Building Microservices with Spring Cloud and Docker Training Course

This instructor-led, live training in South Africa (online or on-site) is aimed at engineers who wish to advance their knowledge of Docker 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 containerisation platform that provides consistent, portable, and reproducible environments for artificial intelligence and machine learning workloads.

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

Upon completing this course, participants will be able to:

• Build and manage Docker images tailored for AI and ML applications.
• Containerise machine learning pipelines, tools, and dependencies.
• Optimise Docker environments for performance and portability.
• Deploy containerised ML services across various runtime environments.

Course Format

• Concept demonstrations supported by guided discussion.
• Hands-on exercises focused on real-world containerisation tasks.
• Practical implementation using live-lab Docker environments.

Course Customisation Options

• To customise this training for your organisational environment, please contact us to arrange.

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

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

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

• Creating automated pipelines for building and testing AI model containers.
• Implementing version control and ensuring reproducibility throughout the model lifecycle.
• Integrating automated deployment strategies for AI services.
• Applying CI/CD best practices tailored specifically 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 conducted 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) programme was established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF).

Kubernetes is currently the leading platform for container orchestration.

NobleProg has been delivering Docker and Kubernetes training since 2015. Having successfully completed over 360 training projects, we have established ourselves as one of the world's most recognised training providers in the field of containerisation.

Since 2019, we have also been assisting our customers in validating their performance in Kubernetes environments by preparing them to sit and 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.

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

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

The Certified Kubernetes Application Developer (CKAD) programme was created by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the custodians of Kubernetes.

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

Furthermore, the training focuses on gaining practical experience in Kubernetes application development; therefore, we recommend participation even if you do not intend to sit for the CKAD exam.

NobleProg has been delivering Docker and Kubernetes training since 2015. With over 360 successfully completed training projects, we have established ourselves as one of the most recognised training providers globally in the field of containerisation. Since 2019, we have also assisted our customers in validating their performance in Kubernetes environments by preparing them and encouraging them to pass the CKA and CKAD exams.

Course Format

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

Course Customisation Options

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

This instructor-led, live training in South Africa (online or onsite) is aimed at engineers who wish to use Docker to deploy and manage software as containers instead of as traditional stand-alone software.

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

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

In this instructor-led, live training in South Africa, 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 South Africa (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 online or onsite) targets intermediate to advanced technical professionals aiming to containerize and operationalise complete ML pipelines using Docker.

Upon completing this training, participants will be able to:

• Containerise ML training, validation, and inference workloads.
• Design and orchestrate end-to-end ML pipelines using Docker and supporting tools.
• Implement versioning, reproducibility, and CI/CD for ML components.
• Deploy, monitor, and scale ML services within containerised environments.

Course Format

• Interactive lectures complemented by practical demonstrations.
• Hands-on exercises focused on constructing real ML pipeline components.
• Live-lab implementation for end-to-end containerised workflows.

Course Customisation Options

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

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

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

This instructor-led live training (available online or onsite) targets intermediate-level technical professionals keen on configuring, optimising, and deploying GPU-enabled AI workloads within Docker containers.

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

• Construct and execute GPU-enabled containers for both training and inference tasks.
• Configure CUDA, drivers, and runtime libraries to support containerised AI workflows.
• Optimise resource allocation and isolation for applications that are intensive on GPU usage.
• Deploy scalable, containerised deep learning services within production environments.

Format of the Course

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

Course Customization Options

• For tailored training that aligns with 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 via unified container-based workflows.

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

Upon completion, participants will be able to:

• Construct secure and scalable containerized AI services for multi-location setups.
• Deploy AI inference workloads to cloud, 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 setup.

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 South Africa (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:

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

In this instructor-led live training held South Africa (onsite or remotely), participants will learn how to deploy sample servers within containers, then automate, scale, and manage these servers in a Kubernetes cluster. The training covers advanced topics, guiding participants through 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 Africa (online or onsite) targets intermediate-level developers and DevOps engineers aiming to build, deploy, and manage microservices via Spring Cloud and Docker.

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

• Developing microservices leveraging Spring Boot and Spring Cloud.
• Containerising applications with Docker and Docker Compose.
• Implementing service discovery, API gateways, and inter-service communication.
• Monitoring and securing microservices within production environments.
• Deploying and orchestrating microservices using Kubernetes.