Containers and Virtual Machines (VMs) Training in Manaus

Edge AI represents a paradigm focused on executing machine learning inference close to 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 looking to deploy, orchestrate, and optimize AI workloads within Kubernetes-based edge environments.

Upon completing this course, participants will be able to:

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

Course Format

• Guided presentations backed by real-world examples.
• Scenario-based labs and practical edge deployment exercises.
• Hands-on experience working with Kubernetes edge frameworks.

Customization Options

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

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

This instructor-led live training, available online or on-site, targets advanced practitioners seeking to leverage AI and machine learning techniques to optimize Kubernetes resource usage, scheduling decisions, and autoscaling strategies.

Upon completing this program, participants will be able to:

• Apply AI/ML models to enhance workload scheduling decisions in Kubernetes.
• Utilize predictive analytics to optimize CPU, GPU, and memory allocation.
• Implement intelligent autoscaling using reinforcement learning and metric forecasting.
• Reduce infrastructure costs and latency through automated resource optimization.

Format of the Course

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

Course Customization Options

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

MLOps on Kubernetes is a framework designed to automate the training, validation, packaging, and deployment of machine learning models through containerized pipelines and GitOps workflows.

This instructor-led, live training (available online or on-site) is targeted at intermediate-level practitioners looking to build automated, scalable MLOps pipelines on Kubernetes.

Upon completing 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 that build real-world CI/CD workflows.
• Live-lab practice deploying ML workloads to Kubernetes.

Course Customization Options

• Organizations may 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:

• 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.

CI/CD for AI represents a structured methodology for automating the packaging, testing, containerization, and deployment of AI models through continuous integration and delivery pipelines.

This instructor-led live training, available online or onsite, is designed for intermediate-level professionals seeking to automate end-to-end AI model delivery workflows using Docker alongside CI/CD platforms.

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

• Develop automated pipelines for constructing and testing AI model containers.
• Establish version control and ensure reproducibility throughout the model lifecycle.
• Incorporate automated deployment strategies for AI services.
• Apply CI/CD best practices specifically adapted for machine learning operations.

Course Format

• Instructor-led presentations accompanied by technical discussions.
• Practical labs and hands-on implementation exercises.
• Realistic CI/CD workflow simulations conducted in a controlled environment.

Course Customization Options

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

This instructor-led live training in Manaus (online or onsite) is designed for advanced-level Kubernetes administrators and DevOps engineers who aim to enhance their monitoring skills for Kubernetes clusters using Prometheus and Grafana.

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

• Set up Prometheus and Grafana for Kubernetes monitoring.
• Monitor key metrics for pods, nodes, and services.
• Create dynamic dashboards to visualize cluster health and performance.
• Implement alerting strategies for proactive issue resolution.
• Apply best practices for scaling monitoring solutions in Kubernetes environments.

Hybrid AI deployment involves executing AI inference across cloud, on-premise, and edge environments through unified, container-based workflows.

This instructor-led live training, available online or onsite, is designed for advanced professionals seeking to architect and deploy distributed AI inference systems across heterogeneous infrastructures.

After completing this training, participants will be equipped to:

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

Course Format

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

Customization Options

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

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) targets beginner to intermediate-level IT professionals who wish to learn the core concepts and components of Kubernetes and use it to manage containerized applications at scale.

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

• Understand Kubernetes architecture and components.
• Deploy and manage containers in a Kubernetes cluster.
• Configure networking, storage, and scaling for workloads.
• Troubleshoot common issues and follow best practices for cluster operations.

Format of the Course

• Interactive lecture and discussion.
• Exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

This live, instructor-led training in Manaus (online or onsite) is designed for DevOps engineers and developers who aim 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.

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

This instructor-led live training, available online or onsite, is designed for beginner to intermediate-level technical professionals who aim to develop secure, portable AI inference microservices capable of consistent deployment across local machines, servers, or cloud virtual machines.

Upon completing this workshop, participants will be able to:

• Build lightweight inference containers suitable for both local and cloud deployment.
• Secure containerized AI services by applying best-practice techniques.
• Implement portable microservice workflows to ensure consistent environments.
• Deploy AI inference endpoints across various infrastructures.

Course Format

• Guided lectures combined with practical demonstrations.
• Hands-on exercises to reinforce deployment and security techniques.
• Live-lab practice for constructing and running 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 Manaus (onsite or remote), participants will learn how to deploy a collection of sample servers inside containers, then automate, scale, and manage their containerized servers within a Kubernetes cluster. The training goes on to more advanced topics, walking participants through the process of securing, networking and monitoring a Kubernetes cluster.

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

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

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

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

Upon completing this course, participants will be able to:

• Build and run GPU-enabled containers for training and inference tasks.
• Configure CUDA, drivers, and runtime libraries for containerized AI workflows.
• Optimize resource allocation and isolation for GPU-intensive applications.
• Deploy scalable, containerized deep learning services in production environments.

Course Format

• Interactive instruction supported by real-world demonstrations.
• Exercise-driven practice focused on GPU-enabled development.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• For tailored training aligned with your infrastructure or GPU stack, please contact us to arrange.

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

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 Manaus (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.

Master the fundamentals of containers, Kubernetes, and OpenShift through practical, hands-on training designed specifically for developers, DevOps engineers, and IT professionals. Participants will learn how to build containerized applications, deploy workloads, manage Kubernetes resources, and leverage OpenShift to streamline modern application delivery across cloud and hybrid environments.

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

This instructor-led live training, available either online or on-site, targets intermediate to advanced technical professionals looking to containerize and operationalize complete ML pipelines using Docker.

Upon completing this training, participants will be able to:

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

Course Format

• Interactive lectures supported by practical demonstrations.
• Hands-on exercises focused on constructing real-world ML pipeline components.
• Live lab implementation for end-to-end containerized workflows.

Customization Options

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

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

This instructor-led live training, available online or onsite, targets intermediate professionals aiming to package ML codebases, dependencies, and models using Docker to establish reliable development-to-production workflows.

Upon completing this course, participants will be able to:

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

Course Format

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

Customization Options

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

This instructor-led, live training in Manaus (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 Manaus (online or onsite) is designed for intermediate-level developers and DevOps engineers aiming to use Minikube as part of their development workflow.

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

• Set up and manage a local Kubernetes environment using Minikube.
• Understand how to deploy, manage, and debug applications on Minikube.
• Integrate Minikube into their continuous integration and deployment pipelines.
• Optimize their development process using Minikube's advanced features.
• Apply best practices for local Kubernetes development.

This instructor-led, live training in Manaus (online or onsite) targets 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 Manaus (online or on-site) is targeted at beginner to intermediate software developers and DevOps professionals who want 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.
• Grasp the fundamental 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: Gain theoretical and practical skills in Docker and Kubernetes.

This instructor-led live training, located in Manaus (onsite or remote), will teach participants how to create and manage Docker containers and deploy a sample application within one. Participants will also learn to automate, scale, and manage their containerized applications inside a Kubernetes cluster. Furthermore, the training covers advanced topics, guiding participants through the process of securing, scaling, and monitoring a Kubernetes cluster.

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

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

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

Kubernetes has emerged as a leading platform for container orchestration.

NobleProg has been delivering Docker and Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most recognized training providers globally in the field of containerization.

Since 2019, we have also been helping our customers validate their performance in Kubernetes environments by preparing them and encouraging them to pass the CKA and CKAD exams.

This instructor-led, live training (available online or onsite) is designed for System Administrators and Kubernetes users who wish to validate their knowledge by passing the CKA exam.

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

Course Format

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

Course Customization Options

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

In this instructor-led live training in Manaus (online or on-site), participants will learn how to set up and manage a production-scale container environment using Kubernetes on AKS.

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

• Configure and manage Kubernetes on AKS.
• Deploy, manage and scale a Kubernetes cluster.
• Deploy 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.

Learn how to build, deploy, and administer containerized environments using Docker, Kubernetes, and OpenShift. This five-day, hands-on training covers container images, Kubernetes workloads, cluster networking, storage, security, monitoring, and practical OpenShift administration. Participants gain the skills needed to operate modern container platforms and troubleshoot applications across development and production environments.

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

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

• Utilize Kubernetes to deploy and manage diverse environments within a single cluster
• Secure, scale, and monitor a Kubernetes cluster

Course Format

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

Customization Options

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

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

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

Additionally, the training emphasizes gaining practical experience in Kubernetes application development, so we recommend participating even if you do not plan to take the CKAD exam.

NobleProg has been delivering Docker & Kubernetes training since 2015. With more than 360 successfully completed training projects, we have become one of the most recognized training companies worldwide in the field of containerization. Since 2019, we have also been assisting our customers in validating their performance in Kubernetes environments by preparing them and encouraging them to pass the CKA and CKAD exams.

Course Format

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

Course Customization Options

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

This instructor-led, live course in Manaus 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, enabling secure, observable, and manageable connections between microservices. By utilizing Istio's Envoy-based sidecar proxies, development teams can enforce policies, secure communications through mTLS, gain deep insights into traffic patterns, and enhance reliability at scale.

This instructor-led live training, available online or on-site, targets intermediate-level engineers looking to deploy, secure, and manage microservices applications using Istio within a Kubernetes environment.

Upon completion of this training, participants will be capable of:

• Installing and configuring Istio on Kubernetes clusters.
• Understanding and applying service mesh concepts, including traffic management, security, and observability.
• Deploying microservices applications within an Istio service mesh.
• Securing service-to-service communications using mutual TLS (mTLS) and Zero Trust principles.
• Monitoring, tracing, and troubleshooting microservices using Prometheus, Grafana, and Jaeger.
• Integrating Istio with Calico for advanced network policies and security.

Course Format

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

Customization Options for the Course

• For requests regarding customized training for this course, please contact us to make arrangements.

The rapid evolution of microservices and container technologies has fundamentally transformed how we design, develop, deploy, and operate software. Today's applications need to excel in scalability, elasticity, resilience to failure, and adaptability to change. To meet these modern demands, architects must adopt a distinct set of patterns and practices. This training explores how to identify, comprehend, and adapt to these evolving requirements.

Audience
This course is designed for professionals who have some familiarity with container technology and Kubernetes concepts but may lack extensive practical experience. Drawing on use cases and lessons learned from real-world projects, the goal is to inspire participants to create and manage superior cloud-native applications.

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

Course Format

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

Course Customization Options

• For customized training arrangements for this course, please contact us.

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

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

• Install and configure Helm.
• Create reproducible builds of Kubernetes applications.
• Share applications as Helm charts.
• Run third-party applications saved as Helm charts.
• Manage releases of Helm packages.

This instructor-led live training in Manaus (available online or onsite) is designed for DevOps engineers who aim 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 Manaus (online or onsite) is designed for 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, held in Manaus (online or onsite), is designed for developers and DevOps engineers who wish to adopt a serverless approach for building enterprise applications on Kubernetes.

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

• Set up and configure the Kubernetes system to initiate development using a serverless architecture.
• Understand the foundational concepts and principles of serverless environments.
• Operate the toolchains required for serverless development and integrate them with Kubernetes components.
• Practice Python programming skills to implement serverless systems.
• Secure enterprise applications deployed through a serverless framework on Kubernetes.
• Utilize modern cloud computing methods to optimize DevOps task processing workflows.

This instructor-led live training in Manaus (online or onsite) is designed for engineers who want to enhance Kubernetes cluster security beyond the default configurations.

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

• Identify vulnerabilities inherent in a default Kubernetes installation.
• Prevent unauthorized access to the Kubernetes API, database, and other services.
• Protect the Kubernetes cluster from accidental or malicious intrusions.
• Develop a comprehensive security policy and establish a set of best practices.

This guided, live training in Manaus (online or in-person) targets engineers who want to advance their Docker knowledge to deploy applications at a larger scale while maintaining control.

Upon completion of this training, participants will be capable of:

• Creating custom Docker images.
• Deploying and managing a high volume of Docker applications.
• Assessing various container orchestration solutions to select the most appropriate one.
• Establishing a continuous integration pipeline for Docker applications.
• Integrating Docker applications with existing CI tooling.
• Securing Docker applications.

This intensive 7-day program offers a comprehensive, hands-on exploration into the design, deployment, and operation of cloud-native applications using contemporary DevOps methodologies.

Participants will delve into creating scalable microservices architectures, optimizing containerized environments, and managing production workloads with Kubernetes. The curriculum encompasses advanced deployment strategies, GitOps-driven automation, and observability techniques to guarantee system reliability and peak performance.

Emphasis is placed on addressing real-world operational hurdles, including incident response protocols, failure simulation exercises, and root cause analysis. The program culminates in leveraging AI-powered tools to enhance troubleshooting capabilities and expedite operational decision-making processes.

Upon completion of the training, participants will possess a solid grasp of how to construct, deploy, monitor, and sustain resilient distributed systems within a Kubernetes-based infrastructure.

This instructor-led, live training in Manaus (online or onsite) is designed for engineers who wish to utilize Docker to deploy and manage software as containers, moving away from traditional standalone software.

By the end 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.
• Understand and edit Docker registries.

This instructor-led, live training in Manaus (online or onsite) is aimed at intermediate to advanced DevOps engineers and system administrators who wish to deploy and manage self-hosted Kubernetes clusters without cloud dependencies.

By the end of this training, participants will be able to: deploy production-ready Kubernetes clusters using kubeadm on bare-metal or virtual machines; configure high-availability control planes and etcd clusters; implement container networking and storage for self-managed environments; set up monitoring and observability using self-hosted solutions.

In this instructor-led live training held at Manaus, participants will learn the essentials of building microservices using Spring Cloud and Docker. Knowledge is reinforced through exercises and the step-by-step development of sample microservices.

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

• Understand the fundamentals of microservices.
• Use Docker to build containers for microservice applications.
• Build and deploy containerized microservices using Spring Cloud and Docker.
• Integrate microservices with discovery services and the Spring Cloud API Gateway.
• Use Docker Compose for end-to-end integration testing.

OpenShift 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 Manaus (online or onsite) is tailored for intermediate-level virtualization administrators who intend 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 mechanisms.
• Optimize performance in open-source virtualization environments.