Building Microservices with Spring Cloud and Docker Training Course

This instructor-led, live training in Turkey (online or on-site) targets engineers who wish to enhance 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 integration processes.
• Secure their Docker applications.

By the end of 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 most appropriate solution.
• Establishing a continuous integration pipeline for Docker applications.
• Integrating Docker applications into existing CI/CD toolchains.
• Implementing security best practices 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 facilitates consistent, portable, and reproducible environments for artificial intelligence and machine learning workloads.

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

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

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

Course Format

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

Course Customization Options

• For training customized to your organizational environment, please contact us to make arrangements.

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

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

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

• Develop automated pipelines for building and testing AI model containers.
• Establish version control and reproducibility standards for model lifecycles.
• Incorporate automated deployment strategies for AI services.
• Apply CI/CD best practices specifically tailored to machine learning operations.

Course Format

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

Customization Options

• Should your organization require 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).

Kubernetes has now become a leading platform for container orchestration.

NobleProg has been delivering Docker & Kubernetes training since 2015. With more than 360 successfully completed training projects, we have become one of the best-known training companies worldwide in the field of containerization.

Since 2019, we have also been helping our customers confirm their performance in k8s environments by preparing them and encouraging them to pass the CKA and CKAD exams.

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

On the other hand, the training is also focused on gaining practical experience in Kubernetes Administration, so we recommend participating in it even if you do not intend to take the CKA exam.

Format of the Course

• Interactive lecture and discussion.
• Abundant 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 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 (online or onsite) is aimed at Developers who wish to confirm their skills in design, build, configure, and expose cloud native applications for Kubernetes.

On the other hand, training is also focused on gaining practical experience in Kubernetes application development, so we recommend taking part in it, even if you don't intend to take CKAD exam.

NobleProg have been delivering Docker & Kubernetes training from 2015. With more than 360 successfully completed training projects, we became one of the best known training company worldwide in field of containerization. Since 2019 we are also helping our customers to confirm their performance in k8s environment by preparing them and encouraging to pass CKA and CKAD exams.

Format of the Course

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

This instructor-led live training in Turkey (online or onsite) is targeted at engineers who want 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.
• Manage Docker-based applications.
• Network different Docker applications and systems.
• Understand and edit Docker registries.

In this instructor-led, live training in Turkey, 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 Turkey (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 build reproducible, portable, and scalable environments for ML systems.

This instructor-led, live training (available online or onsite) targets intermediate to advanced technical professionals who want to containerize and operationalize complete ML pipelines using Docker.

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

• Containerize 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 in containerized environments.

Format of the Course

• Interactive lectures supported by practical demonstrations.
• Hands-on exercises focused on building real 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.

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

This instructor-led, live training session (available online or onsite) is designed for intermediate-level technical professionals who want 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 both training and inference purposes.
• Set up CUDA, drivers, and runtime libraries tailored for containerized AI workflows.
• Enhance resource allocation and isolation specifically for GPU-intensive applications.
• Deploy scalable, containerized deep learning services in production settings.

Course Format

• Interactive instruction enhanced by real-world demonstrations.
• Practice-driven exercises focused on GPU-enabled development.
• Hands-on implementation within a live-lab environment.

Customization Options

• For bespoke training aligned with your specific infrastructure or GPU stack, please get in touch to arrange.

This instructor-led, live training in Turkey (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 live, instructor-led training in Turkey (online or onsite) is designed for intermediate developers and DevOps engineers who aim 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.

This instructor-led, live training in Turkey (online or onsite) targets developers aiming to shift from traditional architecture to a highly concurrent microservices-based model using Spring Cloud, Kafka, Docker, Kubernetes, and Redis.

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

• Configure the required development environment for constructing microservices.
• Design and implement a highly concurrent microservices ecosystem leveraging Spring Cloud, Kafka, Redis, Docker, and Kubernetes.
• Convert monolithic and SOA services into a microservice-based architecture.
• Implement a DevOps approach for software development, testing, and release.
• Ensure high concurrency levels among microservices in production environments.
• Monitor microservices and establish recovery strategies.
• Conduct performance tuning.
• Explore future trends in microservices architecture.