Whether conducted online or onsite, instructor-led live training for Containers and Virtual Machines (VMs) covers fundamental and advanced concepts through practical, hands-on exercises.
Containers and Virtual Machines (VMs) training is offered in two formats: "online live training" and "onsite live training." Online live training (also referred to as "remote live training") is delivered via an interactive remote desktop connection. Onsite live training can be conducted locally at the client’s premises in Bhutan or at NobleProg’s corporate training centers in Bhutan.
NobleProg -- Your Trusted Local Training Provider
Bhutan, Thimphu - Classroom
near Le Méridien , Chorten Lam, Thimphu, Bhutan, 11001
Set in Thimphu, this classroom is well located in Chorten Lam with all amenities and WiFi.
For Sales Enquires and Meetings
All our centres have batches running on weekdays and weekends hence, please note that, in most cases, usually we are not able to organise ad hoc sales meetings, especially on our classrooms as they are all occupied with ongoing training sessions . Please contact us by e-mail or phone at least one day earlier to make an appointment with one of our consultants at our corporate offices.
Bhutan, Paro - Classroom
near Le Méridien Riverfront, thimphu hwy, Shaba, Paro, Bhutan, 12001
Set in Paro, this classroom is well located near Paro-Thimphu Highway around 4 km from the airport, and 7 km from Rinpung Dzong, and possess all amenities and WiFi.
For Sales Enquires and Meetings
All our centres have batches running on weekdays and weekends hence, please note that, in most cases, usually we are not able to organise ad hoc sales meetings, especially on our classrooms as they are all occupied with ongoing training sessions . Please contact us by e-mail or phone at least one day earlier to make an appointment with one of our consultants at our corporate offices.
Edge AI is a paradigm focused on running machine learning inference close to data sources to achieve low-latency, efficient, and scalable processing.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level practitioners who wish to deploy, orchestrate, and optimize AI workloads on Kubernetes-based edge environments.
By completing this course, participants will be able to:
Set up lightweight Kubernetes distributions for edge deployments.
Deploy AI inference workloads effectively across constrained edge nodes.
Manage connectivity challenges and synchronization patterns.
Optimize 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 widely adopted container orchestration platform, essential 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 equipped to:
Utilize AI/ML models to enhance workload scheduling decisions within Kubernetes.
Employ predictive analytics to optimize CPU, GPU, and memory allocation.
Implement intelligent autoscaling mechanisms using reinforcement learning and metric forecasting.
Lower infrastructure costs and latency through automated resource optimization.
Course Format
Instructor-led technical presentations combined with in-depth discussions.
Hands-on lab sessions utilizing real Kubernetes clusters.
Practical exercises involving the application of AI models to real-world operational scenarios.
Customization Options
To tailor this course to your specific platform setup or operational needs, please reach out to us for customization details.
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, targets intermediate-level practitioners looking to build automated, scalable MLOps pipelines on Kubernetes.
Upon completion of this training, participants will be able to:
Design end-to-end CI/CD pipelines for machine learning.
Implement GitOps workflows for model deployment and versioning.
Automate the training, testing, and packaging of ML models.
Integrate monitoring, alerting, and rollback strategies.
Course Format
Instructor-guided presentations and technical deep dives.
Hands-on exercises focused on building real-world CI/CD workflows.
Live-lab practice for deploying ML workloads to Kubernetes.
Customization Options
Organizations can 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:
Explore the Kubeflow ecosystem and its core components.
Develop reproducible workflows using Kubeflow Pipelines.
Execute scalable training jobs on Kubernetes.
Efficiently serve machine learning models via Kubeflow Serving.
Course Format
Guided presentations coupled with collaborative discussions.
Hands-on labs utilizing real 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.
CI/CD for AI represents a systematic methodology for automating the packaging, testing, containerization, and deployment of models through continuous integration and continuous delivery pipelines.
This instructor-led live training, available both online and onsite, is designed for intermediate-level professionals aiming to automate end-to-end AI model delivery workflows leveraging Docker and CI/CD platforms.
Upon completion of the training, participants will be equipped to:
Develop automated pipelines for constructing and validating AI model containers.
Establish version control and reproducibility mechanisms throughout the model lifecycle.
Incorporate automated deployment strategies for AI services.
Apply CI/CD best practices specifically adapted for machine learning operations (MLOps).
Course Format
Instructor-guided presentations and technical discussions.
Practical labs and hands-on implementation exercises.
Realistic CI/CD workflow simulations within a controlled environment.
Course Customization Options
Should your organization require tailored pipeline workflows or specific platform integrations, please reach out to us to customize this course.
This instructor-led, live training in Bhutan (online or onsite) is designed for advanced-level Kubernetes administrators and DevOps engineers who wish to enhance their Kubernetes cluster monitoring skills using Prometheus and Grafana.
Upon completion of this training, participants will be able to:
Configure Prometheus and Grafana for Kubernetes monitoring.
Track key metrics for pods, nodes, and services.
Build dynamic dashboards to visualize cluster health and performance.
Deploy alerting strategies for proactive issue resolution.
Apply best practices for scaling monitoring solutions within Kubernetes environments.
Hybrid AI deployment involves executing AI inference across cloud, on-premise, and edge environments through unified container-based workflows.
This instructor-led, live training—available either online or onsite—is designed for advanced-level professionals aiming to design and deploy distributed AI inference systems within heterogeneous environments.
Upon completing this training, participants will be capable of:
Developing secure and scalable containerized AI services for multi-location settings.
Deploying AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
Integrating orchestration tools to automate distributed AI operations.
Enhancing inference latency, reliability, and resilience across diverse infrastructure.
Course Format
Guided presentations accompanied by expert-led discussions.
Extensive hands-on practice and applied exercises.
Real-world experimentation within a controlled live-lab environment.
Customization Options
For tailored adjustments to align this course with your organization’s infrastructure or specific use cases, please contact us to customize the training.
Kubernetes is an open-source platform designed for automating the deployment, scaling, and management of containerized applications.
This instructor-led live training, available online or onsite, targets beginner to intermediate IT professionals seeking to grasp the core concepts and components of Kubernetes and leverage them to manage containerized applications at scale.
Upon completing this training, participants will be able to:
Grasp the architecture and key components of Kubernetes.
Deploy and manage containers within a Kubernetes cluster.
Configure networking, storage, and scaling for their workloads.
Troubleshoot common issues and adhere to best practices for cluster operations.
Format of the Course
Interactive lectures and discussions.
Extensive exercises and practice sessions.
Hands-on implementation in a live laboratory environment.
Course Customization Options
For customized training on this course, please contact us to arrange it.
This instructor-led live training, conducted in Bhutan (via online or onsite modes), is designed for DevOps engineers and developers keen on utilising Kubernetes to build, deploy, and manage containers and cluster components within a secure and scalable framework.
By the conclusion of this training, participants will be able to:
Understand the architecture, core concepts, and components of the Kubernetes ecosystem.
Set up, install, and configure a Kubernetes cluster for container orchestration.
Learn how to execute Kubernetes operations using command-line tools.
Acquire hands-on experience spanning 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 onsite) targets beginner to intermediate technical professionals aiming to develop secure, portable AI inference microservices that can be consistently deployed across local machines, servers, or cloud VMs.
Upon completion of this workshop, participants will be able to:
Create lightweight inference containers suitable for both local and cloud deployment.
Enhance the security of containerized AI services through best-practice techniques.
Establish portable microservice workflows to ensure consistent environments.
Deploy AI inference endpoints across various infrastructures.
Course Format
Guided lectures complemented by practical demonstrations.
Hands-on exercises to reinforce deployment and security methodologies.
Live-lab practice for constructing and executing portable inference services.
Course Customization Options
To tailor this training to your specific infrastructure or AI tooling stack, please contact us to arrange.
In this instructor-led, live training in Bhutan (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.
Leveraging GPU acceleration is critical for executing high-performance deep learning tasks in a scalable and efficient way.
This instructor-led live training, available both online and onsite, is designed for intermediate-level technical professionals who want to configure, optimize, and deploy GPU-enabled AI workloads within Docker containers.
By the end of this course, participants will be equipped to:
Construct and execute GPU-enabled containers for model training and inference.
Set up CUDA, drivers, and runtime libraries to support containerized AI workflows.
Optimize resource allocation and isolation for applications that are intensive on GPU resources.
Deploy scalable, containerized deep learning services in production settings.
Course Delivery Format
Interactive teaching reinforced with real-world demonstrations.
Practical exercises focused on GPU-enabled development.
Hands-on implementation within a live laboratory environment.
Customization Opportunities
For bespoke training tailored to your specific infrastructure or GPU stack, please get in touch to make arrangements.
This instructor-led, live training in Bhutan (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 various components.
Effectively isolate resources 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 the Kubernetes ecosystem.
Expose applications using Ingress.
Manage ConfigMaps, Secrets, and Persistent Volumes.
Scale and upgrade Kubernetes clusters using advanced strategies.
This instructor-led, live training in Bhutan (online or onsite) is designed for intermediate to advanced developers, DevOps professionals, and architects who wish to design, deploy, and manage resilient applications using microservices, containers, and continuous integration/continuous deployment (CI/CD) pipelines.
Upon completion of this training, participants will be able to:
Understand 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 for security, monitoring, and observability.
This instructor-led, live training in Bhutan (online or onsite) is designed for advanced-level platform engineers and DevOps professionals aiming to master application scaling through microservices and Kubernetes.
Upon completion of this training, participants will be able to:
Design and implement scalable microservices architectures.
Deploy and manage applications on Kubernetes clusters.
Leverage Helm charts for efficient service deployment.
Monitor and maintain the health of microservices in production environments.
Apply security and compliance best practices within a Kubernetes environment.
Learn the fundamentals of containers, Kubernetes and OpenShift in a practical, hands-on training designed for developers, DevOps engineers and IT professionals. Participants will learn how to build containerized applications, deploy workloads, manage Kubernetes resources and use OpenShift to streamline modern application delivery in cloud and hybrid environments.
Docker serves as a containerization platform designed to create reproducible, portable, and scalable environments for machine learning systems.
This instructor-led live training, available both online and onsite, targets intermediate to advanced technical professionals who aim to containerize and operationalize comprehensive ML pipelines using Docker.
After completing this training, participants will be equipped to:
Containerize 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 processes for ML components.
Deploy, monitor, and scale ML services within containerized environments.
Format of the Course
Interactive lectures accompanied by practical demonstrations.
Hands-on exercises centered on constructing real-world ML pipeline components.
Live-lab implementation for end-to-end containerized workflows.
Course Customization Options
For customized training tailored to specific ML infrastructure requirements, please contact us to discuss available options.
Docker serves as a containerization platform that allows for the creation of consistent, portable, and reproducible environments specifically suited for AI and machine learning workloads.
This live training, led by an instructor and available either online or onsite, is designed for intermediate-level professionals aiming to package ML codebases, dependencies, and models using Docker to establish reliable workflows from development to production.
Upon successful completion of this course, participants will gain the ability to:
Create and manage Docker images specifically customized for AI and ML applications.
Containerize machine learning pipelines, tools, and associated dependencies.
Optimize Docker environments to enhance both performance and portability.
Deploy containerized ML services across a variety of runtime environments.
Course Format
Conceptual demonstrations accompanied by guided discussions.
Practical exercises centered on real-world containerization scenarios.
This instructor-led, live training in Bhutan (online or onsite) is tailored for beginner-level developers who want to learn the fundamentals of Kubefirst and understand how it streamlines, secures, and speeds up Kubernetes and Swarm cluster management for large-scale operations.
By the end of this training, participants will be able to:
Set up a Kubefirst development environment.
Write and execute a basic Kubefirst program.
Annotate code with Kubefirst directives and clauses.
This instructor-led, live training in Bhutan (online or onsite) is tailored for intermediate-level developers and DevOps engineers who wish to utilize 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 Bhutan (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 Bhutan (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.
In this instructor-led live training conducted in Bhutan (onsite or remote), participants will learn to create and manage Docker containers and deploy a sample application within a container. Additionally, participants will learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. The training concludes with advanced topics, guiding participants through 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.
The Certified Kubernetes Administrator (CKA) certification is jointly offered by The Linux Foundation and the Cloud Native Computing Foundation (CNCF).
Kubernetes has emerged as a prominent platform for orchestrating containers.
NobleProg has been delivering Docker and Kubernetes training since 2015. Having successfully completed over 360 training projects, we have established ourselves as one of the globally recognized training providers in the field of containerization.
Since 2019, we have assisted our clients in validating their proficiency in Kubernetes (k8s) environments by preparing and encouraging them to take 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 expertise by passing the CKA exam.
Furthermore, the training emphasizes gaining practical experience in Kubernetes administration. Therefore, we recommend participation even if you do not plan to take 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 the CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka
In this instructor-led live training in Bhutan (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.
This instructor-led live training (available online or on-site) is designed for engineers aiming to automate, secure, and monitor containerized applications within large-scale Kubernetes clusters.
Upon completion of this training, participants will be able to:
Leverage Kubernetes to deploy and manage diverse environments within a single cluster
Enhance the security, scalability, and monitoring capabilities of a Kubernetes cluster
Course Format
Engaging lectures and interactive discussions
Extensive exercises and practical practice
Hands-on implementation within a live lab environment
Course Customization Options
For tailored training options for this course, please reach out to us to make arrangements.
The Certified Kubernetes Application Developer (CKAD) certification program is jointly offered by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), which hosts Kubernetes.
This instructor-led, live training session (available online or onsite) is designed for developers who wish to validate their proficiency in designing, building, configuring, and exposing cloud-native applications on Kubernetes.
Additionally, the training emphasizes gaining practical experience in Kubernetes application development. Therefore, we recommend participating even if you do not plan to take the CKAD exam.
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 providers globally in the field of containerization. Since 2019, we have also assisted customers in validating their performance in Kubernetes environments by preparing them to pass the CKA and CKAD exams.
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 arrange.
To learn more about CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/
This instructor-led, live course in Bhutan 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, offering secure, transparent, and manageable connectivity between microservices. By utilizing Istio’s Envoy-based sidecar proxies, development teams can enforce strict policies, secure inter-service communications through mutual TLS (mTLS), gain comprehensive visibility into traffic patterns, and enhance reliability as systems scale.
This instructor-led live training session, available either online or on-site, targets intermediate-level engineers looking to deploy, secure, and manage microservices applications using Istio within Kubernetes environments.
Upon completing this training, participants will be equipped to:
Install and configure Istio on Kubernetes clusters.
Comprehend and implement service mesh concepts, encompassing traffic management, security, and observability.
Deploy microservices applications within an Istio service mesh framework.
Secure service-to-service communications using mutual TLS (mTLS) and adhere to Zero Trust principles.
Monitor, trace, and troubleshoot microservices using Prometheus, Grafana, and Jaeger.
Integrate Istio with Calico to implement advanced network policies and enhance security.
Course Format
Interactive lectures and discussions.
Extensive exercises and practical practice sessions.
Hands-on implementation within a live laboratory environment.
Course Customization Options
To request a customized training session for this course, please contact us to make arrangements.
The rapid advancement of microservices and container technologies in recent years has fundamentally transformed the way we design, develop, deploy, and operate software. Today's applications need to be built with scalability, elasticity, fault tolerance, and adaptability at their core. These evolving requirements have necessitated a shift towards new architectural patterns and best practices. This training explores effective strategies to identify, comprehend, and adapt to these modern demands.
Audience
This course is designed for individuals who possess a foundational understanding of container technology and Kubernetes concepts but may lack extensive practical experience. Drawing on use cases and insights from real-world projects, the training aims to inspire participants to design and manage even more robust cloud-native applications.
Developers
Operations professionals
DevOps engineers
QA Engineers
IT Project Managers
Course Format
Interactive lectures and discussions
Extensive exercises and hands-on practice
Practical implementation in a live-lab environment
Course Customization Options
To request a customized training version for this course, please get in touch with us to make arrangements.
This instructor-led, live training in Bhutan (online or on-site) is designed for engineers who want to utilize 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.
This instructor-led, live training in Bhutan (online or onsite) is designed for DevOps engineers who wish to use Kubernetes and GitLab to automate the DevOps lifecycle.
Upon completion of this training, participants will be able to:
Automate application builds, testing, and deployment processes.
Establish an automated build infrastructure.
Deploy applications to containerized cloud environments.
This instructor-led, live training in Bhutan (online or on-site) is tailored for Kubernetes professionals seeking to prepare for the CKS exam.
By the end of this training, participants will understand how to secure Kubernetes environments and container-based applications throughout the various stages of an application's lifecycle: build, deployment, and runtime.
This instructor-led, live training in Bhutan (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:
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 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 Bhutan (available online or onsite) is tailored for engineers who wish to strengthen their Kubernetes cluster security beyond the default configurations.
By the end of this training, participants will be able to:
Identify the vulnerabilities exposed by a standard Kubernetes installation.
Prevent unauthenticated access to the Kubernetes API, databases, and other services.
Protect the Kubernetes cluster from both accidental and malicious access.
Develop a comprehensive security policy and a set of best practices.
This instructor-led live training in Bhutan (online or onsite) is aimed at engineers who wish to advance their knowledge of Docker 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.
This intensive 7-day programme offers a comprehensive, hands-on journey into the design, deployment, and operation of cloud-native applications using contemporary DevOps methodologies.
Participants will delve into designing scalable microservices architectures, optimising container environments, and managing production workloads with Kubernetes. The curriculum encompasses advanced deployment strategies, GitOps-driven automation, and robust observability practices to guarantee system reliability and peak performance.
Emphasis is placed on addressing real-world operational challenges, including incident response, failure simulation, and root cause analysis. The programme wraps up by leveraging AI-powered tools to streamline troubleshooting and expedite operational decision-making.
Upon completion of the training, participants will possess a clear understanding of how to build, deploy, monitor, and maintain resilient distributed systems within a Kubernetes ecosystem.
This live training, led by an instructor in Bhutan (available online or onsite), is intended for engineers looking to adopt Docker for deploying and managing software as containers, moving away from traditional standalone models.
By the conclusion of this training, participants will be able to:
Install and configure Docker.
Understand and implement software containerization.
Manage Docker-based applications.
Network different Docker applications and systems.
This instructor-led, live training in Bhutan (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 conducted at Bhutan, participants will master the essentials of building microservices using Spring Cloud and Docker. Through practical exercises and the step-by-step construction of sample microservices, participants will have their knowledge tested and refined.
By the conclusion 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 is one of the leading Kubernetes-based platforms for deploying and managing containerized applications in cloud, hybrid and on-premises environments.
This hands-on training teaches participants how to install, administer and troubleshoot OpenShift clusters while applying security, networking and storage best practices. Through practical exercises, participants gain the skills needed to confidently manage production-ready OpenShift environments.
Learn 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, giving participants the skills to build and maintain modern applications in production environments.
This instructor-led, live training in Bhutan (online or onsite) is designed 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.
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Testimonials (4)
Training being interactive. He engaged us a lot by asking questions and imaginary use cases. He shifted away from his agenda to explain more of the things we are demanded.
Berk Ozdilek - Deutsche Bank
Course - Kubernetes Advanced
About the microservices and how to maintenance kubernetes
Yufri Isnaini Rochmat Maulana - Bank Indonesia
Course - Advanced Platform Engineering: Scaling with Microservices and Kubernetes
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