Building Microservices with Spring Cloud and Docker Training Course

This instructor-led live training in India (online or onsite) 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 containerization platform that allows for the creation of consistent, portable, and reproducible environments specifically suited for AI and machine learning workloads.

This live training, led by an instructor and available either online or onsite, is designed for intermediate-level professionals aiming to package ML codebases, dependencies, and models using Docker to establish reliable workflows from development to production.

Upon successful completion of this course, participants will gain the ability to:

• Create and manage Docker images specifically customized for AI and ML applications.
• Containerize machine learning pipelines, tools, and associated dependencies.
• Optimize Docker environments to enhance both performance and portability.
• Deploy containerized ML services across a variety of runtime environments.

Course Format

• Conceptual demonstrations accompanied by guided discussions.
• Practical exercises centered on real-world containerization scenarios.
• Hands-on implementation utilizing live-lab Docker environments.

Options for Course Customization

• For organizations seeking to tailor this training to their specific environment, please reach out to us to make arrangements.

CI/CD for AI represents a systematic methodology 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, is designed for intermediate-level professionals aiming to automate end-to-end AI model delivery workflows leveraging Docker and CI/CD platforms.

Upon completion of the training, participants will be equipped to:

• Develop automated pipelines for constructing and validating AI model containers.
• Establish version control and reproducibility mechanisms throughout the model lifecycle.
• Incorporate automated deployment strategies for AI services.
• Apply CI/CD best practices specifically adapted for machine learning operations (MLOps).

Course Format

• 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

• Should your organization require tailored pipeline workflows or specific platform integrations, please reach out to us to customize this course.

The Certified Kubernetes Administrator (CKA) certification is jointly offered by The Linux Foundation and the Cloud Native Computing Foundation (CNCF).

Kubernetes has emerged as a prominent platform for orchestrating containers.

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 globally recognized training providers in the field of containerization.

Since 2019, we have assisted our clients in validating their proficiency in Kubernetes (k8s) environments by preparing and encouraging them to take the CKA and CKAD examinations.

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

Furthermore, the training emphasizes gaining practical experience in Kubernetes administration. Therefore, we recommend participation 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 make arrangements.
• For more information about the CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

The Certified Kubernetes Application Developer (CKAD) certification program is jointly offered by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), which hosts Kubernetes.

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

Additionally, the training emphasizes gaining practical experience in Kubernetes application development. Therefore, we recommend participating 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 most recognized training providers globally in the field of containerization. Since 2019, we have also assisted customers in validating their performance in Kubernetes environments by preparing them to pass the CKA and CKAD exams.

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

This live training, led by an instructor in India (available online or onsite), is intended for engineers looking to adopt Docker for deploying and managing software as containers, moving away from traditional standalone models.

By the conclusion 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 India, 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 conducted in India (onsite or remote), participants will learn to create and manage Docker containers and deploy a sample application within a container. Additionally, participants will learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. The training concludes with advanced topics, guiding participants through 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 who aim to containerize and operationalize comprehensive ML pipelines using Docker.

After completing this training, participants will be equipped to:

• Containerize ML 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.

Format of the Course

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

Course Customization Options

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

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

Leveraging GPU acceleration is critical for executing high-performance deep learning tasks in a scalable and efficient way.

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

By the end of this course, participants will be equipped to:

• Construct and execute GPU-enabled containers for model training and inference.
• Set up CUDA, drivers, and runtime libraries to support containerized AI workflows.
• Optimize resource allocation and isolation for applications that are intensive on GPU resources.
• Deploy scalable, containerized deep learning services in production settings.

Course Delivery Format

• Interactive teaching reinforced with real-world demonstrations.
• Practical exercises focused on GPU-enabled development.
• Hands-on implementation within a live laboratory environment.

Customization Opportunities

• For bespoke training tailored to your specific infrastructure or GPU stack, please get in touch to make arrangements.

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 either online or onsite—is designed for advanced-level professionals aiming to design and deploy distributed AI inference systems within heterogeneous environments.

Upon completing this training, participants will be capable of:

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

Course Format

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

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 India (online or onsite) is designed for intermediate-level Java developers who aim 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 core 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 leveraging Docker and Kubernetes.

In this instructor-led, live training in India (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 India (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.