Containers and Virtual Machines (VMs) Training in Kuala Lumpur

Edge AI focuses on performing machine learning inference close to the source of data to deliver low-latency, efficient, and scalable processing capabilities.

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

Upon completing this course, participants will be able to:

• Set up lightweight Kubernetes distributions suitable for edge deployments.
• Effectively deploy AI inference workloads across resource-constrained edge nodes.
• Address connectivity challenges and implement synchronization patterns.
• Optimize performance, storage, and networking for real-world edge scenarios.

Course Format

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

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

Upon completing this program, participants will be able to:

• Utilize AI/ML models to enhance workload scheduling decisions in Kubernetes.
• Implement intelligent autoscaling using reinforcement learning and metric forecasting.
• Lower infrastructure costs and reduce latency through automated resource optimization.

Course Format

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

Course Customization Options

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

MLOps on Kubernetes serves as a framework that automates the training, validation, packaging, and deployment of machine learning models through containerized pipelines and GitOps workflows.

This instructor-led live training, available both online and onsite, is designed for intermediate-level practitioners looking to construct automated, scalable MLOps pipelines on Kubernetes.

Upon completing this training, participants will gain the ability to:

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

Course Format

• Instructor-guided presentations alongside technical deep dives.
• Practical exercises focused on building real-world CI/CD workflows.
• Live-lab sessions for deploying ML workloads to Kubernetes.

Customization Options

• Organizations can request tailored content that aligns 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 systematic methodology for automating the packaging, testing, containerization, and deployment of machine learning models through continuous integration and delivery pipelines.

This instructor-led live training, available in online or onsite formats, targets intermediate-level professionals seeking to automate end-to-end AI model delivery workflows leveraging Docker and CI/CD platforms.

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

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

Course Format

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

Course Customization Options

• Should your organization require customized pipeline workflows or specific platform integrations, please contact us to tailor this course to your needs.

This instructor-led, live training in Kuala Lumpur (online or onsite) is aimed at advanced-level Kubernetes administrators and DevOps engineers who wish to enhance their monitoring skills for Kubernetes clusters using Prometheus and Grafana.

By the end 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 visualize 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 infrastructures using standardized, container-driven workflows.

This instructor-led live training, available online or onsite, is designed for advanced professionals seeking to design and implement distributed AI inference systems within heterogeneous environments.

Upon completing this training, participants will be equipped to:

• Construct secure and scalable containerized AI services for multi-site operations.
• Deploy AI inference workloads across cloud platforms, local servers, and edge devices utilizing Docker.
• Integrate orchestration tools to automate distributed AI operations.
• Enhance inference latency, reliability, and resilience across diverse infrastructure setups.

Course Format

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

Customization Options

• To tailor this course to your organization’s specific infrastructure or use cases, please contact us to arrange customization.

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

This instructor-led, live training (available online or onsite) is tailored for beginner to intermediate IT professionals who aim to grasp the core concepts and components of Kubernetes and utilise 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 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 Kuala Lumpur (online or onsite) 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 command-line tools.
• Gain hands-on experience covering basic to advanced Kubernetes operations and administration.

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

This instructor-led, live training (available online or onsite) is intended for beginner to intermediate-level technical professionals who aim to build 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 able to:

• Create lightweight inference containers suitable for local and cloud deployment.
• Secure containerized AI services using best-practice techniques.
• Implement portable microservice workflows to ensure 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 Customization Options

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

In this instructor-led live training at Kuala Lumpur (onsite or remote), participants will learn how to deploy a collection of sample servers inside containers, then automate, scale, and manage their containerized servers within a Kubernetes cluster. The training goes on to more advanced topics, walking participants through the process of securing, networking and monitoring a Kubernetes cluster.

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

• Set up and run a Docker container.
• Deploy containerized databases and servers.
• Set up a Docker and Kubernetes cluster.
• Use Kubernetes to deploy and manage different environments under the same cluster.
• Secure, scale and monitor a Kubernetes cluster.

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

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

Upon completing 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.

Format of the Course

• 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 Kuala Lumpur (online or onsite) is aimed at intermediate-level professionals who wish to effectively deploy, manage, and scale containerized applications using Kubernetes.

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

• Grasp the Kubernetes architecture and its key components.
• Effectively isolate resources using Namespaces.
• Manage and customize workloads through Deployments, StatefulSets, and DaemonSets.
• Define computational resources by setting Requests and Limits.
• Utilize Jobs and CronJobs for scheduled tasks.
• Gain a clear understanding of Services and DNS within Kubernetes.
• Expose applications via Ingress.
• Manage ConfigMaps, Secrets, and Persistent Volumes.
• Scale and upgrade Kubernetes clusters employing advanced strategies.
• Analyze and troubleshoot issues arising within Kubernetes.
• Deploy resources efficiently using Helm Charts.

This instructor-led live training in Kuala Lumpur (online or onsite) is tailored for intermediate to advanced 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.

Upon completing this training, participants will be able to:

• Comprehend and implement microservices architecture.
• Deploy and manage containerized applications using Docker and Kubernetes.
• Establish and optimize CI/CD pipelines for automated deployments.
• Apply best practices regarding security, monitoring, and observability.

This instructor-led, live training in Kuala Lumpur (online or onsite) is designed for advanced-level platform engineers and DevOps professionals aiming to master application scaling through microservices and Kubernetes.

Upon completing 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.

This training provides a comprehensive introduction to containers, the fundamentals of Kubernetes, and core concepts of the OpenShift platform, with a strong emphasis on practical, hands-on skills.

Designed for beginner to intermediate-level technical professionals, this instructor-led live training (available online or onsite) covers essential container workflows, Kubernetes primitives, and the methods required to deploy and manage applications on OpenShift.

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

• Construct and manage container images and registries, adhering to best practices for security and reproducibility.
• Deploy and oversee Kubernetes objects such as pods, deployments, and services within the OpenShift environment.
• Leverage OpenShift features like routes, buildconfigs, and the web console to accelerate application delivery.
• Implement persistent storage, configuration management, and secrets handling for stateful workloads.
• Apply fundamental security measures, RBAC, and monitoring practices to ensure cluster health and application stability.

Course Format

• Interactive lectures and discussions.
• Daily hands-on labs conducted in a live OpenShift environment.
• Scenario-based exercises and troubleshooting workshops.

Customization Options

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

Docker serves as a containerization platform designed to create reproducible, portable, and scalable environments for machine learning systems.

This instructor-led training session, available online or on-site, targets intermediate to advanced technical professionals seeking to containerize and operationalise complete ML pipelines using Docker.

Upon completing this training, participants will gain the ability to:

• Containerise ML training, validation, and inference workloads.
• Design and orchestrate end-to-end ML pipelines utilizing Docker and complementary tools.
• Implement versioning, reproducibility, and CI/CD practices for ML components.
• Deploy, monitor, and scale ML services within containerised environments.

Course Format

• Interactive lectures complemented by practical demonstrations.
• Hands-on exercises centred on constructing real-world ML pipeline components.
• Live-lab implementation of end-to-end containerised workflows.

Course Customization Options

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

Docker serves as a containerization platform that provides consistent, portable, and reproducible environments for artificial intelligence and machine learning workloads.

This instructor-led live training, available either 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 completing this course, participants will be able to:

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

Course Format

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

Customization Options

• To tailor this training to your organization's specific environment, please contact us to arrange.

This instructor-led, live training in Kuala Lumpur (online or on-site) is designed for beginner-level developers who wish to learn the basics of Kubefirst and 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 Kuala Lumpur (online or on-site) targets intermediate-level developers and DevOps engineers who wish to use Minikube as part of their development workflow.

By the end 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.
• Optimize their development process using Minikube's advanced features.
• Apply best practices for local Kubernetes development.

This instructor-led, live training in Kuala Lumpur (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 Kuala Lumpur (online or in-person) is designed for beginner to intermediate software developers and DevOps professionals looking to learn how to set up and manage a local Kubernetes environment using Minikube.

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

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

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

In this instructor-led live training in Kuala Lumpur (onsite or remote), participants will learn how to create and manage Docker containers and 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 progresses to 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 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.

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

Kubernetes has emerged as the premier 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 leading training providers globally in the field of containerization.

Since 2019, we have also supported our clients in validating their proficiency in Kubernetes environments by preparing them and encouraging them to take the CKA and CKAD exams.

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.

Additionally, the training focuses on gaining practical experience in Kubernetes Administration; therefore, we recommend participation even if you do not intend to sit for the CKA exam.

Course Format

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

Course Customization Options

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

In this instructor-led live training in Kuala Lumpur (online or on-site), participants will learn how to set up and manage a production-scale 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-premise to 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 Kuala Lumpur, 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 OpenShift Container Platform
• Monitor and gather metrics.
• Manage storage.

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

Upon completing this training, participants will be capable of:

• Utilizing Kubernetes to deploy and manage various environments within a single cluster
• Securing, scaling, and monitoring a Kubernetes cluster

Course Format

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

Customization Options

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

The Certified Kubernetes Application Developer (CKAD) programme has been established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), which hosts Kubernetes.

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

Additionally, the training focuses on gaining practical experience in Kubernetes application development. Therefore, we recommend participating even if you do not intend to take 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 most renowned training companies globally in the field of containerization. Since 2019, we have also assisted our customers in validating their performance in the k8s environment by preparing them and encouraging them to pass the CKA and CKAD exams.

Course Format

• Interactive lecture and discussion.
• Ample 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 CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

This instructor-led, live course in Kuala Lumpur 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, delivering secure, observable, and manageable connections between microservices. By utilising Istio’s Envoy-based sidecar proxies, teams can enforce policies, secure communications via mTLS, gain deep visibility into traffic patterns, and enhance reliability at scale.

This instructor-led live training (available online or onsite) targets intermediate-level engineers who want to deploy, secure, and manage microservices applications using Istio on Kubernetes.

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 for advanced network policies and security.

Course Format

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

Course Customisation Options

• To request a tailored training session for this course, please get in touch with us to arrange.

In recent years, the advancement of microservices and container technologies has fundamentally transformed how software is designed, developed, deployed, and operated. Contemporary applications demand optimization for scalability, elasticity, fault tolerance, and adaptability. To meet these evolving needs, modern architectural approaches necessitate a distinct set of patterns and practices. This training explores strategies to identify, comprehend, and adapt to these new requirements.

Audience
This course is designed for professionals who possess a foundational understanding of container technology and Kubernetes concepts but may lack practical, real-world experience. Drawing on use cases and lessons learned from actual projects, the content aims to inspire participants to design and manage superior cloud-native applications.

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

Format of the Course

• Interactive lectures and discussions
• Extensive exercises and practical sessions
• Hands-on implementation within a live laboratory environment

Course Customization Options

• To request tailored training for this course, please get in touch with us to make arrangements.

This instructor-led, live training in Kuala Lumpur (online or onsite) is designed for engineers who want to use Helm to simplify the installation and management of Kubernetes applications.

Upon completion 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 Kuala Lumpur (online or onsite) is designed for DevOps engineers who wish to utilise 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 Kuala Lumpur (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 in Kuala Lumpur (online or on-site) is targeted at developers and DevOps engineers who wish to utilize 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 skills in the Python programming language and apply them to implement serverless systems.
• Secure enterprise applications that are deployed through a serverless framework on Kubernetes.
• Utilize modern cloud computing methods in optimizing DevOps task processing workflows.

This instructor-led live training in Kuala Lumpur (online or onsite) is designed for engineers who wish to secure a Kubernetes cluster beyond the default security settings.

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

• Understand the vulnerabilities exposed by a default Kubernetes installation.
• Prevent unauthenticated access to the Kubernetes API, database, 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 Kuala Lumpur (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 manager 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 7-day programme provides a comprehensive, hands-on journey into designing, deploying, and operating cloud-native applications using modern DevOps practices.

Participants will explore how to design scalable microservices architectures, optimise container environments, and manage production workloads using Kubernetes. The course covers advanced deployment strategies, GitOps-based automation, and observability practices to ensure system reliability and performance.

A strong focus is placed on real-world operational challenges, including incident response, failure simulation, and root cause analysis. The programme concludes with the use of AI-powered tools to support troubleshooting and accelerate operational decision-making.

By the end of the training, participants will have a clear understanding of how to build, deploy, monitor, and maintain resilient distributed systems in a Kubernetes-based environment.

This instructor-led, live training in Kuala Lumpur (online or onsite) is designed for engineers who want to use Docker to deploy and manage software as containers instead of as traditional standalone software.

Upon completing this training, participants will be capable of:

• Installing and configuring Docker.
• Understanding and implementing software containerization.
• Managing Docker-based applications.
• Networking distinct Docker applications and systems.
• Understanding and editing Docker registries.

This instructor-led, live training in Kuala Lumpur (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 held in Kuala Lumpur, participants will learn the essentials of building microservices using Spring Cloud and Docker. Knowledge is assessed through practical exercises and the incremental development of sample microservices.

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

• Understand the fundamentals of microservices.
• Use Docker to build containers for microservice applications.
• Build and deploy containerized 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 Container Platform v4 is an enterprise-grade Kubernetes platform created by Red Hat, built to automate the deployment, scaling, and management of containerised applications.

This instructor-led, live training (delivered online or onsite) is tailored for system administrators and DevOps engineers who want to deploy, manage, and operate OpenShift clusters in production environments.

The course offers a practical, hands-on approach to installing and managing OpenShift 4 clusters, working with Operators, securing workloads, and running applications at scale.

In this instructor-led, live training in Kuala Lumpur (online or onsite), participants will learn how to create, update, and maintain applications using OpenShift Container Platform.

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 (OKD, OpenShift Container Platform, Red Hat OpenShift, etc.).
• Automate the software delivery pipeline.
• Apply DevOps principles to deliver software continuously.

This instructor-led, live training in Kuala Lumpur (online or on-site) is tailored for intermediate-level virtualization administrators who wish to utilize 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.