Docker Training in Auckland

CI/CD for AI is a structured approach to automating model packaging, testing, containerisation, and deployment using continuous integration and continuous delivery pipelines.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to automate end-to-end AI model delivery workflows using Docker and CI/CD platforms.

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

• Create automated pipelines for building and testing AI model containers.
• Implement version control and ensure reproducibility throughout model lifecycles.
• Integrate automated deployment strategies for AI services.
• Apply CI/CD best practices 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 in a controlled environment.

Course Customisation Options

• If your organisation requires customised pipeline workflows or platform integrations, please contact us to tailor this course.

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

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

Upon completing this training, participants will be able to:

• Build secure and scalable containerised 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.
• Optimise 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 Customisation Options

• For tailored adjustments to align this course with your organisation's infrastructure or use cases, please contact us to customise the training.

Docker is a containerisation platform used to build portable, isolated, and secure deployment environments for AI inference services.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level technical professionals who wish to build secure, portable AI inference microservices that can be deployed consistently across local machines, servers, or cloud VMs.

By the conclusion of this workshop, participants will be able to:

• Build lightweight inference containers for local and cloud deployment.
• Secure containerised AI services using best-practice techniques.
• Implement portable microservice workflows for consistent environments.
• Deploy AI inference endpoints across diverse infrastructures.

Format of the Course

• Guided lectures paired with practical demonstrations.
• Hands-on exercises to reinforce deployment and security techniques.
• Live-lab practice for building and running portable inference services.

Course Customisation Options

• To tailor this training to your infrastructure or AI tooling stack, please contact us to arrange.

In this instructor-led, live training in Auckland (onsite or remote), participants will learn how to deploy a collection of sample servers inside containers, then automate, scale, and manage their containerised servers within a Kubernetes cluster. The training progresses to more advanced topics, guiding 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 containerised 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.

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

This instructor-led, live training (online or on-site) is designed for intermediate-level technical professionals who wish to configure, optimise, and run GPU-enabled AI workloads inside Docker containers.

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

• Build and run GPU-enabled containers for training and inference.
• Configure CUDA, drivers, and runtime libraries for containerised AI workflows.
• Optimise resource allocation and isolation for GPU-intensive applications.
• Deploy scalable, containerised deep learning services in production environments.

Course Format

• Interactive instruction supported by real-world demonstrations.
• Exercise-driven practice focused on GPU-enabled development.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

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

Docker is a containerisation platform used to build reproducible, portable, and scalable environments for ML systems.

This instructor-led, live training (online or on-site) is designed for intermediate to advanced-level technical professionals who wish to containerise and operationalise complete ML pipelines using Docker.

Upon completion of 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 in containerised environments.

Course Format

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

Course Customisation Options

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

Docker is a containerisation platform that enables consistent, portable, and reproducible environments for AI and machine learning workloads.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to package ML codebases, dependencies, and models using Docker for 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 different 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.

This instructor-led, live training in Auckland (online or on-site) is designed for intermediate-level developers and DevOps engineers who aspire to build, deploy, and manage microservices using Spring Cloud and Docker.

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

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

Training objectives: Gain theoretical and practical skills in Docker and Kubernetes.

In this instructor-led, live training in Auckland (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 containerised 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 containerised 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.

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

Kubernetes is now a leading platform used 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 containerisation.

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 (online or on-site) 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 taking part in it, even if you do not intend to take the CKA exam.

Course Format

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

Course Customisation Options

• To request customised 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 aim of this hands-on course is to equip participants with all the tools needed to address the practical aspects of Docker and Kubernetes, ensuring they develop the essential skills for effective program management.

In this instructor-led, live training in Auckland, 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 containerised applications on-premise, in public cloud or on a hosted cloud.
• Secure Red Hat OpenShift Container Platform
• Monitor and gather metrics.
• Manage storage.

In this instructor-led, live training in Auckland, participants will learn how to use OpenShift Container Platform to deploy containerised applications.

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

• Create and configure an OpenShift environment.
• Deploy applications rapidly on-premises, in the public cloud, or on a hosted cloud.

The Certified Kubernetes Application Developer (CKAD) programme has been 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 designing, building, configuring, and exposing cloud-native applications for Kubernetes.

Furthermore, the training is also focused on gaining practical experience in Kubernetes application development, so we recommend taking part even if you do not intend to sit 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 best-known training companies worldwide in the field of containerisation. Since 2019, we have also been helping our customers confirm their performance in k8s environments by preparing them and encouraging them to pass CKA and CKAD exams.

Course Format

• Interactive lecture and discussion.
• Abundant exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training session 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 course in Auckland provides participants with an overview of Rancher and demonstrates, through hands-on practice, how to deploy and manage a Kubernetes cluster using Rancher.

This instructor-led, live training (delivered online or on-site) is designed for engineers who wish to evaluate each of these services to make an informed decision about which solution best fits their organisation's needs.

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

• Set up a development environment equipped with all the necessary libraries, packages, and frameworks required to begin development.
• Configure, set up, and deploy a series of demonstration containers using a variety of different approaches.
• Understand the architectural and design differences between various Docker and Kubernetes solutions within AWS.
• Automate the deployment of Docker containers.
• Establish a continuous integration and deployment pipeline.
• Integrate Docker and Kubernetes into an existing continuous integration system.

This instructor-led, live training in Auckland (available online or on-site) is designed for engineers who wish to deepen their Docker expertise to deploy applications at scale while maintaining full control.

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

• Build their own Docker images.
• Deploy and manage large numbers of Docker applications.
• Evaluate different container orchestration solutions and select the most suitable one.
• Establish a continuous integration pipeline for Docker applications.
• Integrate Docker applications with existing continuous integration tools and processes.
• Secure their Docker applications.

Docker is a platform designed for developers and system administrators to build, deploy, and maintain distributed applications. It includes a runtime environment for executing containers and a service for sharing them.

With Docker, the same application can run unmodified across laptops, dedicated servers, and virtual servers.

This course, spanning the first two days, covers the fundamental usage of Docker, providing valuable skills for both developers and system administrators. The course features numerous hands-on exercises, allowing participants to practice within their own Docker environments and create their own Docker images.

On the final day, participants will explore more advanced tools that integrate with Docker, including Docker Machine, Docker Compose, and Docker Swarm.

This instructor-led, live training in Auckland (available online or on-site) is tailored for engineers who wish to adopt Docker to deploy and manage software as containers, rather than as traditional stand-alone applications.

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

• Install and configure Docker.
• Understand and implement software containerisation.
• Manage Docker-based applications.
• Network different Docker applications and systems.
• Understand and work with Docker registries.

Docker is a platform designed for developers and system administrators to maintain distributed applications. It comprises a runtime for executing containers and a service for sharing them.

With Docker, the same application can run unchanged on laptops, dedicated servers, and virtual servers.

This course covers the fundamentals of Docker, making it valuable for both developers and system administrators. It includes numerous hands-on exercises, allowing participants to practice within their own Docker environments and build their own Docker images over the two-day period.

This instructor-led, live training in Auckland (available online or on-site) is designed for DevOps engineers who wish to optimise and streamline their CI/CD workflows using Docker and Jenkins.

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

• Automate code delivery and pipeline deployment using Jenkins.
• Build applications with Docker and Dockerfiles.
• Configure authentication options to enhance security.

Course Format

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

Course Customisation Options

• To request a customised training session for this course, please contact us to make arrangements.

In this instructor-led, live training in Auckland, participants will learn the fundamentals of building microservices using Spring Cloud and Docker. Their understanding will be tested through hands-on exercises and the step-by-step development of sample microservices.

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

• Understand the core principles of microservices.
• Use Docker to build containers for microservice applications.
• Build and deploy containerised microservices using Spring Cloud and Docker.
• Integrate microservices with discovery services and the Spring Cloud API Gateway.
• Use Docker Compose for end-to-end integration testing.

In this instructor-led, live training in Auckland (delivered online or on-site), participants will learn how to install, configure, and manage OpenShift Container Platform v4.

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

• Understand OCI (Open Containers Initiative) and its implications for using container engines such as Docker in OpenShift.
• Understand the relationship between the different versions of OpenShift (OKP, OpenShift Container Platform, Red Hat OpenShift, etc.).
• Create, configure, manage, and troubleshoot an OpenShift cluster.
• Implement OpenShift's self-management capabilities to improve platform stability and consistency.
• Secure OpenShift Container Platform.
• Monitor and gather metrics.
• Manage storage.
• Upgrade an OpenShift Container Platform 3 cluster to OpenShift Container Platform 4.

This instructor-led, live training (available online or on-site) is designed for DevOps engineers who wish to use Selenium to execute Selenium tests within Docker containers.

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

• Build test automation infrastructure for on-demand testing.
• Develop a test automation framework using Java.
• Construct a CI/CD pipeline from scratch using Jenkins and Docker.