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Production Monitoring
Learn how to monitor deployed projects and API services in production.
Curriculum75 min
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Production Monitoring Foundations
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Concept | Unified Monitoring
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Concept | Process governance for MLOps
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Concept | Model comparisons
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Concept | Model evaluation stores
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Concept | Monitoring model performance and drift in production
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Model Monitoring with a Model Evaluation Store
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Create two model monitoring pipelines
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Compare and contrast model monitoring pipelines
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Run more model evaluations
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Automate model monitoring
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Create additional model monitoring assets
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Model Monitoring Feedback Loops
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Concept | Monitoring and feedback in the AI project lifecycle
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Tutorial | API endpoint monitoring
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Optional: Production Deployment Automation
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Start with a retrain model scenario
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Add a Create bundle or API service version step
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Add an Update project or API deployment step
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Run the scenario & observe the outcome
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Plan for a more robust setup
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Optional: Model Monitoring in Different Contexts
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A batch workflow within Dataiku
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An API endpoint on a Dataiku API node
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An exported Python model scored externally
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An exported Java model scored externally
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Wrap Up
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Course checkpoint | Production Monitoring
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Tell us what you think | Production Monitoring
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Course complete | Production Monitoring
Curriculum75 min
-
Production Monitoring Foundations
-
Concept | Unified Monitoring
-
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
-
-
Create two model monitoring pipelines
-
Compare and contrast model monitoring pipelines
-
Run more model evaluations
-
-
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
-
-
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
-
-
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
-
-
Wrap Up
-
Course checkpoint | Production Monitoring
-
Tell us what you think | Production Monitoring
-
Course complete | Production Monitoring