Podman Containers Training Course

This instructor-led, live training in Guatemala (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.

This instructor-led, live training in Guatemala (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 Guatemala (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 (online or onsite) is aimed at engineers wishing to run containerized applications using the CRI-O container runtime.

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

• Install and configure the CRI-O container runtime.
• Pull images from a variety of OCI-compliant registries.
• Run, test and manage containerized applications using CRI-O.

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 CRI-O, please visit: http://cri-o.io/.

This instructor-led, live training in Guatemala (online or onsite) is aimed at developers who wish to use Heroku to conveniently deploy web and mobile applications to the cloud, without grappling with infrastructure setup, configuration, management, etc.

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

• Understand the Heroku ecosystem and how it differs from AWS EC2 and other PaaS offerings.
• Leverage Heroku features such as Git integration, Heroku CLI and Heroku Dashboard to push applications to the cloud with ease.

This instructor-led, live training in Guatemala (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.

This instructor-led, live course in Guatemala provides participants with an overview of Rancher and demonstrates through hands-on practice how to deploy and manage a Kubernetes cluster with Rancher.

In this instructor-led, live training in Guatemala, 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 Guatemala, 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.

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 Guatemala, 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 Guatemala, 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 in (online or onsite) is aimed at engineers who wish to deploy Machine Learning workloads to an OpenShift on-premise or hybrid cloud.

• By the end of this training, participants will be able to:
• Install and configure Kubernetes and Kubeflow on an OpenShift cluster.
• Use OpenShift to simplify the work of initializing a Kubernetes cluster.
• Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
• Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
• Call public cloud services (e.g., AWS services) from within OpenShift to extend an ML application.

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

In this instructor-led, live training in Guatemala (onsite or remote), participants will learn learn to create, update, and maintain containerized applications using OKD.

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

• Deploy a containerized web application to an OKD cluster on-premise or in the cloud.
• Automate part of the software delivery pipeline.
• Apply the principles of the DevOps philosophy to ensure continuous delivery of an application.