Containers and Virtual Machines (VMs) Training in Trenton

Edge AI is a paradigm that emphasizes running machine learning inference near data sources to achieve low-latency, efficient, and scalable processing. This instructor-led, live training (online or onsite) is designed for intermediate to advanced practitioners who wish to deploy, orchestrate, and optimize AI workloads in Kubernetes-based edge environments for government applications. By completing this course, participants will be able to: - Set up lightweight Kubernetes distributions suitable for edge deployments. - Deploy AI inference workloads effectively across resource-constrained edge nodes. - Manage connectivity challenges and synchronization patterns in edge environments. - Optimize performance, storage, and networking for real-world edge scenarios. **Format of the Course** - Guided presentations supported by practical government-focused examples. - Scenario-based labs and hands-on edge deployment exercises. - Direct experience with Kubernetes edge frameworks tailored to public sector workflows. **Course Customization Options** - To request a customized training that aligns with specific edge platform needs for government, 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 artificial intelligence and machine learning techniques to optimize Kubernetes resource usage, scheduling decisions, and autoscaling strategies for government operations. At the completion of this program, participants will be able to: - Apply AI/ML models to enhance 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 costs 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 for government, please contact us for customization.

MLOps on Kubernetes is a framework designed to automate the training, validation, packaging, and deployment of machine learning models using containerized pipelines and GitOps workflows. This instructor-led, live training (available online or onsite) is targeted at intermediate-level practitioners who wish to develop automated, scalable MLOps pipelines on Kubernetes for government use. Upon completion of this training, participants will be equipped 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. **Format of the Course** - 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 for government operations.

Kubeflow is an open-source platform designed to streamline the development, training, and deployment of machine learning workloads on Kubernetes. This instructor-led, live training (online or onsite) is aimed at professionals at the beginner to intermediate levels who wish to build reliable ML workflows using Kubeflow for government applications. Upon completion of this training, attendees will gain the skills to: - Navigate the Kubeflow ecosystem and its 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 for government use.

For government agencies, maintaining clear, factual, and neutral communication is essential to ensure transparency and accountability in all public sector workflows.

CI/CD for AI is a structured approach to automating the packaging, testing, containerization, and deployment of machine learning models using continuous integration and continuous delivery pipelines.

This instructor-led, live training (available online or on-site) is designed for intermediate-level professionals who wish to automate end-to-end AI model delivery workflows using Docker and CI/CD platforms.

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

• Create automated pipelines for building and testing AI model containers.
• Implement version control and reproducibility for model lifecycles.
• Integrate automated deployment strategies for AI services.
• Apply CI/CD best practices tailored to machine learning operations, ensuring alignment with public sector workflows, governance, and accountability.

Format of the Course

• Instructor-guided presentations and technical discussions.
• Practical labs and hands-on implementation exercises.
• Realistic CI/CD workflow simulations in a controlled environment, specifically designed to meet the needs of government agencies.

Course Customization Options

• If your organization requires customized pipeline workflows or platform integrations for government operations, please contact us to tailor this course to your specific requirements.

This instructor-led, live training (available online or on-site) is designed for advanced-level Kubernetes administrators and DevOps engineers who aim to enhance their monitoring capabilities for Kubernetes clusters using Prometheus and Grafana.

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

• Configure Prometheus and Grafana for effective Kubernetes cluster monitoring.
• Track essential metrics for pods, nodes, and services.
• Develop dynamic dashboards to illustrate cluster health and performance.
• Establish alerting mechanisms for timely issue detection and resolution.
• Adhere to best practices for scaling monitoring solutions in Kubernetes environments, ensuring optimal resource utilization and system reliability for government applications.

Hybrid AI deployment involves running AI inference across cloud, on-premise, and edge environments using unified container-based workflows. This instructor-led, live training (online or onsite) is designed for advanced-level professionals who aim to design and deploy distributed AI inference systems across diverse environments for government and other sectors. Upon completion of this training, participants will be able to: - Build secure and scalable containerized AI services for multi-location environments. - Deploy AI inference workloads to cloud, local servers, and edge devices using Docker. - Integrate orchestration tools to automate distributed AI operations. - Optimize inference latency, reliability, and resilience across diverse infrastructure. **Format of the Course** - Guided presentations and expert-led discussions. - Extensive hands-on practice and applied exercises. - Real-world experimentation in a controlled live-lab setup. **Course Customization Options** - For tailored adjustments to align this course with your organization’s infrastructure or use cases, please contact us to customize the training for government or other specific needs.

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) is tailored for IT professionals at beginner to intermediate levels who seek to understand the core concepts and components of Kubernetes and apply this knowledge to manage containerized applications effectively. By the end of this training, participants will be able to: - Comprehend Kubernetes architecture and its key components. - Deploy and manage containers within a Kubernetes cluster. - Configure networking, storage, and scaling for workloads. - Diagnose common issues and adhere to best practices for cluster operations. **Format of the Course:** - Interactive lectures and discussions. - Extensive exercises and practical activities. - Hands-on implementation in a live-lab environment. **Course Customization Options:** To request a customized training program tailored to specific needs, please contact us to arrange. This training can be adapted to align with public sector workflows, governance, and accountability requirements for government agencies.

This instructor-led, live training in Trenton (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 for government. 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 command line tools. - Gain hands-on experience from basic to advanced Kubernetes operations and administration.

Docker is a containerization platform used to create portable, isolated, and secure deployment environments for AI inference services. This instructor-led, live training (online or onsite) is designed for government technical professionals at beginner to intermediate levels who aim to build secure, portable AI inference microservices that can be deployed consistently across local machines, servers, or cloud VMs for government use. By the conclusion of this workshop, participants will be able to: - Build lightweight inference containers suitable for both local and cloud deployment. - Secure containerized AI services using best-practice techniques. - Implement portable microservice workflows for consistent environments. - Deploy AI inference endpoints across diverse infrastructures. **Format of the Course** - Guided lectures paired with practical demonstrations. - Hands-on exercises to reinforce deployment and security techniques. - Live-lab practice for building 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 Trenton (onsite or remote), participants will learn how to deploy sample servers within containers, then automate, scale, and manage these containerized servers using a Kubernetes cluster. The training progresses to more advanced topics, guiding participants through the processes of securing, networking, and monitoring a Kubernetes cluster for government use.

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

• Set up and operate a Docker container.
• Deploy containerized databases and servers.
• Configure a Docker and Kubernetes cluster.
• Utilize Kubernetes to deploy and manage multiple environments within the same cluster.
• Secure, scale, and monitor a Kubernetes cluster for government operations.

GPU acceleration is essential for executing high-performance deep learning workloads in a scalable and efficient manner. This instructor-led, live training (online or onsite) is designed for intermediate-level technical professionals who wish to configure, optimize, and run GPU-enabled AI workloads within Docker containers. At the conclusion of this course, participants will be able to: - Build and run GPU-enabled containers for both training and inference. - 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. **Format of the Course** - Interactive instruction supported by real-world demonstrations. - Practice exercises 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 for government, please contact us to arrange.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to effectively deploy, manage, and scale containerized applications using Kubernetes for government operations. 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 Trenton (online or onsite) is designed for intermediate to advanced developers, DevOps professionals, and architects who aim 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 in alignment with standards and guidelines for government.

This instructor-led, live training (online or onsite) is aimed at advanced-level platform engineers and DevOps professionals who wish to master scaling applications using microservices and Kubernetes for government. 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.

This program provides foundational instruction on container technologies, Kubernetes architecture, and OpenShift platform capabilities, emphasizing practical application. Designed for technical professionals ranging from novice to intermediate proficiency, the instructor-led sessions—available in virtual or on-premises formats—facilitate mastery of container operations, core Kubernetes components, and the deployment lifecycle within the OpenShift environment. Upon completion, participants will demonstrate the ability to: * Construct and administer container images and registries while adhering to standards for security and reproducibility. * Orchestrate Kubernetes resources, including pods, deployments, and services, within the OpenShift ecosystem. * Utilize OpenShift-specific functionalities such as routes, BuildConfigs, and the web console to enhance application delivery efficiency. * Configure persistent storage, management of configuration data, and secure handling of secrets for stateful applications. * Enforce fundamental security protocols, role-based access control (RBAC), and monitoring standards to ensure cluster stability and operational integrity. **Instructional Methodology** * Interactive lectures coupled with collaborative discussion. * Daily practical exercises conducted in a live OpenShift environment. * Scenario-based problem-solving workshops focused on troubleshooting. **Tailored Curriculum Availability** Organizations seeking a customized curriculum for government or enterprise audiences may contact our office to arrange specific training modules.

Docker is a containerization platform designed to create reproducible, portable, and scalable environments for machine learning (ML) systems. This instructor-led, live training (available online or onsite) is targeted at intermediate to advanced technical professionals who aim to containerize and operationalize comprehensive ML pipelines using Docker. Upon completion of 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 continuous integration/continuous deployment (CI/CD) for ML components. - Deploy, monitor, and scale ML services in containerized environments. **Format of the Course** - Interactive lectures supported by practical demonstrations. - Hands-on exercises focused on constructing real ML pipeline components. - Live-lab implementation for end-to-end containerized workflows. **Course Customization Options** - For customized training aligned with specific ML infrastructure needs, please contact us to discuss options tailored for government and other public sector entities.

Docker is a containerization platform that enables consistent, portable, and reproducible environments for artificial intelligence (AI) and machine learning (ML) workloads. This instructor-led, live training (online or onsite) is designed for intermediate-level professionals who wish to package ML codebases, dependencies, and models using Docker for reliable development-to-production workflows in government settings. After completing this course, participants will be able to: - Build and manage Docker images tailored for AI and ML applications. - Containerize machine learning pipelines, tools, and dependencies. - Optimize Docker environments for performance and portability. - Deploy containerized ML services across different runtime environments. **Format of the Course** - Concept demonstrations supported by guided discussion. - Hands-on exercises focused on real-world containerization tasks. - Practical implementation using live-lab Docker environments. **Course Customization Options** - To customize this training for government or your organizational environment, please contact us to arrange.

This instructor-led, live training in [location] (online or onsite) is designed for beginner-level developers who wish to learn the fundamentals of Kubefirst and how it simplifies, secures, and accelerates Kubernetes and Swarm cluster management at enterprise scale for government. By the end of this training, participants will be able to: - Set up a Kubefirst development environment. - Write and run basic Kubefirst programs. - Annotate code with Kubefirst directives and clauses. - Utilize Kubefirst APIs and libraries. - Profile and debug Kubefirst programs.

This instructor-led, live training (online or onsite) is designed for intermediate-level developers and DevOps engineers who wish to incorporate Minikube into their development workflows for government. 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 for government. - Optimize their development process using Minikube's advanced features. - Apply best practices for local Kubernetes development in alignment with public sector standards.

This instructor-led, live training (online or onsite) is designed for intermediate-level developers and DevOps engineers who aim to build, deploy, and manage microservices using Spring Cloud and Docker. By the end of this training, participants will be able to: - Develop microservices with Spring Boot and Spring Cloud. - Containerize applications using 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, ensuring alignment with best practices for government workflows and governance.

This instructor-led, live training in Trenton (online or onsite) is designed for government software developers and DevOps professionals at the beginner to intermediate level 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 fundamental concepts and architecture of Kubernetes for government use. - Deploy and manage containers using kubectl and the Minikube dashboard. - Set up persistent storage and networking solutions for Kubernetes in a government context. - Utilize Minikube for developing, testing, and debugging applications for government projects.

This instructor-led program, available online or on-site at Trenton, provides technical professionals and interested parties with the skills necessary to leverage Skupper for establishing secure connectivity within hybrid multi-cloud architectures. Upon completion of this training for government, participants will demonstrate proficiency in the following areas: * Comprehend the core principles and operational fundamentals of Skupper. * Deploy and configure Skupper across multiple namespaces. * Implement security configurations to enable interoperable communication between applications across diverse cloud environments.

Training objectives: Acquire theoretical and operational skills in Docker and Kubernetes.

In this instructor-led, live training in [location] (onsite or remote), participants will learn how to create and manage Docker containers, then deploy a sample application within a container. They will also gain the skills to automate, scale, and manage their containerized applications within a Kubernetes cluster. The training further delves into advanced topics, guiding participants through securing, scaling, and monitoring a Kubernetes cluster for government use. 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 for government operations.

The Certified Kubernetes Administrator (CKA) program was developed by The Linux Foundation and the Cloud Native Computing Foundation (CNCF). Kubernetes has become a leading platform for container orchestration in modern computing environments. 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 premier training organizations globally in the field of containerization. Since 2019, we have also assisted our clients in validating their performance in Kubernetes environments by preparing them to pass the CKA and CKAD exams. This instructor-led, live training (available online or on-site) is designed for System Administrators and Kubernetes users who wish to confirm their expertise by passing the CKA exam. Additionally, the training focuses on gaining practical experience in Kubernetes administration, making it valuable even for those not planning to take the CKA exam. **Format of the Course:** - Interactive lectures and discussions. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options:** - To request a customized training program for government or other specific needs, please contact us to arrange. - For more information about CKA certification, visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

In this instructor-led, live training for government agencies (available online or onsite), participants will learn how to set up and manage a production-scale container environment using Kubernetes on Azure Kubernetes Service (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 the AKS 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 Trenton, participants will learn how to manage the Red Hat OpenShift Container Platform for government environments.

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

• Create, configure, manage, and troubleshoot OpenShift clusters for government use.
• Deploy containerized applications on-premises, in public clouds, or on hosted clouds for government operations.
• Secure the OpenShift Container Platform to meet government security standards.
• Monitor and gather metrics to ensure compliance with government regulations.
• Manage storage solutions that align with government data management policies.

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 for government. 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 - Extensive exercises and practice sessions - Hands-on implementation in a live-lab environment **Course Customization Options** - To request a customized training for this course, please contact us to arrange.

The Certified Kubernetes Application Developer (CKAD) program has been developed by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), which hosts Kubernetes. This instructor-led, live training (online or onsite) is designed for Developers who wish to validate their skills in designing, building, configuring, and exposing cloud native applications for government use on Kubernetes. The training also emphasizes gaining practical experience in Kubernetes application development. We recommend participating in this course even if you do not plan to take the CKAD exam. NobleProg has been delivering Docker & Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the best-known training companies worldwide in the field of containerization. Since 2019, we have also been assisting our clients in confirming their proficiency in Kubernetes environments by preparing them and encouraging them to pass the CKA and CKAD exams. **Format of the Course** - Interactive lecture and discussion. - Numerous exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options** - To request a customized training for this course, please contact us to arrange. - For more information about CKAD, visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

This instructor-led, live course in Trenton offers participants a comprehensive overview of Rancher, tailored for government use. Through hands-on practice, attendees will learn how to effectively deploy and manage a Kubernetes cluster using Rancher, ensuring alignment with public sector workflows and governance requirements.

Istio is an open-source service mesh designed to run on Kubernetes, providing secure, observable, and manageable connectivity between microservices. By utilizing Istio’s Envoy-based sidecar proxies, teams can enforce policies, secure communications with mutual TLS (mTLS), achieve deep observability into traffic, and enhance reliability at scale. This instructor-led, live training (available online or onsite) is targeted at intermediate-level engineers who aim to deploy, secure, and manage microservices applications using Istio on Kubernetes for government. 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 using Prometheus, Grafana, and Jaeger. - Integrate Istio with Calico for advanced network policies and security. **Format of the Course** - Interactive lecture and discussion. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options** - To request a customized training for this course, please contact us to arrange.

The evolution of microservices and containers in recent years has significantly transformed how we design, develop, deploy, and manage software. Modern applications must be optimized for scalability, elasticity, resilience, and adaptability. These new demands necessitate a different set of patterns and practices in modern architectures. This training program examines methods to identify, understand, and adjust to these evolving requirements. **Audience** This training is designed for individuals who have a basic understanding of container technology and Kubernetes concepts but may lack practical experience. It draws on real-world use cases and lessons learned from actual projects, aiming to inspire participants to create and manage more effective cloud-native applications for government environments. - Developers - Operations Staff - DevOps Engineers - Quality Assurance (QA) Engineers - IT Project Managers **Format of the Course** - Interactive lectures and discussions - Extensive exercises and hands-on practice - Implementation in a live-lab environment **Course Customization Options** To request a customized training for government-specific needs, please contact us to arrange.

This instructor-led, live training in [location] (online or onsite) is designed for engineers who wish to use Helm to streamline the process of installing and managing Kubernetes applications for government. By the end of this training, participants will be able to: - Install and configure Helm. - Create reproducible builds of Kubernetes applications. - Share applications as Helm charts. - Run third-party applications saved as Helm charts. - Manage releases of Helm packages.

This instructor-led, live training in [location] (online or onsite) is aimed at DevOps engineers who wish to utilize Kubernetes and GitLab to automate the DevOps lifecycle for government projects. By the end of this training, participants will be able to: - Automate application builds, tests, and deployments. - Establish an automated build infrastructure. - Deploy an application to a containerized cloud environment.

This instructor-led, live training in [location] (online or onsite) is aimed at Kubernetes practitioners who wish to prepare for the Certified Kubernetes Security Specialist (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 training aligns with best practices for government agencies seeking to enhance their cybersecurity measures for government operations.

This instructor-led, live training (online or onsite) is aimed at developers and DevOps engineers who wish to utilize a serverless approach for building enterprise applications in Kubernetes for government. By the end of this training, participants will be able to: - Set up and configure the Kubernetes system to begin developing with a serverless architecture. - Understand the foundational concepts and principles that underpin serverless environments. - Operate the necessary toolchains for serverless development and integrate them with Kubernetes components. - Practice their skills in Python programming and apply it 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 Trenton (online or onsite) is aimed at engineers who wish to enhance the security of a Kubernetes cluster beyond its default settings for government use.

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

• Identify vulnerabilities that are exposed by a default Kubernetes installation.
• Prevent unauthorized access to the Kubernetes API, database, and other services.
• Safeguard a Kubernetes cluster from both accidental and malicious access.
• Develop a comprehensive security policy and set of best practices for government environments.

This instructor-led, live training in Trenton (online or onsite) is aimed at engineers who wish to enhance their knowledge of Docker for government purposes, enabling them to deploy applications on a larger scale while maintaining control. By the end of this training, participants will be able to: - Construct their own Docker images. - Deploy and manage multiple Docker applications efficiently. - Evaluate various container orchestration solutions and select the most appropriate one. - Establish a continuous integration process for Docker applications. - Integrate Docker applications with existing continuous integration tooling processes. - Secure their Docker applications effectively.

By the end of this training, participants will be able to: - Construct their own Docker images. - Deploy and manage a large number of Docker applications. - Assess various container orchestration solutions and select the most appropriate one for government needs. - Establish a continuous integration process for Docker applications. - Integrate Docker applications with existing continuous integration tools and processes. - Secure their Docker applications effectively. - Utilize Kubernetes to deploy and manage different environments within the same cluster. - Ensure the security, scalability, and monitoring of a Kubernetes cluster.

This 7-day program offers a comprehensive, hands-on exploration into designing, deploying, and operating cloud-native applications using modern DevOps practices for government agencies.

Participants will delve into the design of scalable microservices architectures, optimization of container environments, and management of production workloads with Kubernetes. The curriculum covers advanced deployment strategies, GitOps-based automation, and observability techniques to ensure system reliability and performance.

A significant emphasis is placed on addressing real-world operational challenges, such as incident response, failure simulation, and root cause analysis. The program concludes with an examination of AI-powered tools that support troubleshooting and enhance 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 for government operations.

This instructor-led, live training in Trenton (online or onsite) is aimed at engineers who wish to utilize Docker for deploying and managing software as containers, rather than traditional standalone applications. 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 training is designed to align with public sector workflows, governance, and accountability, ensuring that participants are well-equipped to leverage Docker for government projects.

This instructor-led, live training in Trenton (online or onsite) is designed for intermediate to advanced DevOps engineers and system administrators who seek to deploy and manage self-hosted Kubernetes clusters without relying on cloud services.

Upon completion of this training, participants will be equipped 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 solutions for self-managed environments; establish monitoring and observability systems using self-hosted tools. This course is tailored to enhance the skills needed for government IT professionals to effectively manage secure and scalable Kubernetes deployments.

Upon completion of this professional course, participants will have acquired the knowledge and skills necessary to effectively implement, manage, and scale Kuma's service mesh within Kubernetes environments. They will be able to implement advanced traffic routing, observability, and security features to optimize the performance and reliability of their microservices-based applications.

In this instructor-led, live training in Trenton, participants will gain a comprehensive understanding of building microservices using Spring Cloud and Docker. The training includes hands-on exercises and the step-by-step development of sample microservices to reinforce participant knowledge.

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

• Understand the core principles and benefits of microservices architecture.
• Utilize Docker to create and manage containers for microservice applications.
• Develop and deploy containerized microservices using Spring Cloud and Docker, ensuring alignment with best practices for government projects.
• Integrate microservices with discovery services and the Spring Cloud API Gateway to enhance system reliability and scalability.
• Employ Docker Compose for comprehensive end-to-end integration testing, ensuring robustness and efficiency in deployment processes for government applications.

OpenShift Container Platform v4 is an enterprise-ready Kubernetes platform developed by Red Hat, designed to automate the deployment, scaling, and management of containerized applications for government and other public sector organizations.

This instructor-led, live training (available online or onsite) is aimed at system administrators and DevOps engineers who wish to deploy, manage, and operate OpenShift clusters in production environments for government use.

The course offers a hands-on approach to installing and managing OpenShift 4 clusters, working with Operators, securing workloads, and operating applications at scale within the context of public sector workflows, governance, and accountability.

The Red Hat OpenShift Administration II: Configuring a Production Cluster (DO280) course is designed to equip OpenShift Cluster Administrators with the skills necessary to manage daily administration tasks for clusters hosting applications from both internal teams and external vendors. This training enables administrators to facilitate self-service capabilities for users with varying roles and deploy applications that necessitate specific permissions, such as CI/CD tooling, performance monitoring, and security scanners. The course emphasizes configuring multi-tenancy and security features of OpenShift, as well as managing add-ons based on operators, ensuring robust and secure cluster operations for government and other organizational environments.

In this instructor-led, live training in Trenton (online or onsite), participants will learn how to create, update, and maintain applications using OpenShift Container Platform for government environments.

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

• Understand OCI (Open Containers Initiative) and its implications for utilizing container engines such as Docker within OpenShift for government operations.
• Grasp the relationship between the different versions of OpenShift (OKP, OpenShift Container Platform, Red Hat OpenShift, etc.) in the context of public sector workflows.
• Automate the software delivery pipeline to enhance efficiency and security for government applications.
• Apply DevOps principles to deliver software continuously, ensuring alignment with governance and accountability standards for government projects.

This in-depth technical course is designed to provide participants with the advanced skills needed to manage Proxmox VE-based virtualized infrastructure, focusing on storage, backup, high availability, security, and monitoring. Through theoretical lessons and numerous practical exercises, participants will learn how to:

• Manage local and remote storage, leveraging ZFS for advanced features and integrating Ceph for distributed storage scenarios.
• Implement backup and disaster recovery strategies using snapshots, replication, restore, and Proxmox Backup Server.
• Design and administer high-availability clusters, enabling live VM migration and load balancing.
• Apply best practices for security reinforcement, configure firewalls, and protect VMs and containers.
• Monitor performance and logs with integrable tools like Zabbix, Prometheus, and Grafana, for comprehensive visibility into the infrastructure.
• Develop real-world use cases in academic and corporate settings, including DevOps environments, production service hosting, and HPC clusters.

The course is highly practical and operational, with hands-on sessions guiding participants from initial configuration to failover scenario simulation.

This instructor-led, live training (available online or onsite) is designed for intermediate-level virtualization administrators who wish to transition to open-source platforms 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 to these open-source solutions. - Implement high availability and disaster recovery strategies for government environments. - Optimize performance in open-source virtualization environments to meet the needs of public sector workflows and governance.