Building Microservices with Spring Cloud and Docker Training Course

This instructor-led, live training in Romania (online or onsite) is aimed at engineers who wish to advance their knowledge of Docker so as 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 manager 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.

Upon completing this training, participants will be capable of:

• Creating custom Docker images.
• Deploying and managing a high volume of Docker applications.
• Evaluating various container orchestration platforms and selecting the optimal solution.
• Establishing a continuous integration pipeline for Docker-based applications.
• Integrating Docker applications into existing continuous integration workflows.
• Implementing security measures for Docker applications.
• Utilizing Kubernetes to deploy and manage diverse environments within a single cluster.
• Securing, scaling, and monitoring a Kubernetes cluster.

Docker serves as a containerization platform that delivers consistent, portable, and reproducible environments specifically designed for artificial intelligence and machine learning workloads.

This instructor-led live training, available online or onsite, targets intermediate-level professionals seeking to package ML codebases, dependencies, and models using Docker to ensure reliable workflows from development to production.

Upon completing this course, participants will be able to:

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

Course Format

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

Course Customization Options

• To tailor this training to your organizational environment, please contact us to make arrangements.

CI/CD for AI represents a systematic method for automating the packaging, testing, containerization, and deployment of models through continuous integration and continuous delivery pipelines.

This instructor-led, live training, available both online and onsite, targets intermediate-level professionals seeking to streamline end-to-end AI model delivery workflows using Docker and CI/CD platforms.

Upon completing the training, participants will be equipped to:

• Construct automated pipelines for building and testing AI model containers.
• Establish version control and reproducibility standards throughout the model lifecycle.
• Incorporate automated deployment strategies for AI services.
• Apply CI/CD best practices specifically adapted for 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

• Should your organization require customized pipeline workflows or specific platform integrations, please contact us to tailor this course accordingly.

The Certified Kubernetes Administrator (CKA) certification was established by The Linux Foundation in collaboration with the Cloud Native Computing Foundation (CNCF).

Kubernetes has emerged as the premier platform for container orchestration.

Since 2015, NobleProg has specialized in Docker and Kubernetes training. With over 360 successfully delivered training projects, we have become one of the world’s most recognized training providers in the field of containerization.

Since 2019, we have further supported our customers by preparing them to validate their performance in Kubernetes environments through 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 plan to take the CKA exam.

Course Format

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

Course Customization Options

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

The Certified Kubernetes Application Developer (CKAD) program was established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), which hosts Kubernetes.

This instructor-led live training (available online or onsite) targets developers who wish to validate their ability to design, build, configure, and expose cloud-native applications on Kubernetes.

Additionally, the training emphasizes gaining practical experience in Kubernetes application development, so we encourage participation even if you do not plan to take the CKAD exam.

NobleProg has delivered Docker and Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most recognized training companies globally in the field of containerization. Since 2019, we have also assisted our customers in validating their performance in Kubernetes environments by preparing and encouraging them to pass the CKA and CKAD exams.

Format of the Course

• Interactive lecture and discussion.
• Ample 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.
• To learn more about CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

This instructor-led, live training in Romania (online or onsite) is designed for engineers who wish to use Docker to deploy and manage software as containers rather than as traditional standalone applications.

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

• Install and configure Docker.
• Understand and implement software containerization.
• Manage Docker-based applications.
• Network different Docker applications and systems.
• Understand and edit Docker registries.

In this instructor-led, live training in Romania, participants will acquire the skills necessary to manage the Red Hat OpenShift Container Platform.

Upon completion of this training, participants will be capable of:

• Creating, configuring, managing, and troubleshooting OpenShift clusters.
• Deploying containerized applications on-premise, in public cloud environments, or on hosted cloud services.
• Implementing security measures for OpenShift Container Platform
• Monitoring and collecting metrics.
• Managing storage solutions.

In this instructor-led, live training in Romania (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 designed to create reproducible, portable, and scalable environments for machine learning systems.

This instructor-led live training, available both online and onsite, targets intermediate to advanced technical professionals seeking to containerize and operationalize entire ML pipelines using Docker.

Upon completing this training, participants will be equipped to:

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

Format of the Course

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

Course Customization Options

• For customized training aligned with specific ML infrastructure needs, please contact us to discuss options.

Training Objectives: Acquire theoretical and practical skills in Docker and Kubernetes.

Leveraging GPU acceleration is crucial for executing high-performance deep learning tasks in a manner that is both scalable and efficient.

This instructor-led live training, available online or on-site, targets intermediate-level technical professionals looking to configure, optimize, and execute GPU-enabled AI workloads within Docker containers.

Upon completing this course, participants will be equipped to:

• Construct and operate GPU-enabled containers for model training and inference.
• Set up CUDA, drivers, and runtime libraries specifically for containerized AI workflows.
• Fine-tune resource allocation and ensure isolation for GPU-heavy applications.
• Deploy scalable, containerized deep learning services within production environments.

Course Format

• Interactive instruction reinforced by real-world demonstrations.
• Practical exercises centered on GPU-enabled development.
• Hands-on implementation within a live laboratory setting.

Customization Options

• For customized training tailored to your specific infrastructure or GPU stack, please reach out to us to arrange.

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

This instructor-led, live training (available online or onsite) targets advanced professionals aiming to design and deploy distributed AI inference systems within heterogeneous environments.

After completing this training, participants will be equipped 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.
• Extensive hands-on practice and applied exercises.
• Real-world experimentation in a controlled live-lab environment.

Course Customization Options

• For tailored adjustments to align this course with your organization’s infrastructure or specific use cases, please contact us to customize the training.

This instructor-led live training in Romania (online or onsite) is aimed at intermediate-level Java developers who wish to design, develop, deploy, and maintain microservices-based applications using Java frameworks like Spring Boot and Spring Cloud.

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

• Understand the principles and benefits of microservices architecture.
• Build and deploy microservices using Java and Spring Boot.
• Implement service discovery, configuration management, and API gateways.
• Secure, monitor, and scale microservices effectively.
• Deploy microservices using Docker and Kubernetes.

This instructor-led live training, conducted Romania (online or onsite), targets intermediate developers and DevOps engineers seeking to build, deploy, and manage microservices using Spring Cloud and Docker.

By the conclusion 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.