Kubernetes Training in Taichung

Edge AI is a framework that emphasizes executing machine learning inference near data sources to achieve low-latency, efficient, and scalable processing.

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

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

• Set up lightweight Kubernetes distributions suitable for edge deployments.
• Effectively deploy AI inference tasks across resource-constrained edge devices.
• Address connectivity issues and implement synchronization strategies.
• Optimize performance, storage, and network configurations for practical edge scenarios.

Course Format

• Guided presentations enriched with real-world examples.
• Scenario-based labs and hands-on exercises for practical edge deployment.
• Direct experience working with Kubernetes edge frameworks.

Course Customization Options

• For a customized training program tailored to your specific edge platform requirements, please contact us to arrange.

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

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

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

• Apply AI/ML models to optimize workload scheduling in Kubernetes.
• Use predictive analytics to refine CPU, GPU, and memory allocation.
• Implement intelligent autoscaling through reinforcement learning and metric forecasting.
• Minimize infrastructure costs and latency via automated resource optimization.

Course Format

• Guided technical presentations and in-depth discussions led by the instructor.
• Hands-on lab work using actual Kubernetes clusters.
• Practical exercises that apply AI models to real-world operational scenarios.

Course Customization Options

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

MLOps on Kubernetes is a framework designed to automate the processes of training, validating, packaging, and deploying machine learning models using containerized pipelines and GitOps workflows.

This instructor-led, live training (available both online and onsite) is targeted at intermediate-level practitioners who aim to develop automated, scalable MLOps pipelines on Kubernetes.

Upon completing this training, participants will be able to:

• Design comprehensive CI/CD pipelines for machine learning projects.
• Implement GitOps workflows for the deployment and versioning of models.
• Automate the processes of training, testing, and packaging ML models.
• Integrate monitoring, alerting, and rollback strategies into their pipelines.

Format of the Course

• Instructor-guided presentations and in-depth technical discussions.
• Hands-on exercises that build real-world CI/CD workflows.
• Live-lab practice for deploying ML workloads to Kubernetes.

Course Customization Options

• Organizations can request customized content that aligns with their internal MLOps tools and infrastructure.

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

This instructor-led, live training (available both online and onsite) is targeted at professionals ranging from beginners to intermediates who want to develop reliable ML workflows using Kubeflow.

Upon completing this training, participants will acquire the skills to:

• Navigate the Kubeflow ecosystem and understand its core components.
• Create reproducible workflows with Kubeflow Pipelines.
• Execute scalable training jobs on Kubernetes.
• Efficiently serve machine learning models using Kubeflow Serving.

Course Format

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

Course Customization Options

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

Kubernetes is a scalable platform designed for deploying, serving, and managing machine learning models in production environments.

This instructor-led, live training (available online or on-site) is targeted at intermediate-level professionals who aim to reliably operationalize ML models using Kubernetes.

Upon completing this training, participants will acquire the skills to:

• Containerize and prepare ML models for efficient deployment.
• Serve models using modern inference frameworks.
• Optimize workloads through autoscaling, GPU configuration, and resource tuning.
• Implement model rollout strategies such as A/B testing and canary deployments.

Format of the Course

• A combination of lectures, architectural analysis, and guided discussions.
• Extensive practical exercises involving real-world deployment scenarios.
• Hands-on implementation in a live Kubernetes environment.

Course Customization Options

• If you require this course to be tailored to your specific environment or toolchain, please contact us to discuss customization options.

This instructor-led, live training in Taichung (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.

Kubernetes is an open-source platform designed to automate the deployment, scaling, and management of containerized applications.

This instructor-led, live training (available online or on-site) is targeted at IT professionals ranging from beginners to intermediates who want to master the core concepts and components of Kubernetes and effectively manage containerized applications at scale.

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

• Grasp the architecture and key components of Kubernetes.
• Deploy and manage containers within a Kubernetes cluster.
• Set up networking, storage, and scaling for various workloads.
• Diagnose common issues and adhere to best practices for cluster operations.

Course Format

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

Customization Options for the Course

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

This instructor-led, live training in Taichung (online or onsite) is aimed at 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.

In this instructor-led, live training in Taichung (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.

This instructor-led, live training in Taichung (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:

• Understand the Kubernetes architecture and its components.
• Isolate resources effectively using Namespaces.
• Manage and customize 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.
• Analyze and troubleshoot Kubernetes issues.
• Deploy resources efficiently using Helm Charts.

This instructor-led, live training in Taichung (online or onsite) is aimed at advanced-level platform engineers and DevOps professionals who wish 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.

DO180 is an introductory course on containers, Kubernetes fundamentals, and the Red Hat OpenShift platform, focusing on hands-on skills development.

This instructor-led, live training (available online or onsite) is designed for technical professionals at beginner to intermediate levels who are interested in learning container workflows, Kubernetes basics, and how to deploy and manage applications on OpenShift.

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

• Create and manage container images and registries using best practices for reproducibility and security.
• Deploy and manage Kubernetes objects such as pods, deployments, and services within OpenShift.
• Leverage OpenShift features like routes, build configurations, and the web console to streamline application delivery processes.
• Implement persistent storage, configuration management, and secrets handling for stateful workloads.
• Apply fundamental security measures, role-based access control (RBAC), and monitoring practices to ensure healthy clusters and applications.

Course Format

• Interactive lectures and discussions.
• Hands-on labs in a live OpenShift environment every day.
• Scenario-driven exercises and troubleshooting workshops.

Customization Options for the Course

• To request a customized training program, please contact us to arrange.

This instructor-led, live training in Taichung (online or onsite) is aimed at beginner-level developers who wish to learn the basics of Kubefirst and how it simplifies, secures, and accelerates Kubernetes and Swarm cluster management at 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 Taichung (online or onsite) is aimed at intermediate-level developers and DevOps engineers who wish to use Minikube as a 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 Taichung (online or onsite) is aimed at beginner to intermediate-level developers, system administrators, and DevOps engineers who wish to understand Kubernetes and cloud-native principles.

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

• Set up a development environment that includes Kubernetes.
• Create a microservices application using Kubernetes.
• Deploy, manage, and scale applications in Kubernetes.
• Debug common issues in Kubernetes environments.

This instructor-led, live training in Taichung (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 Taichung (onsite or remote), participants will learn how to create and manage Docker containers, then deploy a sample application inside a container. Participants will also learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. Finally, the training goes on to more advanced topics, walking participants through the process of securing, scaling and monitoring a Kubernetes cluster.

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

• Set up and run a Docker container.
• Deploy a containerized server and web application.
• Build and manage Docker images.
• Set up a Docker and Kubernetes cluster.
• Use Kubernetes to deploy and manage a clustered web application.
• Secure, scale and monitor a Kubernetes cluster.

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

Kubernetes has become a leading platform for container orchestration in recent years.

NobleProg has been providing Docker and Kubernetes training since 2015. With over 360 successfully completed training projects, we have established ourselves as one of the most recognized training companies globally in the field of containerization.

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

This instructor-led, live training (available online or on-site) 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. We recommend participating in it even if you do not plan to take the CKA exam.

Course Format

• Interactive lectures and discussions.
• Plenty of exercises and hands-on practice.
• Practical implementation in a live-lab environment.

Course Customization Options

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

In this instructor-led, live training in Taichung (online or onsite), 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 containerized (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.

The goal of this hands-on course is to equip participants with all the essential tools to handle the practical aspects of Docker and Kubernetes. This ensures they have the necessary skills for effective program management.

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

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

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

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

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

• Create and configure an OpenShift setup.
• Quickly deploy applications on-premise, in public cloud or on a hosted cloud.

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

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

• Utilize Kubernetes to deploy and manage various environments within the same cluster
• Ensure security, scalability, and monitoring of a Kubernetes cluster

Format of the Course

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

Course Customization Options

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

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

This instructor-led, live training (available online or on-site) 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. We highly recommend participating in this training even if you do not plan to take the CKAD exam.

NobleProg has been offering Docker & Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most recognized training companies worldwide in the field of containerization. Since 2019, we have also been helping our clients confirm their proficiency in k8s environments by preparing them and encouraging them to pass the CKA and CKAD exams.

Format of the Course

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

Course Customization Options

• To request a customized training for this course, please contact us to arrange.
• To learn more about CKAD, visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

This instructor-led, live course in Taichung 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 run on Kubernetes, providing secure, observable, and manageable connectivity between microservices. By utilizing Istio’s Envoy-based sidecar proxies, teams can enforce policies, ensure secure communications with mutual TLS (mTLS), achieve deep observability into traffic, and enhance reliability at scale.

This instructor-led, live training (available online or onsite) is targeted at intermediate-level engineers who aim 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 such as 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 with tools like Prometheus, Grafana, and Jaeger.
• Integrate Istio with Calico for advanced network policies and security measures.

Format of the Course

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

Course Customization Options

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

EKS is a self-managed Kubernetes-as-a-service offering from AWS. It is fully scalable and customizable, allowing a Kubernetes deployment to either mimic or integrate with an existing on-premise Kubernetes setup.

In this instructor-led, live training, participants will learn how to set up and manage a production-scale container environment using Kubernetes on EKS.

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

• Configure and manage Kubernetes on EKS
• Migrate an existing Kubernetes environment from on-premise to the AWS cloud
• Integrate Kubernetes with third-party continuous integration (CI) software
• Ensure high availability and disaster recovery in Kubernetes
• Understand and adopt the tools available for efficient EKS management

Audience

• Developers
• System Administrators
• DevOps Engineers

Format of the Course

• Part lecture, part discussion, exercises, and extensive hands-on practice in a live-lab environment.

Note

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

The development of microservices and containers over recent years has profoundly transformed the way we design, develop, deploy, and manage software. Contemporary applications must be optimized for scalability, elasticity, resilience, and adaptability. These evolving demands have necessitated a new set of architectural patterns and practices. In this training, we explore methods to identify, comprehend, and adapt to these emerging requirements.

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

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

Format of the Course

• Interactive lectures and discussions
• Extensive exercises and hands-on practice
• Practical implementation in a live-lab environment

Course Customization Options

• For customized training tailored to your specific needs, please contact us to arrange.

This instructor-led, live training in Taichung (online or onsite) is aimed at engineers who wish to evaluate, select and deploy the most appropriate Kubernetes solution for their specific situation.

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

• Install and configure a Kubernetes cluster on premise and in the cloud.
• Evaluate different cloud-hosted Kubernetes solutions and understand the advantages over an self-hosted approach.
• Compare different tools for testing, managing, and monitoring a Kubernetes cluster.

This instructor-led, live training in Taichung (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 Taichung (online or onsite) is aimed at system administrators and developers who wish to use Prometheus to monitor Kubernetes clusters.

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

• Install and configure Prometheus.
• Monitor dynamic cloud environments.
• Gain better insight into their Kubernetes clusters.
• Set up alerts that are precise and insightful.

This instructor-led, live training in Taichung (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 containerized cloud environment.

This instructor-led, live training in Taichung (online or onsite) is aimed at engineers who wish to optimize networking for Kubernetes clusters.

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

• Install and configure Calico.
• Understand how Calico differs from traditional overlay networks.
• Understand how Calico combines internet routing protocols with consensus-based data stores.
• Use Calico to create a container networking solution for Kubernetes clusters.
• Use Calico to provide network policy for Kubernetes.

In this instructor-led, live training in Taichung, participants will learn how to set up and manage a production-scale container environment using Kubernetes on Google Cloud. 

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

• Configure and manage Kubernetes on Google Cloud.
• Deploy, manage and scale a Kubernetes cluster.
• Deploy containerized (Docker) applications on Google Cloud.
• Migrate an existing Kubernetes environment from on-premise to Google 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 Taichung (onsite or remote), participants will learn how to how to install, configure, and manage OKD on-premise or in the cloud.

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

• Create, configure, manage, and troubleshoot an OKD cluster.
• Secure OKD.
• Deploy containerized applications on OKD.
• Monitor the performance of an application running in OKD.
• Manage data storage.
• Quickly deploy applications on-premise or on a public cloud such as AWS.

This instructor-led, live training in Taichung (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 Taichung (online or onsite) is aimed 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:

• Setup and configure the Kubernetes system to start developing with a serverless architecture.
• Understand the concepts and principles foundational to serverless environments.
• Operate toolchains necessary to serverless development and integrate it 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.
• Utilize modern cloud computing methods in optimizing DevOps task processing workflows.

This instructor-led, live training in Taichung (online or onsite) is aimed at 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 that are 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.
• Put together a comprehensive security policy and set of best practices.

This instructor-led, live training in (online or onsite) is aimed at engineers who wish to evaluate each of these services to make an informed decisions about which to deploy within their organization.

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

• Set up a development environment that includes all needed libraries, packages and frameworks needed to start developing.
• Set up, configure and deploy a series of demo containers using a number of different approaches.
• Understand the architectural and design differences among different Docker/Kubernetes solutions within AWS.
• Automate the deployment of Docker containers.
• Set up a continuous integration and deployment pipeline.
• Integrate Docker and Kubernetes into an existing continuous integration system.

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 Taichung (online or onsite) is aimed at DevOps engineers and developers who wish to use Fedora CoreOS to reduce the maintenance and upgrade costs of running  containerized applications on Kubernetes.

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

• Install and configure Fedora CoreOS.
• Set up Kubernetes cluster on Fedora CoreOS.
• Run and manage Kubernetes deployments on Fedora CoreOS.
• Automatically update Fedora OS with the latest OS improvements, bug fixes, and security updates.

This instructor-led, live training in Taichung (online or onsite) is aimed at DevOps engineers who wish to set up, deploy and manage a Git-based software deployment workflow for their Kubernetes applications.

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

• Install and configure Spinnaker and Terraform.
• Understand the benefits of GitOps over traditional CI/CD and Infrastructure-as-Code (IAC).
• Move away from maintaining scripts. Configure and execute well-defined deployment process.
• Apply best practices for cloud-native deployment, management, and monitoring.
• Recover deployments from partial failures without manual intervention.
• Create a GitOps strategy for application development.

This instructor-led, live training Taichung (online or onsite) is aimed at DevOps engineers and developers who wish to use Java and Kubernetes (K8s) to create, build, test, debug and deploy high-performance and scalable applications.

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

• Set up the necessary development environment to build Java applications.
• Understand the features and architecture of Kubernetes.
• Learn about the key concepts and tools for DevOps.
• Get a refresher on Java programming fundamentals.
• Containerize Java microservices using Docker.
• Build, scale, and deploy Java applications on Kubernetes.

Kubernetes is an open-source platform designed to automate the development stages of containerized applications. Design patterns offer repeatable solutions to common software design challenges. Kubernetes extensions are used to configure and support Kubernetes clusters. By leveraging Kubernetes design patterns and extensions, users can implement CI/CD practices while ensuring the scalability and flexibility of their software applications.

This instructor-led, live training (available online or on-site) is targeted at developers and DevOps engineers who aim to utilize Kubernetes design patterns and extensions to build enterprise applications on Kubernetes clusters.

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

• Set up a Kubernetes cluster and configure the required DevOps tools.
• Grasp the basics of software design patterns and Kubernetes extensions.
• Use Kubernetes extensions and design patterns when working with the Kubernetes API.
• Create customized Kubernetes resources and implement dynamic controllers in a cluster.
• Manage and secure any Kubernetes environment using Kubernetes plugins.
• Integrate DevOps networking models into existing and new Kubernetes projects.

Format of the Course

• Interactive lecture and discussion sessions.
• Ample exercises and hands-on practice.
• Practical 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 Taichung (online or onsite) is aimed at DevOps engineers and developers who wish to deploy and manage OpenStack services on cloud infrastructures using Kubernetes.

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

• Deploy, configure, and manage MOS and its components.
• Access OpenStack APIs.
• Perform common OpenStack operations tasks (backup, restore, etc.).
• Upgrade OpenStack deployments.

This instructor-led, live training in Taichung (online or onsite) is aimed at developers and DevOps engineers who wish to leverage Tekton Pipelines for supporting complex software development workflows and building automated CI/CD pipelines.

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

• Install and configure Tekton Pipelines and other foundational Tekton components.
• Design and create the building blocks of pipelines for software development in Tekton.
• Automate existing pipelines and development processes using Tekton framework concepts and principles.
• Run and manage Tekton Pipelines for various workload types across multiple platforms.
• Implement CI/CD systems based on the Tekton framework to enhance future software development projects.