Online or onsite, instructor-led live Containers and Virtual Machines (VMs) training courses demonstrate through hands-on practice the fundamentals and advanced topics of Containers and Virtual Machines (VMs).
Containers and Virtual Machines (VMs) training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Dartmouth onsite live Containers and Virtual Machines (VMs) trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Dartmouth - Metropolitan Place
99 Wyse Road, Dartmouth, Canada, B3A 4S5
Metropolitan Place is an ocean-front building, close to Alderney Landing and home to leading businesses. Motorway exits and the local ferry terminal are located close by, and restaurants cafes are easily accessible for lunch.
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 is a container orchestration platform widely used for managing distributed applications at scale.
This instructor-led, live training (online or onsite) is aimed at advanced-level practitioners who wish to apply AI and machine learning techniques to optimize Kubernetes resource usage, scheduling decisions, and autoscaling strategies.
At the completion of this program, participants will be able to:
Apply AI/ML models to improve workload scheduling decisions in Kubernetes.
Use predictive analytics to optimize CPU, GPU, and memory allocation.
Implement intelligent autoscaling using reinforcement learning and metric forecasting.
Reduce infrastructure cost and latency through automated resource optimization.
Format of the Course
Instructor-guided technical presentations and deep-dive discussions.
Hands-on lab work 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.
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
Customized versions of this training can be arranged to align with your team’s technology stack and project requirements.
Kubernetes is a scalable platform for deploying, serving, and managing machine learning models in production environments.
This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to operationalize ML models reliably on Kubernetes.
Upon completing this training, participants will gain the skills to:
Containerize and prepare ML models for efficient deployment.
Serve models using modern inference frameworks.
Optimize workloads with autoscaling, GPU configuration, and resource tuning.
Implement model rollout strategies such as A/B testing and canary deployments.
Format of the Course
Blended lecture, architectural analysis, and guided discussion.
Extensive practical exercises with real-world deployment scenarios.
Hands-on implementation using a live Kubernetes environment.
Course Customization Options
If you need this course tailored to your environment or toolchain, please contact us to discuss customization options.
This instructor-led, live training in Dartmouth (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 Dartmouth (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.
This instructor-led, live training in Dartmouth (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.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level to advanced-level 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.
By the end of this training, participants will be able to:
Understand and implement microservices architecture.
Deploy and manage containerized applications with Docker and Kubernetes.
Set up and optimize CI/CD pipelines for automated deployments.
Apply best practices for security, monitoring, and observability.
This instructor-led, live training in Dartmouth (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 introduction to containers, Kubernetes fundamentals, and Red Hat OpenShift platform concepts focused on hands-on skills.
This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level technical professionals who wish to learn container workflows, Kubernetes primitives, and how to deploy and operate applications on OpenShift.
By the end of this training, participants will be able to:
Build and manage container images and registries with best practices for reproducibility and security.
Deploy and manage Kubernetes objects such as pods, deployments, and services in OpenShift.
Use OpenShift features including routes, buildconfigs, and the web console to streamline application delivery.
Implement persistent storage, configuration management, and secrets handling for stateful workloads.
Apply basic security, RBAC, and monitoring practices to maintain healthy clusters and applications.
Format of the Course
Interactive lecture and discussion.
Hands-on labs in a live OpenShift environment every day.
Scenario-driven exercises and troubleshooting workshops.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
This instructor-led, live training in Dartmouth (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.
This instructor-led, live training in Dartmouth (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 Dartmouth (online or onsite) is aimed at intermediate-level system administrators who wish to effectively deploy, manage, and troubleshoot Hyper-V environments.
By the end of this training, participants will be able to:
Understand virtualization concepts and configure Hyper-V.
Create and manage virtual machines, VM storage, and networking.
Utilize advanced Hyper-V features and secure Hyper-V environments.
This instructor-led, live training in Dartmouth (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.
This instructor-led, live training in Dartmouth (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 in Dartmouth (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.
The Certified Kubernetes Administrator (CKA) program was created by The Linux Foundation and the Cloud Native Computing Foundation (CNCF).
Kubernetes is nowadys a leading platform used for containers orchestration.
NobleProg have been delivering Docker & Kubernetes training from 2015. With more than 360 successfully completed training projects, we became one of the best known training companies worldwide in field of containerization.
Since 2019 we are also helping our customers to confirm their performance in k8s environment by preparing them and encouraging to pass CKA and CKAD exams.
This instructor-led, live training (online or onsite) is aimed at System Administrators, Kubernetes users who wish to confirm their knowledge by passing CKA exam.
On the other hand, training is focused also on gaining practical experience in Kubernetes Administration, so we recommend taking part in it, even if you don't intend to take CKA exam.
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.
To learn more about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka
In this instructor-led, live training in Dartmouth (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 objective of this practical course is to provide all the tools that address the practical aspects of Docker and Kubernetes, in order that the participants can count on the necessary skills for the proper management of the program.
In this instructor-led, live training in Dartmouth, 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 aimed at engineers wishing to automate, secure, and monitor containerized applications in a large-scale Kubernetes cluster.
By the end of this training, participants will be able to:
Use Kubernetes to deploy and manage different environments under the same cluster
Secure, scale and monitor a Kubernetes cluster
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.
The Certified Kubernetes Application Developer (CKAD) program has been developed by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the host of Kubernetes.
This instructor-led, live training (online or onsite) is aimed at Developers who wish to confirm their skills in design, build, configure, and expose cloud native applications for Kubernetes.
On the other hand, training is also focused on gaining practical experience in Kubernetes application development, so we recommend taking part in it, even if you don't intend to take CKAD exam.
NobleProg have been delivering Docker & Kubernetes training from 2015. With more than 360 successfully completed training projects, we became one of the best known training company worldwide in field of containerization. Since 2019 we are also helping our customers to confirm their performance in k8s environment by preparing them and encouraging to pass CKA and CKAD exams.
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.
To learn more about CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/
This instructor-led, live course in Dartmouth 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 that runs on Kubernetes to provide secure, observable, and manageable connectivity between microservices. By leveraging Istio’s Envoy-based sidecar proxies, teams can enforce policies, secure communications with mTLS, gain deep observability into traffic, and improve reliability at scale.
This instructor-led, live training (online or onsite) is aimed at intermediate-level engineers who wish to deploy, secure, and manage microservices applications using Istio on Kubernetes.
By the end of this training, participants will be able to:
Install and configure Istio on Kubernetes clusters.
Understand and apply service mesh concepts including traffic management, security, and observability.
Deploy microservices applications within an Istio service mesh.
Secure service-to-service communications with mutual TLS (mTLS) and Zero Trust principles.
Monitor, trace, and troubleshoot microservices with Prometheus, Grafana, and Jaeger.
Integrate Istio with Calico for advanced network policies and security.
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.
EKS is a self-managed Kubernetes-as-a-service offering from AWS. EKS is fully scalable and customizable and allows a Kubernetes deployment to mimic and/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 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 to efficiently manage EKS
Audience
Developers
System Administrators
DevOps Engineers
Format of the Course
Part lecture, part discussion, exercises and heavy hands-on practice in a live-lab environment.
Note
To request a customized training for this course, please contact us to arrange.
The evolution of microservices and containers in recent years has significantly changed how we design, develop, deploy and run software. Modern applications must be optimized for scalability, elasticity, failure, and change. Driven by these new demands, modern architectures require a different set of patterns and practices. In this training, we examine ways to identify, understand and adjust to these new requirements.
Audience
This training is intended for people who are somewhat familiar with container technology and with Kubernetes concepts but are perhaps lacking the real world experience. It is based on use cases, and lessons learnt from real life projects with the intention of making people inspired to create and manage even better cloud native applications.
Developers
Operations
DevOps
QA Engineers
IT Project Managers
Format of the Course
Interactive lecture and discussion
Lots of exercises and practice
Handson 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 Dartmouth (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.
In this instructor-led, live training in Dartmouth, 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 Dartmouth (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 Dartmouth (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 (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.
Apache Karaf is an OSGi based runtime for deploying containerized applications.
In this instructor-led, live training (onsite or remote), participants will learn how to set up an OSGi based project as they step through the deployment of a modular Java application using Apache Karaf.
By the end of this training, participants will be able to:
Install and configure Apache Karaf
Understand the essential features of the OSGi runtime environment
Develop a containerized application using the Apache Karaf run time environment
Audience
Architects
Developers
Format of the Course
Part lecture, part discussion, exercises and heavy hands-on practice.
Note
To request a customized training for this course, please contact us to arrange.
In this instructor-led, live training in Dartmouth, we introduce the architecture, components and processes behind application virtualization and walk participants step-by-step through the deployment of App-V and App-V applications in a live lab environment. By the end of the course, participants will have knowledge and hands-on practice needed to install, configure, administer, and troubleshoot App-V as well as create, package and deploy their own App-V applications.
In this instructor-led, live training in Dartmouth, we cover advanced techniques and troubleshooting for Microsoft Application Virtualization (App-V), especially in the area of sequencing and packaging.
By the end of the course, participants will have a deep understanding of App-V and be able to sequence, troubleshoot and resolve complex issues.
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.
DC/OS (Distributed Cloud Operating System) is an open-source distributed operating system built upon the Apache Mesos project. Apache Mesos was built using the same principles as the Linux kernel, only at a different level of abstraction. The Mesos kernel runs on every machine and provides applications such as Hadoop, Spark, Kafka and Elasticsearch with API’s for resource management and scheduling across entire datacenter and cloud environments. Apache Mesos abstracts CPU, memory, storage, and other compute resources away from machines (physical or virtual), enabling fault-tolerant and elastic distributed systems to easily be built and run effectively.
DC/OS brings together Mesos and more than 30 applications into one coherent system, similar to how a Linux distribution packages the Linux kernel with applications to create a working operating system.
This course provides participants with an overview of Apache Mesos and DC/OS and demonstrates through hands-on practice how to deploy and manage a complete Data Center Operating System.
Audience
System administrators
DevOps engineers
Format of the course
Part lecture, part discussion, heavy hands-on practice
This instructor-led, live training in Dartmouth (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 Dartmouth (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 Dartmouth (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 for automating all development stages of containerized applications. Design patterns are iterable solutions to software development problems pertinent to software design. Kubernetes extensions are utilized for configuring and supporting Kubernetes clusters. With the help of Kubernetes design patterns and extensions, users of the platform can achieve CI/CD approaches while maintaining scalability and flexibility of software applications.
This instructor-led, live training (online or onsite) is aimed at developers and DevOps engineers who wish to leverage Kubernetes design patterns and extensions to create enterprise applications on Kubernetes clusters.
By the end of this training, participants will be able to:
Set up a Kubernetes cluster and configure the necessary DevOps tools.
Understand the fundamentals of software design patterns and Kubernetes extensions.
Utilize Kubernetes extensions and design patterns when interacting with Kubernetes API.
Develop customized Kubernetes resources and apply dynamic controllers to a cluster.
Manage and secure any Kubernetes environment with the help of Kubernetes plugins.
Integrate DevOps networking models to existing and prospective Kubernetes projects.
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.
OpenShift Container Platform v4 is an enterprise-ready Kubernetes platform developed by Red Hat, designed to automate the deployment, scaling, and management of containerised applications.
This instructor-led, live training (online or onsite) is aimed at system administrators and DevOps engineers who wish to deploy, manage, and operate OpenShift clusters in production environments.
The course provides a hands-on approach to installing and managing OpenShift 4 clusters, working with Operators, securing workloads, and operating applications at scale.
In this instructor-led, live training in Dartmouth (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:
Undersand OCI (Open Containers Initiative) and its implications for using container enginees such as Docker in OpenShift.
Understand the relationship between the different versions of OpenShift (OKP, 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 Dartmouth (online or onsite) is aimed at DevOps engineers and developers who wish to use Podman to create, run, and manage containers and pods as a non-root user.
By the end of this training, participants will be able to:
Install and configure Podman in rootless mode.
Build and run containers, container images, and pods.
Manage container networking and lifecycle.
Use Podman instead of Docker for creating and deploying containerized applications.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at penetration testers who wish to penetrate test networks in Kali Linux using Python.
By the end of this training, participants will be able to:
Create Python programs to seek network vulnerabilities.
Explore and use Kali web shells and shellcode in exploits.
This practical course contains topics addressed to system administrators, developers, embedded developers and ordinary desktop users (including managers) who would like to have an introduction to virtualization in general. After this course, administrators will be able to create private clouds for use in production, and developers will be able to test their code on multiple operating systems without needing a second PC or a non-x86 board.
We understand that the set of topics presented in this course covered a wide range of subjects that might not be applicable for all customers. When booking this course, please specify what you wish to achieve using QEMU or KVM, and we will customize it by reallocating time from less relevant topics to the ones that would be important for you.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level infrastructure professionals who wish to use Red Hat OpenShift to deploy, manage, and troubleshoot production containerized workloads.
By the end of this training, participants will be able to manage OpenShift clusters via CLI and web console, deploy applications with container images and Kubernetes manifests, troubleshoot networking and storage issues, and configure workloads for high availability and updates.
This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level virtualization administrators who wish to use open-source platforms to migrate away from VMware.
By the end of this training, participants will be able to:
Install and configure KVM, oVirt, and Proxmox VE.
Migrate virtual workloads from VMware.
Implement high availability and disaster recovery.
Optimize performance in open-source virtualization environments.
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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