Containers and Virtual Machines (VMs) Training in Auckland

Edge AI is a paradigm focused on running machine learning inference close to data sources to achieve low-latency, efficient, and scalable processing.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level practitioners who wish to deploy, orchestrate, and optimise AI workloads on Kubernetes-based edge environments.

By completing this course, participants will be able to:

• Set up lightweight Kubernetes distributions for edge deployments.
• Deploy AI inference workloads effectively across constrained edge nodes.
• Manage connectivity challenges and synchronisation patterns.
• Optimise performance, storage, and networking for real-world edge scenarios.

Format of the Course

• Guided presentations supported by real-world examples.
• Scenario-based labs and practical edge deployment exercises.
• Hands-on experience with Kubernetes edge frameworks.

Course Customisation Options

• To request a customised training tailored to your edge platform needs, please contact us to arrange.

Kubernetes is a container orchestration platform widely used for managing distributed applications at scale.

This instructor-led, live training (online or on-site) is aimed at advanced-level practitioners who wish to apply AI and machine learning techniques to optimise Kubernetes resource usage, scheduling decisions, and autoscaling strategies.

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

• Apply AI/ML models to improve workload scheduling decisions in Kubernetes.
• Use predictive analytics to optimise CPU, GPU, and memory allocation.
• Implement intelligent autoscaling using reinforcement learning and metric forecasting.
• Reduce infrastructure costs and latency through automated resource optimisation.

Course Format

• Instructor-led technical presentations and in-depth discussions.
• Hands-on lab work using real Kubernetes clusters.
• Practical exercises applying AI models to real operational scenarios.

Course Customisation Options

• To tailor this course to your platform setup or operational requirements, please contact us for customisation.

MLOps on Kubernetes is a framework for automating the training, validation, packaging, and deployment of machine learning models using containerised pipelines and GitOps workflows.

This instructor-led, live training (online or on-site) is aimed at intermediate-level practitioners who wish to build automated, scalable MLOps pipelines on Kubernetes.

Upon completing this training, participants will be equipped to:

• Design end-to-end CI/CD pipelines for machine learning.
• Implement GitOps workflows for model deployment and versioning.
• Automate the training, testing, and packaging of ML models.
• Integrate monitoring, alerting, and rollback strategies.

Course Format

• Instructor-led presentations and technical deep dives.
• Hands-on exercises that build real-world CI/CD workflows.
• Live-lab practice deploying ML workloads to Kubernetes.

Course Customisation Options

• Organisations may request tailored content aligned with their internal MLOps tools and infrastructure.

Kubeflow is an open-source platform designed to streamline building, training, and deploying machine learning workloads on Kubernetes.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to build reliable ML workflows using Kubeflow.

Upon completion of this training, attendees will gain the skills to:

• Navigate the Kubeflow ecosystem and core components.
• Build reproducible workflows with Kubeflow Pipelines.
• Run scalable training jobs on Kubernetes.
• Serve machine learning models efficiently using Kubeflow Serving.

Course Format

• Guided presentations and collaborative discussions.
• Hands-on labs using real Kubeflow components.
• Practical exercises to build end-to-end ML workflows.

Course Customisation Options

• Customised versions of this training can be arranged to align with your team’s technology stack and project requirements.

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.

This instructor-led, live training in Auckland (either online or on-site) is designed for advanced-level Kubernetes administrators and DevOps engineers who wish to enhance their monitoring skills for Kubernetes clusters using Prometheus and Grafana.

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

• Set up Prometheus and Grafana for Kubernetes monitoring.
• Monitor key metrics across pods, nodes, and services.
• Create dynamic dashboards to visualise cluster health and performance.
• Implement alerting strategies for proactive issue resolution.
• Apply best practices for scaling monitoring solutions within Kubernetes environments.

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.

Kubernetes is an open-source platform for automating the deployment, scaling, and management of containerised applications.

This instructor-led, live training (available online or on-site) is designed for beginner to intermediate-level IT professionals who wish to master the core concepts and components of Kubernetes and use it to manage containerised applications at scale.

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

• Understand Kubernetes architecture and components.
• Deploy and manage containers within a Kubernetes cluster.
• Configure networking, storage, and scaling for workloads.
• Troubleshoot common issues and follow best practices for cluster operations.

Course Format

• Interactive lectures and discussion.
• Abundant exercises and practice opportunities.
• 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.

This instructor-led, live training in Auckland (delivered either online or on-site) is designed for DevOps engineers and developers who wish to leverage Kubernetes to build, deploy, and manage containers and cluster components within a secure and scalable environment.

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

• Understand the architecture, core concepts, and components of the Kubernetes ecosystem.
• Set up, install, and configure a Kubernetes cluster for container orchestration.
• Learn how to execute Kubernetes operations using command-line tools.
• Gain hands-on experience ranging from basic to advanced Kubernetes operations and administration.

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 then advances to more complex 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 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.

This instructor-led, live training in Auckland (online or onsite) is aimed at intermediate-level professionals who wish to effectively deploy, manage, and scale containerised applications using Kubernetes.

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

• Understand the Kubernetes architecture and its components.
• Isolate resources effectively using Namespaces.
• Manage and customise workloads with Deployments, StatefulSets, and DaemonSets.
• Define computational resources using Requests and Limits.
• Work with Jobs and CronJobs for scheduled tasks.
• Understand Services and DNS within Kubernetes.
• Expose applications using Ingress.
• Manage ConfigMaps, Secrets, and Persistent Volumes.
• Scale and upgrade Kubernetes clusters using advanced strategies.
• Analyse and troubleshoot Kubernetes issues.
• Deploy resources efficiently using Helm Charts.

This instructor-led, live training in Auckland (delivered online or on-site) is designed for intermediate to advanced-level developers, DevOps professionals, and architects who aim to design, deploy, and manage resilient applications using microservices, containers, and continuous integration/continuous deployment (CI/CD) pipelines.

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

• Understand and implement microservices architecture.
• Deploy and manage containerised applications using Docker and Kubernetes.
• Configure and optimise CI/CD pipelines for automated deployments.
• Apply best practices for security, monitoring, and observability.

This instructor-led, live training in Auckland (online or onsite) is designed for advanced-level platform engineers and DevOps professionals seeking to master scaling applications using microservices and Kubernetes.

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

• Design and implement scalable microservices architectures.
• Deploy and manage applications on Kubernetes clusters.
• Utilise Helm charts for efficient service deployment.
• Monitor and maintain the health of microservices in production.
• Apply best practices for security and compliance within a Kubernetes environment.

Learn the fundamentals of containers, Kubernetes and OpenShift in a practical, hands-on training designed for developers, DevOps engineers and IT professionals. Participants will learn how to build containerized applications, deploy workloads, manage Kubernetes resources and use OpenShift to streamline modern application delivery in cloud and hybrid environments.

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 (available online or on-site) is designed for beginner-level developers who wish to learn the fundamentals of Kubefirst and how it streamlines, secures, and speeds up Kubernetes and Swarm cluster management in enterprise environments.

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

• Set up a Kubefirst development environment.
• Write and execute a basic Kubefirst program.
• Annotate code using Kubefirst directives and clauses.
• Utilise the Kubefirst API and associated libraries.
• Profile and debug Kubefirst programs.

This instructor-led, live training in Auckland (online or on-site) is designed for intermediate-level developers and DevOps engineers who wish to incorporate Minikube into their development workflows.

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

• Set up and manage a local Kubernetes environment using Minikube.
• Understand how to deploy, manage, and debug applications on Minikube.
• Integrate Minikube into their continuous integration and deployment pipelines.
• Optimise their development processes by leveraging Minikube's advanced features.
• Apply best practices for local Kubernetes development.

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.

This instructor-led, live training in Auckland (online or on-site) is designed for beginner to intermediate-level software developers and DevOps professionals who want to learn how to set up and manage a local Kubernetes environment using Minikube.

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

• Install and configure Minikube on their local machine.
• Grasp the core concepts and architecture of Kubernetes.
• Deploy and manage containers using kubectl and the Minikube dashboard.
• Set up persistent storage and networking solutions for Kubernetes.
• Leverage Minikube for developing, testing, and debugging applications.

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

In this instructor-led, live training in Auckland (online or on-site), participants will learn how to set up and manage a production-grade container environment using Kubernetes on AKS.

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

• Configure and manage Kubernetes on AKS.
• Deploy, manage, and scale a Kubernetes cluster.
• Deploy containerised (Docker) applications on Azure.
• Migrate an existing Kubernetes environment from on-premises to the AKS cloud.
• Integrate Kubernetes with third-party continuous integration (CI) software.
• Ensure high availability and disaster recovery in Kubernetes.

Learn how to build, deploy and administer containerised environments using Docker, Kubernetes, and OpenShift. This five-day, hands-on training covers container images, Kubernetes workloads, cluster networking, storage, security, monitoring, and practical OpenShift administration. Participants gain the skills needed to operate modern container platforms and troubleshoot applications across development and production environments.

This instructor-led, live training (online or onsite) is designed for engineers who wish to automate, secure, and monitor containerised applications within a large-scale Kubernetes cluster.

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

• Use Kubernetes to deploy and manage different environments under the same cluster
• Secure, scale, and monitor a Kubernetes cluster

Course Format

• Interactive lectures and discussions
• Numerous exercises and practice sessions
• 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.

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.

Istio is an open-source service mesh that runs on Kubernetes to provide secure, observable, and manageable connectivity between microservices. By leveraging Istio's Envoy-based sidecar proxies, teams can enforce policies, secure communications with mTLS, gain deep observability into traffic, and improve reliability at scale.

This instructor-led, live training (online or on-site) is aimed at intermediate-level engineers who wish to deploy, secure, and manage microservices applications using Istio on Kubernetes.

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

• Install and configure Istio on Kubernetes clusters.
• Understand and apply service mesh concepts including traffic management, security, and observability.
• Deploy microservices applications within an Istio service mesh.
• Secure service-to-service communications with mutual TLS (mTLS) and Zero Trust principles.
• Monitor, trace, and troubleshoot microservices with Prometheus, Grafana, and Jaeger.
• Integrate Istio with Calico for advanced network policies and security.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice opportunities.
• 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.

The evolution of microservices and containers in recent years has significantly transformed how we design, develop, deploy, and operate software. Modern applications must be optimised for scalability, elasticity, resilience to failure, and adaptability to change. Driven by these evolving demands, contemporary architectures require a distinct set of patterns and practices. In this training, we explore ways to identify, understand, and adapt to these new requirements.

Audience
This training is designed for individuals who are already somewhat familiar with container technology and Kubernetes concepts but may lack hands-on, real-world experience. Grounded in real-world use cases and lessons learned from actual projects, the course aims to inspire participants to create and manage even better cloud-native applications.

• Developers
• Operations
• DevOps
• QA Engineers
• IT Project Managers

Course Format

• Interactive lectures and discussions
• Abundant exercises and practical practice
• Hands-on implementation in a live-lab environment

Course Customisation Options

• To request a customised version of this training, please contact us to arrange.

This instructor-led, live training in Auckland (online or onsite) is aimed at engineers who wish to use Helm to streamline the process of installing and managing Kubernetes applications.

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

• Install and configure Helm.
• Create reproducible builds of Kubernetes applications.
• Share applications as Helm charts.
• Run third-party applications saved as Helm charts.
• Manage releases of Helm packages.

This instructor-led, live training in Auckland (available online or on-site) is designed for DevOps engineers who want to leverage Kubernetes and GitLab to automate their DevOps lifecycle.

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

• Automate application builds, testing, and deployments.
• Establish an automated build infrastructure.
• Deploy applications to a containerised cloud environment.

This instructor-led, live training in Auckland (delivered online or on-site) is designed for Kubernetes practitioners seeking to prepare for the CKS exam.

By the end of this training, participants will know how to secure Kubernetes environments and container-based applications throughout the various stages of an application's lifecycle: build, deployment, and runtime.

This instructor-led, live training in Auckland (available online or on-site) is designed for developers and DevOps engineers who wish to adopt a serverless approach to build enterprise applications on Kubernetes.

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

• Set up and configure the Kubernetes system to begin developing with a serverless architecture.
• Understand the core concepts and principles underpinning serverless environments.
• Operate the toolchains essential for serverless development and integrate them with Kubernetes components.
• Apply their Python programming skills to implement serverless systems.
• Secure enterprise applications deployed through a serverless framework on Kubernetes.
• Leverage modern cloud computing methods to optimise DevOps task processing workflows.

This instructor-led, live training in Auckland (available online or on-site) is intended for engineers who wish to strengthen a Kubernetes cluster beyond its default security configuration.

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

• Understand the vulnerabilities inherent in a default Kubernetes installation.
• Prevent unauthenticated access to the Kubernetes API, databases, and other services.
• Protect a Kubernetes cluster from accidental or malicious access.
• Develop a comprehensive security policy and a set of best practices.

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.

This intensive 7-day programme delivers a comprehensive, hands-on exploration into the design, deployment, and operation of cloud-native applications through modern DevOps methodologies.

Attendees will learn to architect scalable microservices solutions, optimise container environments, and manage production workloads using Kubernetes. The curriculum encompasses advanced deployment techniques, GitOps-driven automation, and observability frameworks designed to guarantee system reliability and performance.

A significant emphasis is placed on addressing real-world operational challenges, such as incident response, failure simulation, and root cause analysis. The programme concludes with the integration of AI-powered tools to streamline troubleshooting and expedite operational decision-making.

Upon completion, participants will possess a solid grasp of how to build, deploy, monitor, and maintain resilient distributed systems within a Kubernetes ecosystem.

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.

This instructor-led, live training in Auckland (online or onsite) is aimed at intermediate to advanced DevOps engineers and system administrators who wish to deploy and manage self-hosted Kubernetes clusters without cloud dependencies.

By the end of this training, participants will be able to: deploy production-ready Kubernetes clusters using kubeadm on bare-metal or virtual machines; configure high-availability control planes and etcd clusters; implement container networking and storage for self-managed environments; set up monitoring and observability using self-hosted solutions.

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.

OpenShift is one of the leading Kubernetes-based platforms for deploying and managing containerized applications in cloud, hybrid and on-premises environments.

This hands-on training teaches participants how to install, administer and troubleshoot OpenShift clusters while applying security, networking and storage best practices. Through practical exercises, participants gain the skills needed to confidently manage production-ready OpenShift environments.

Discover how to develop, deploy, and manage containerised applications with OpenShift, one of the premier Kubernetes-based platforms for cloud-native development. This practical course covers application deployment, containers, networking, CI/CD, and DevOps workflows, providing participants with the skills to build and maintain modern applications in production environments.

This instructor-led, live training in Auckland (available online or on-site) is designed for intermediate-level virtualisation administrators who wish to leverage open-source platforms to migrate away from VMware.

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

• Install and configure KVM, oVirt, and Proxmox VE.
• Migrate virtual workloads from VMware.
• Implement high availability and disaster recovery.
• Optimise performance within open-source virtualisation environments.