Containers and Virtual Machines (VMs) Training in Adelaide

Edge AI is an approach centred on executing machine learning inference near data sources to deliver low-latency, efficient, and scalable processing.

This instructor-led, live training (delivered online or onsite) is designed for intermediate to advanced practitioners looking to deploy, orchestrate, and optimise AI workloads within Kubernetes-based edge environments.

Upon 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 synchronization 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 Customization Options

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

Kubernetes serves as a leading container orchestration platform, extensively utilised for managing distributed applications at scale.

This instructor-led, live training (available online or onsite) is designed for advanced-level practitioners seeking to leverage AI and machine learning techniques to optimise Kubernetes resource usage, refine scheduling decisions, and enhance autoscaling strategies.

Upon completing this program, participants will be equipped to:

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

Course Format

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

Course Customisation Options

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

MLOps on Kubernetes provides a framework for automating the training, validation, packaging, and deployment of machine learning models through containerized pipelines and GitOps workflows.

This instructor-led live training (available online or onsite) is designed for intermediate-level practitioners aiming to construct automated, scalable MLOps pipelines on Kubernetes.

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

• Design end-to-end CI/CD pipelines tailored 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-guided presentations and technical deep dives.
• Hands-on exercises focused on building real-world CI/CD workflows.
• Live-lab practice deploying ML workloads to Kubernetes.

Course Customization Options

• Organizations 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.

Format of the Course

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

Course Customization Options

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

CI/CD for AI represents a structured methodology for automating the packaging, testing, containerisation, 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 able to:

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

Course Format

• 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 organisation requires tailored pipeline workflows or platform integrations, please contact us to customise this course.

This instructor-led, live training in Adelaide (online or onsite) is designed for advanced-level Kubernetes administrators and DevOps engineers looking to enhance their monitoring capabilities for Kubernetes clusters using Prometheus and Grafana.

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

• Set up Prometheus and Grafana for Kubernetes monitoring.
• Monitor key metrics for 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 in Kubernetes environments.

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

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

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

• Build secure and scalable containerised AI services for multi-location environments.
• Deploy AI inference workloads to the cloud, local servers, and edge devices using Docker.
• Integrate orchestration tools to automate distributed AI operations.
• Optimise inference latency, reliability, and resilience across diverse infrastructure.

Format of the Course

• Guided presentations and expert-led discussions.
• Extensive hands-on practice and applied exercises.
• Real-world experimentation in a controlled live-lab setup.

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 deployment, scaling, and management of containerized applications.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level IT professionals who wish to learn the core concepts and components of Kubernetes and use it to manage containerized applications at scale.

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

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

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.

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

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

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

Docker serves as a containerization platform designed to create portable, isolated, and secure deployment environments for AI inference services.

This instructor-led live training, available online or on-site, is tailored for beginner to intermediate technical professionals keen on developing secure, portable AI inference microservices. These services can be deployed consistently across local machines, servers, or cloud virtual machines.

Upon completing this workshop, participants will be equipped to:

• Construct lightweight inference containers suitable for both local and cloud deployment.
• Enhance the security of containerized AI services using industry best practices.
• Establish portable microservice workflows to ensure consistent environments.
• Deploy AI inference endpoints across a variety of infrastructures.

Course Format

• Guided lectures complemented by practical demonstrations.
• Hands-on exercises to reinforce deployment and security techniques.
• Live-lab practice sessions focused on building and running portable inference services.

Course Customization Options

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

In this instructor-led live training in Adelaide (onsite or remote), participants will learn how to deploy a set of sample servers inside containers, then automate, scale, and manage these containerised servers within a Kubernetes cluster. The training advances to more complex topics, walking participants through the processes of securing, networking, and monitoring a Kubernetes cluster.

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

• Set up and run a Docker container.
• Deploy containerised databases and servers.
• Establish a Docker and Kubernetes cluster.
• Utilise Kubernetes to deploy and manage different environments within a single cluster.
• Secure, scale, and monitor a Kubernetes cluster.

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

This instructor-led, live training (available online or onsite) is designed for intermediate-level technical professionals seeking to configure, optimize, and run GPU-enabled AI workloads within Docker containers.

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

• Build and run GPU-enabled containers for training and inference tasks.
• Configure CUDA, drivers, and runtime libraries for containerized AI workflows.
• Optimize resource allocation and isolation for GPU-intensive applications.
• Deploy scalable, containerized 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 Customization Options

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

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

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

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

This instructor-led, live training in Adelaide (online or onsite) is designed for advanced-level platform engineers and DevOps professionals who want 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.
• Utilize Helm charts for efficient service deployment.
• Monitor and maintain the health of microservices in production.
• Apply best practices for security and compliance in a Kubernetes environment.

Master the fundamentals of containers, Kubernetes, and OpenShift through practical, hands-on training designed for developers, DevOps engineers, and IT professionals. Participants will learn to build containerised applications, deploy workloads, manage Kubernetes resources, and utilise OpenShift to streamline modern application delivery across cloud and hybrid environments.

Docker is a containerisation platform utilised to construct reproducible, portable, and scalable environments for machine learning systems.

This instructor-led, live training (available online or onsite) targets intermediate to advanced-level technical professionals looking 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 within 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 serves as a containerisation platform that facilitates consistent, portable, and reproducible environments for artificial intelligence and machine learning workloads.

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

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

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

Format of the Course

• 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 Adelaide (online or onsite) is designed for beginner-level developers who wish to learn the fundamentals of Kubefirst and understand how it simplifies, secures, and accelerates Kubernetes and Swarm cluster management at an enterprise scale.

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

• Set up a Kubefirst development environment.
• Write and run a basic Kubefirst program.
• Annotate code with Kubefirst directives and clauses.
• Use Kubefirst API and libraries.
• Profile and debug Kubefirst programs.

This instructor-led, live training in Adelaide (online or onsite) is designed for intermediate-level developers and DevOps engineers who want to incorporate Minikube into their development workflow.

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

• Set up and manage a local Kubernetes environment using Minikube.
• Gain insight into deploying, managing, and debugging applications on Minikube.
• Integrate Minikube into their continuous integration and deployment pipelines.
• Enhance their development process by leveraging Minikube's advanced features.
• Apply best practices for local Kubernetes development.

This instructor-led, live training in Adelaide (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.

This instructor-led, live training in Adelaide (online or onsite) is aimed at beginner-level to intermediate-level software developers and DevOps professionals who wish 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.
• Understand the basic concepts and architecture of Kubernetes.
• Deploy and manage containers using kubectl and the Minikube dashboard.
• Set up persistent storage and networking solutions for Kubernetes.
• Utilize Minikube for developing, testing, and debugging applications.

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

In this instructor-led, live training in Adelaide (onsite or remote), participants will learn how to create and manage Docker containers, before deploying a sample application inside a container. Participants will also discover how to automate, scale, and manage their containerised applications within a Kubernetes cluster. Finally, the training covers more advanced topics, guiding 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) qualification 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 and Kubernetes training since 2015. With over 360 successfully completed training projects, we have established ourselves as one of the most well-known training providers globally in the field of containerisation.

Since 2019, we have also been assisting our customers in validating their performance in Kubernetes environments by preparing them and encouraging them to sit for 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 knowledge by passing the CKA exam.

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

Format of the Course

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

Course Customization Options

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

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

Upon completion 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-premise to the AKS cloud.
• Integrate Kubernetes with third-party continuous integration (CI) software.
• Ensure high availability and disaster recovery in Kubernetes.

In this instructor-led, live training in Adelaide, participants will learn how to manage Red Hat OpenShift Container Platform.

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

• Create, configure, manage, and troubleshoot OpenShift clusters.
• Deploy containerised applications on-premise, in public cloud environments, or on hosted cloud services.
• Secure OpenShift Container Platform
• Monitor systems and gather metrics.
• Manage storage solutions.

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

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

• Deploy and manage multiple environments under a single Kubernetes cluster
• Secure, scale, and monitor a Kubernetes cluster

Course Format

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

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

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

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

Furthermore, the training emphasises gaining practical experience in Kubernetes application development. We recommend attending, even if you do not currently plan 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 become one of the most recognised training providers globally in the field of containerisation. Since 2019, we have also been assisting our customers in demonstrating their proficiency 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 bespoke 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 course in Adelaide provides participants with an overview of Rancher and demonstrates through hands-on practice how to deploy and manage a Kubernetes cluster with Rancher.

Istio is an open-source service mesh designed to operate on Kubernetes, facilitating secure, observable, and manageable communication between microservices. By utilising Istio’s Envoy-based sidecar proxies, teams can enforce policy controls, secure communications through mTLS, gain comprehensive visibility into traffic patterns, and enhance reliability at scale.

This instructor-led live training (available online or on-site) is tailored for intermediate-level engineers looking to deploy, secure, and manage microservices applications using Istio within a Kubernetes environment.

Upon completion 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 using mutual TLS (mTLS) and Zero Trust principles.
• Monitor, trace, and troubleshoot microservices using Prometheus, Grafana, and Jaeger.
• Integrate Istio with Calico to implement advanced network policies and security measures.

Course Format

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

Course Customization Options

• To arrange a customized training session for this course, please contact us.

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

Audience
This training is designed for individuals who have some familiarity with container technology and Kubernetes concepts but may lack real-world experience. It is grounded in use cases and lessons learned from practical projects, aiming to inspire participants to create and manage even better cloud-native applications.

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

Course Format

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

Course Customisation Options

• To request a tailored training for this course, please contact us to arrange.

This instructor-led, live training in Adelaide (online or onsite) is designed for engineers who want to use Helm to streamline the installation and management of 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 Adelaide (online or onsite) is aimed at DevOps engineers who wish to use Kubernetes and GitLab to automate the DevOps lifecycle.

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

• Automate application builds, tests, and deployments.
• Create an automated build infrastructure.
• Deploy an application to a containerised cloud environment.

This instructor-led, live training in Adelaide (online or onsite) is aimed at Kubernetes practitioners who wish 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 different stages of an application's life cycle: build, deployment and runtime.

This instructor-led live training, available in Adelaide (online or onsite), is aimed at developers and DevOps engineers who wish to utilise a serverless approach for building enterprise applications in Kubernetes.

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

• Set up and configure the Kubernetes system to start developing with a serverless architecture.
• Understand the concepts and principles foundational to serverless environments.
• Operate toolchains necessary for serverless development and integrate them with Kubernetes components.
• Practice their skill in Python programming language and apply it to implement serverless systems.
• Secure enterprise applications that are deployed through a serverless framework on Kubernetes.
• Utilise modern cloud computing methods in optimising DevOps task processing workflows.

This instructor-led live training in Adelaide (online or onsite) is designed for engineers who want to secure their Kubernetes cluster beyond the default security settings.

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

• Identify vulnerabilities inherent in a standard Kubernetes installation.
• Prevent unauthenticated access to the Kubernetes API, database, and other services.
• Safeguard the Kubernetes cluster against both accidental and malicious access.
• Develop a comprehensive security policy and implement best practices.

This instructor-led, live training in Adelaide (online or onsite) is aimed at engineers who wish to advance their knowledge of Docker so as 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.

This seven-day programme offers an immersive, hands-on exploration into the design, deployment, and operation of cloud-native applications using contemporary DevOps methodologies.

Participants will delve into the creation of scalable microservice architectures, optimise container environments, and manage production workloads via Kubernetes. The curriculum encompasses advanced deployment strategies, GitOps-driven automation, and observability techniques to guarantee system reliability and performance.

There is a pronounced emphasis on real-world operational challenges, including incident response, failure simulation, and root cause analysis. The programme culminates with the application of AI-powered tools to aid troubleshooting and expedite operational decision-making.

Upon completion of the training, participants will possess a robust understanding of how to build, deploy, monitor, and maintain resilient distributed systems within a Kubernetes-based environment.

This instructor-led, live training in Adelaide (online or onsite) is designed for engineers who wish to utilise 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 edit Docker registries.

This instructor-led, live training in Adelaide (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 at Adelaide, participants will learn the fundamentals of building microservices using Spring Cloud and Docker. Participant knowledge will be tested through exercises and the step-by-step development of sample microservices.

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

• Understand the core concepts 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 containerised 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 containerized applications with OpenShift, one of the leading Kubernetes-based platforms for cloud-native development. This practical training 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 Adelaide (online or onsite) is aimed at intermediate-level virtualization administrators who wish to use open-source platforms to migrate away from VMware.

By the end 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.
• Optimize performance in open-source virtualization environments.