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 Duration 14 hours

Course Outline

Foundations of MLOps on Kubernetes

  • Essential concepts in MLOps
  • Distinguishing MLOps from traditional DevOps
  • Addressing key challenges in ML lifecycle management

Containerizing ML Workloads

  • Packaging models and associated training code
  • Optimizing container images specifically for ML
  • Handling dependencies to ensure reproducibility

CI/CD for Machine Learning

  • Organizing ML repositories to facilitate automation
  • Embedding testing and validation steps into the workflow
  • Configuring pipeline triggers for retraining and model updates

GitOps for Model Deployment

  • Core GitOps principles and workflow patterns
  • Leveraging Argo CD for seamless model deployment
  • Maintaining version control for models and configurations

Pipeline Orchestration on Kubernetes

  • Constructing pipelines using Tekton
  • Overseeing complex, multi-step ML workflows
  • Optimizing scheduling and resource allocation

Monitoring, Logging, and Rollback Strategies

  • Monitoring data drift and assessing model performance
  • Integrating comprehensive alerting and observability tools
  • Implementing effective rollback and failover techniques

Automated Retraining and Continuous Improvement

  • Creating efficient feedback loops
  • Scheduling and automating retraining cycles
  • Utilizing MLflow for tracking experiments and managing runs

Advanced MLOps Architectures

  • Implementing multi-cluster and hybrid-cloud deployment models
  • Enabling team scaling through shared infrastructure
  • Addressing security and compliance requirements

Summary and Next Steps

Requirements

  • A solid grasp of Kubernetes fundamentals
  • Practical experience with machine learning workflows
  • Familiarity with Git-based development practices

Audience

  • ML engineers
  • DevOps engineers
  • ML platform teams

Number of participants


Price per participant

Open Training Courses require 5+ participants.

Testimonials (3)

About the microservices and how to maintenance kubernetes

Yufri Isnaini Rochmat Maulana - Bank Indonesia
Course - Advanced Platform Engineering: Scaling with Microservices and Kubernetes

How trainer deliver knowledge so effectively

Vu Thoai Le - Reply Polska sp. z o. o.
Course - Certified Kubernetes Administrator (CKA) - exam preparation

The knowledge and the patience from the trainer to answer to our questions.

Calin Avram - REGNOLOGY ROMANIA S.R.L.
Course - Deploying Kubernetes Applications with Helm

Upcoming Courses

MLOps on Kubernetes: CI/CD Pipelines for Machine Learning

2026-11-09 09:30
14 hours
Thessaloniki
608 EUR (Online)
608 EUR (Classroom)

MLOps on Kubernetes: CI/CD Pipelines for Machine Learning

2026-11-23 09:30
14 hours
Nicosia
608 EUR (Online)
608 EUR (Classroom)

MLOps on Kubernetes: CI/CD Pipelines for Machine Learning

2026-12-07 09:30
14 hours
Nicosia
608 EUR (Online)
1008 EUR (Classroom)

MLOps on Kubernetes: CI/CD Pipelines for Machine Learning

2026-12-21 09:30
14 hours
Athens
608 EUR (Online)
1008 EUR (Classroom)

MLOps on Kubernetes: CI/CD Pipelines for Machine Learning

2027-01-04 09:30
14 hours
Kaminia
608 EUR (Online)
1008 EUR (Classroom)

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