Building Microservices with Spring Cloud and Docker Training Course

This instructor-led, live training in South Korea (online or onsite) is designed for engineers looking to advance their Docker knowledge to deploy applications at a larger scale while maintaining control.

By the end of this training, participants will be able to:

• Build their own Docker images.
• Deploy and manage a large number of Docker applications.
• Evaluate different container orchestration solutions and choose the most suitable one.
• Set up a continuous integration process for Docker applications.
• Integrate Docker applications with existing continuous tools integration processes.
• Secure their Docker applications.

Docker serves as a containerization platform that facilitates consistent, portable, and reproducible environments for AI and machine learning workloads.

This instructor-led, live training (available online or onsite) is designed for intermediate-level professionals looking to package ML codebases, dependencies, and models using Docker to ensure reliable workflows from development to production.

Upon completion of this course, participants will be able to:

• Create and manage Docker images specifically tailored for AI and ML applications.
• Containerize machine learning pipelines, tools, and dependencies.
• Optimize Docker environments for both performance and portability.
• Deploy containerized ML services across various runtime environments.

Course Format

• Concept demonstrations accompanied by guided discussions.
• Hands-on exercises centered on real-world containerization tasks.
• Practical implementation using live-lab Docker environments.

Course Customization Options

• To tailor this training to your organizational needs, please contact us to arrange a session.

CI/CD for AI is a structured approach to automating model packaging, testing, containerization, and deployment using continuous integration and continuous delivery pipelines.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to automate end-to-end AI model delivery workflows using Docker and CI/CD platforms.

As the training concludes, participants will be able to:

• Create automated pipelines for building and testing AI model containers.
• Implement version control and reproducibility for model lifecycles.
• Integrate automated deployment strategies for AI services.
• Apply CI/CD best practices tailored to machine learning operations.

Format of the Course

• Instructor-guided presentations and technical discussions.
• Practical labs and hands-on implementation exercises.
• Realistic CI/CD workflow simulations in a controlled environment.

Course Customization Options

• If your organization requires customized pipeline workflows or platform integrations, please contact us to tailor this course.

The Certified Kubernetes Administrator (CKA) program was developed by The Linux Foundation and the Cloud Native Computing Foundation (CNCF).

Kubernetes has emerged as the leading platform for container orchestration today.

NobleProg has been providing Docker & Kubernetes training since 2015. With over 360 successfully completed training projects, we have established ourselves as one of the most recognized training companies globally in the field of containerization.

Since 2019, we have also been assisting our customers in validating their performance in Kubernetes environments by preparing them and encouraging them to pass the CKA and CKAD exams.

This instructor-led live training (available online or onsite) is designed for System Administrators and Kubernetes users who wish to validate their knowledge by passing the CKA exam.

Additionally, the training focuses on gaining practical experience in Kubernetes Administration; therefore, we recommend participating even if you do not intend to take the CKA exam.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice.
• Hands-on implementation in a live lab environment.

Course Customization Options

• To request customized training for this course, please contact us to arrange it.
• To learn more about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

The Certified Kubernetes Application Developer (CKAD) certification was established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the organization responsible for Kubernetes.

This instructor-led, live training—available either online or on-site—is designed for developers who wish to validate their proficiency in designing, building, configuring, and exposing cloud-native applications within Kubernetes environments.

Moreover, the program emphasizes practical, hands-on experience in Kubernetes application development. Therefore, we recommend participating in this course even if you do not plan to take the CKAD exam.

NobleProg has been providing Docker and Kubernetes training since 2015. With over 360 successfully completed training projects, we have established ourselves as one of the leading training providers globally in the field of containerization. Since 2019, we have also supported our clients in validating their performance in Kubernetes environments by preparing them to pass the CKA and CKAD examinations.

Course Format

• Interactive lectures and discussions.
• Ample exercises and practice sessions.
• Hands-on implementation in a live laboratory environment.

Course Customization Options

• To request customized training for this course, please contact us to make arrangements.
• For more information about CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

This instructor-led, live training in South Korea (online or onsite) is designed for engineers who wish to use Docker to deploy and manage software as containers instead of as traditional standalone software.

Upon completion of this training, participants will be able to:

• Install and configure Docker.
• Understand and implement software containerization.
• Manage Docker-based applications.
• Connect various Docker applications and systems.
• Understand and modify Docker registries.

In this instructor-led, live training in South Korea, participants will learn how to manage Red Hat OpenShift Container Platform.

By the end of this training, participants will be able to:

• Create, configure, manage, and troubleshoot OpenShift clusters.
• Deploy containerized applications on-premise, in public cloud or on a hosted cloud.
• Secure OpenShift Container Platform
• Monitor and gather metrics.
• Manage storage.

In this instructor-led live training in South Korea (onsite or remote), participants will learn how to create and manage Docker containers, then deploy a sample application inside a container. Participants will also learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. Finally, the training goes on to more advanced topics, walking participants through the process of securing, scaling and monitoring a Kubernetes cluster.

By the end of this training, participants will be able to:

• Set up and run a Docker container.
• Deploy a containerized server and web application.
• Build and manage Docker images.
• Set up a Docker and Kubernetes cluster.
• Use Kubernetes to deploy and manage a clustered web application.
• Secure, scale and monitor a Kubernetes cluster.

Docker serves as a containerization platform that enables the creation of reproducible, portable, and scalable environments for machine learning systems.

This instructor-led training, available in online or onsite formats, is designed for intermediate to advanced technical professionals seeking to containerize and operationalize complete ML pipelines using Docker.

Upon completing this training, participants will be equipped to:

• Containerize machine learning training, validation, and inference workloads.
• Design and orchestrate end-to-end ML pipelines utilizing Docker and complementary tools.
• Implement versioning, reproducibility, and CI/CD processes for ML components.
• Deploy, monitor, and scale ML services within containerized environments.

Course Format

• Interactive lectures accompanied by practical demonstrations.
• Hands-on exercises focused on constructing real-world ML pipeline components.
• Live-lab implementation of end-to-end containerized workflows.

Customization Options

• For training tailored to specific ML infrastructure requirements, please contact us to discuss available options.

Course Objectives: Acquire theoretical and operational skills in Docker and Kubernetes.

GPU acceleration is critical for executing high-performance deep learning workloads in a scalable and efficient manner.

This instructor-led, live training (available online or onsite) is designed for intermediate-level technical professionals looking to configure, optimize, and deploy GPU-enabled AI workloads within Docker containers.

Upon completing this course, participants will be able to:

• Build and run GPU-enabled containers for both training and inference.
• Configure CUDA, drivers, and runtime libraries for containerized AI workflows.
• Optimize resource allocation and isolation for GPU-intensive applications.
• Deploy scalable, containerized deep learning services in production environments.

Format of the Course

• Interactive instruction supported by real-world demonstrations.
• Exercise-driven practice focused on GPU-enabled development.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• For tailored training aligned with your infrastructure or GPU stack, please contact us to arrange.

Hybrid AI deployment involves executing AI inference across cloud, on-premises, and edge environments using unified, container-based workflows.

This instructor-led live training, available online or on-site, is designed for advanced professionals seeking to architect and deploy distributed AI inference systems within heterogeneous environments.

Upon completing this training, participants will gain the ability to:

• Construct secure and scalable containerized AI services for multi-location settings.
• Deploy AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
• Integrate orchestration tools to automate distributed AI operations.
• Enhance inference latency, reliability, and resilience across diverse infrastructure.

Course Format

• Guided presentations and expert-led discussions.
• Comprehensive hands-on practice and applied exercises.
• Real-world experimentation within a controlled live-lab environment.

Customization Options

• To tailor this course to your organization’s specific infrastructure or use cases, please contact us for customization options.

This instructor-led, live training in South Korea (online or onsite) is designed for intermediate Java developers aiming to design, develop, deploy, and maintain microservices-based applications using Java frameworks such as Spring Boot and Spring Cloud.

Upon completion of this training, participants will be able to:

• Comprehend the fundamental principles and advantages of microservices architecture.
• Build and deploy microservices using Java and Spring Boot.
• Implement service discovery, configuration management, and API gateways.
• Effectively secure, monitor, and scale microservices.
• Deploy microservices using Docker and Kubernetes.

In this instructor-led, live training in South Korea (onsite or remote), participants will learn how to deploy a collection of sample servers inside containers, then automate, scale, and manage their containerized servers within a Kubernetes cluster. The training goes on to more advanced topics, walking participants through the process of securing, networking and monitoring a Kubernetes cluster.

By the end of this training, participants will be able to:

• Set up and run a Docker container.
• Deploy containerized databases and servers.
• Set up a Docker and Kubernetes cluster.
• Use Kubernetes to deploy and manage different environments under the same cluster.
• Secure, scale and monitor a Kubernetes cluster.

This instructor-led, live training in South Korea (online or onsite) is aimed at intermediate-level developers and DevOps engineers who wish to build, deploy, and manage microservices using Spring Cloud and Docker.

By the end of this training, participants will be able to:

• Develop microservices using Spring Boot and Spring Cloud.
• Containerize applications with Docker and Docker Compose.
• Implement service discovery, API gateways, and inter-service communication.
• Monitor and secure microservices in production environments.
• Deploy and orchestrate microservices using Kubernetes.