance and drift in production
  • Model Monitoring with a Model Evaluation Store
  • Get started
  • Create two model monitoring pipelines
  • Compare and contrast model monitoring pipelines
  • Run more model evaluations
  • Conduct drift analysis
  • Automate model monitoring
  • Create additional model monitoring assets
  • Model Monitoring Feedback Loops
  • Concept | Monitoring and feedback in the AI project lifecycle
  • Tutorial | API endpoint monitoring
  • Optional: Production Deployment Automation
  • Get started
  • Start with a retrain model scenario
  • Add a Create bundle or API service version step
  • Add an Update project or API deployment step
  • Run the scenario & observe the outcome
  • Plan for a more robust setup
  • Optional: Model Monitoring in Different Contexts
  • Get started
  • A batch workflow within Dataiku
  • An API endpoint on a Dataiku API node
  • An exported Python model scored externally
  • An exported Java model scored externally
  • What's next?
  • Wrap Up
  • Course checkpoint | Production Monitoring
  • Tell us what you think | Production Monitoring
  • Course complete | Production Monitoring

About this course

Curriculum75 min

  • Production Monitoring Foundations
  • Concept | Process governance for MLOps
  • Concept | Model comparisons
  • Concept | Model evaluation stores
  • Concept | Monitoring model performance and drift in production
  • Model Monitoring with a Model Evaluation Store
  • Get started
  • Create two model monitoring pipelines
  • Compare and contrast model monitoring pipelines
  • Run more model evaluations
  • Conduct drift analysis
  • Automate model monitoring
  • Create additional model monitoring assets
  • Model Monitoring Feedback Loops
  • Concept | Monitoring and feedback in the AI project lifecycle
  • Tutorial | API endpoint monitoring
  • Optional: Production Deployment Automation
  • Get started
  • Start with a retrain model scenario
  • Add a Create bundle or API service version step
  • Add an Update project or API deployment step
  • Run the scenario & observe the outcome
  • Plan for a more robust setup
  • Optional: Model Monitoring in Different Contexts
  • Get started
  • A batch workflow within Dataiku
  • An API endpoint on a Dataiku API node
  • An exported Python model scored externally
  • An exported Java model scored externally
  • What's next?
  • Wrap Up
  • Course checkpoint | Production Monitoring
  • Tell us what you think | Production Monitoring
  • Course complete | Production Monitoring