Building Microservices with Spring Cloud and Docker Training Course

This instructor-led, live training in Bulgaria (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 completion of this training, participants will be able to:

• Create custom Docker images.
• Deploy and manage a large volume of Docker applications.
• Evaluate various container orchestration solutions and select the most appropriate one.
• Establish a continuous integration process for Docker applications.
• Integrate Docker applications with existing CI tooling workflows.
• Implement security measures for Docker applications.
• Utilize Kubernetes to deploy and manage multiple environments within a single cluster.
• Secure, scale, and monitor a Kubernetes cluster.

Docker serves as a containerization platform, providing consistent, portable, and reproducible environments specifically designed for AI and machine learning workloads.

This instructor-led training, available both online and on-site, targets intermediate-level professionals who aim to encapsulate ML codebases, dependencies, and models within Docker to ensure reliable workflows from development to production.

Upon finishing this course, participants will be capable of:

• Creating and managing Docker images customized for AI and ML applications.
• Containerizing machine learning pipelines, tools, and associated dependencies.
• Optimizing Docker environments to enhance performance and portability.
• Deploying containerized ML services across various runtime environments.

Course Format

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

Customization Options

• For training tailored to your organizational needs, please reach out to us to arrange a session.

CI/CD for AI provides a structured methodology for automating the packaging, testing, containerization, and deployment of AI models through continuous integration and continuous delivery pipelines.

This instructor-led live training, available both online and onsite, is designed for intermediate-level professionals seeking to automate end-to-end AI model delivery workflows utilizing Docker and CI/CD platforms.

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

• Establishing automated pipelines for the construction and testing of AI model containers.
• Enforcing version control and reproducibility throughout the model lifecycle.
• Integrating automated deployment strategies for AI services.
• Applying 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 within a controlled environment.

Course Customization Options

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

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

Today, Kubernetes stands as the leading platform for container orchestration.

Since 2015, NobleProg has been providing Docker and Kubernetes training. With over 360 successfully completed training projects, we have become one of the most recognized training providers globally in the field of containerization.

Since 2019, we have also been assisting our clients in validating their proficiency in Kubernetes (k8s) environments by preparing them for and encouraging them to take 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.

Furthermore, the training emphasizes gaining practical experience in Kubernetes Administration. Therefore, we recommend participating even if you do not plan to take the CKA exam.

Format of the Course

• 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 make arrangements.
• To learn more about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

The Certified Kubernetes Application Developer (CKAD) program is developed by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the host of Kubernetes.

This instructor-led, live training (available online or onsite) is aimed at Developers who want to validate their skills in designing, building, configuring, and exposing cloud native applications for Kubernetes.

Additionally, the training focuses on gaining practical experience in Kubernetes application development, so we recommend participating even if you do not plan to take the CKAD exam.

NobleProg has been delivering Docker & Kubernetes training since 2015. With more than 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 been helping our customers validate their performance in Kubernetes environments by preparing them to pass the CKA and CKAD exams.

Course Format

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

Course Customization Options

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

This instructor-led, live training in Bulgaria (online or onsite) is designed for engineers who want to deploy and manage software as containers instead of as traditional standalone applications.

Upon completion 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 Bulgaria, 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 Bulgaria (onsite or remote), participants will learn to create and manage Docker containers and deploy a sample application within one. Attendees will also learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. Finally, the training progresses to more advanced topics, guiding 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 online or on-site, targets technical professionals at intermediate to advanced levels who aim to containerize and operationalize complete ML pipelines using Docker.

Upon completing this course, participants will be able to:

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

Course Format

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

Course Customization Options

• For customized training tailored to specific ML infrastructure requirements, please contact us to explore options.

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

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

This instructor-led live training, available either online or onsite, is designed for technical professionals with intermediate expertise who aim to configure, optimize, and deploy GPU-enabled AI workloads within Docker containers.

Upon completing this course, participants will be capable of:

• Constructing and running GPU-enabled containers for both training and inference tasks.
• Setting up CUDA, drivers, and runtime libraries to support containerized AI workflows.
• Optimizing resource allocation and isolation for applications heavily reliant on GPUs.
• Deploying scalable, containerized deep learning services within production environments.

Course Format

• Interactive instruction complemented by real-world demonstrations.
• Exercise-driven practice focusing on GPU-enabled development.
• Hands-on implementation within a live laboratory environment.

Customization Options

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

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

This instructor-led, live training (available online or onsite) is designed for advanced-level professionals aiming to design and deploy distributed AI inference systems across heterogeneous environments.

Upon completing this training, participants will be able to:

• Create secure and scalable containerized AI services for multi-location environments.
• Deploy AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
• Integrate orchestration tools to automate distributed AI operations.
• Optimize 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 setup.

Course Customization Options

• To tailor this course to your organization’s specific infrastructure or use cases, please contact us to customize the training.

This instructor-led, live training in Bulgaria (online or onsite) targets intermediate-level Java developers who want 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:

• Grasp the principles and advantages of microservices architecture.
• Construct and deploy microservices utilizing Java and Spring Boot.
• Implement service discovery, configuration management, and API gateways.
• Secure, monitor, and scale microservices efficiently.
• Deploy microservices using Docker and Kubernetes.

This instructor-led, live training in Bulgaria (online or onsite) is designed for developers and DevOps engineers with intermediate-level skills who wish to build, deploy, and manage microservices using Spring Cloud and Docker.

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

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