NobleProg delivers comprehensive Containers and Virtual Machines (VMs) training courses in Atlanta, providing professionals with the expertise needed to succeed in today's competitive market. Our programs are designed to enhance skills and knowledge, ensuring participants are well-prepared for advanced roles within the industry. With a focus on practical application and strategic insights, we support career growth and organizational development across the region.
Whether delivered virtually or at a designated location, instructor-led instruction regarding Containers and Virtual Machines (VMs) utilizes practical exercises to illustrate core principles and sophisticated applications for government entities.
This educational offering is accessible as either remote or on-site instruction. Remote sessions are conducted via an interactive remote desktop environment, while on-site options may be facilitated locally in Atlanta or at NobleProg’s corporate training facilities in Atlanta.
NobleProg -- Your Local Training Provider
Atlanta, GA – Regus at Colony Squar
1201 Peachtree Street NE, Suite 200, Atlanta, United States, 30361
The venue is centrally located in Midtown Atlanta within the prominent Colony Square complex at 1201 Peachtree Street NE, easily accessed by car via I‑75/85 or GA‑400, with several parking garages nearby. From Hartsfield–Jackson Atlanta International Airport (ATL), around 15 miles south, a taxi or rideshare typically takes 20–30 minutes north along I‑75/85 N. Public transit users can take MARTA Rail to the Arts Center or Midtown stations (0.3–0.5 miles away) and walk easily, and numerous MARTA bus routes along Peachtree Street stop directly outside the entrance.
Atlanta, GA – The Proscenium
1170 Peachtree Street NE, Atlanta, United States, 30309
The venue is located in the heart of Midtown Atlanta in the Proscenium high–rise at 1170 Peachtree Street NE, easily accessible by car via I‑75/85 and GA‑400 with several parking garages nearby. Visitors arriving from Hartsfield–Jackson Atlanta International Airport (ATL), about 15 miles south, can expect a taxi or rideshare ride taking 20–30 minutes via I‑75/85 North. Public transit is seamless with MARTA Rail service; the Arts Center and Midtown stations are within walking distance (approximately 0.3–0.4 miles), and multiple MARTA bus routes also serve Peachtree Street.
Atlanta, GA – Regus at One Hartsfield
100 Hartsfield Centre Parkway, Suite 500, Atlanta, United States, 30354
The venue is located in the One Hartsfield Center office building, adjacent to Hartsfield–Jackson Atlanta International Airport, easily reached by car via I‑75/I‑85 or GA‑138, with abundant on-site parking. Visitors arriving from ATL airport can walk or take a shuttle to the building, or opt for a quick 2–3‑minute taxi or rideshare ride. Public transit users can board MARTA from the Airport Station and ride one stop to College Park Station, then catch a connecting shuttle or enjoy a brief walk of about half a mile.
Atlanta, GA – Regus at Peachtree
260 Peachtree Street NW, Suite 2200, Atlanta, United States, 30303
The venue is situated in the iconic Coastal States Building at 260 Peachtree Street in downtown Atlanta, accessible by car via I‑75/85 or I‑20 with convenient parking garages nearby. From Hartsfield–Jackson Atlanta International Airport (ATL), about 12 miles south, a taxi or rideshare along I‑75/85 North takes approximately 15–20 minutes. For public transit, MARTA rail users can disembark at Five Points Station and walk 0.5 miles northeast, or exit at Peachtree Center Station and walk two blocks north—both routes offering easy access.
Edge AI represents a technological approach focused on executing machine learning inference near data sources to ensure low-latency, efficient, and scalable processing for government and public sector applications.
This instructor-led live training, available online or on-site, targets intermediate to advanced practitioners seeking to deploy, orchestrate, and optimize AI workloads within Kubernetes-based edge environments for government and enterprise infrastructure.
Upon completion, participants will be equipped to:
Configure lightweight Kubernetes distributions for edge deployments.
Implement AI inference workloads across constrained edge nodes.
Address connectivity challenges and establish synchronization protocols.
Enhance performance, storage, and network operations for operational edge scenarios.
Course Format
Structured presentations accompanied by practical, real-world examples.
Scenario-based laboratory exercises and practical deployment tasks.
Direct hands-on interaction with Kubernetes edge frameworks.
Customization Options
Contact us to arrange a customized training program tailored to specific edge platform requirements.
Kubernetes serves as a standard container orchestration platform for the management of distributed applications at scale for government entities.
This instructor-led, live training program, available online or onsite, is designed for advanced practitioners seeking to leverage artificial intelligence and machine learning to optimize Kubernetes resource utilization, scheduling logic, and autoscaling strategies.
Upon completion of this program, participants will be equipped to:
Apply AI/ML models to enhance workload scheduling decisions within Kubernetes environments.
Utilize predictive analytics to refine the allocation of CPU, GPU, and memory resources.
Implement intelligent autoscaling mechanisms utilizing reinforcement learning and metric forecasting.
Decrease infrastructure costs and latency through automated resource optimization.
Format of the Course
Instructor-guided technical presentations and in-depth analytical discussions.
Hands-on laboratory work conducted on real Kubernetes clusters.
Practical exercises focused on applying AI models to realistic operational scenarios.
Course Customization Options
To align this course with specific platform configurations or operational requirements for government use, please contact our team for customization.
MLOps on Kubernetes serves as a structured framework for automating the training, validation, packaging, and deployment of machine learning models, utilizing containerized pipelines and GitOps workflows to support operations for government.
This instructor-led training session, available either online or onsite, is designed for intermediate-level professionals seeking to develop automated, scalable MLOps pipelines on Kubernetes.
Upon completion of this program, participants will be positioned to:
Architect end-to-end CI/CD pipelines tailored for machine learning operations.
Establish GitOps workflows to manage model deployment and versioning.
Automate the training, testing, and packaging of ML models.
Integrate comprehensive monitoring, alerting, and rollback strategies.
Course Delivery Format
Instructor-led presentations and detailed technical analyses.
Practical exercises focused on constructing operational CI/CD workflows.
Live-lab sessions involving the deployment of ML workloads to Kubernetes.
Customization Capabilities
Agencies may request tailored content that aligns with their specific internal MLOps tools and infrastructure requirements.
Kubeflow constitutes an open-source infrastructure intended to optimize the development, training, and deployment of machine learning operations on Kubernetes for government and public sector use.
This live, instructor-facilitated session, available remotely or in-person, targets professionals with foundational to intermediate experience who seek to establish secure and reliable machine learning workflows for government applications.
Upon successful completion of this instruction, participants will acquire the competency to:
Operate within the Kubeflow ecosystem and utilize its core modules.
Develop consistent and reproducible workflows utilizing Kubeflow Pipelines.
Execute scalable training operations on Kubernetes infrastructure.
Deliver machine learning models with high efficiency using the Kubeflow Serving framework.
Instructional Methodology
Structured presentations and facilitated collaborative dialogue.
Practical laboratory sessions utilizing actual Kubeflow components.
Applied exercises focused on constructing complete machine learning workflows.
Adaptation Options for Course Content
Tailored variations of this training program may be developed to accommodate specific agency technology stacks and mission requirements.
Continuous Integration and Continuous Delivery (CI/CD) for AI represents a systematic methodology for automating model packaging, testing, containerization, and deployment via integrated pipelines.
This instructor-led live training, available online or on-site, targets intermediate-level professionals seeking to automate comprehensive AI model delivery workflows using Docker and CI/CD platforms.
Upon completion, participants will be equipped to:
Develop automated pipelines for constructing and testing AI model containers.
Enforce version control and reproducibility standards across model lifecycles.
Incorporate automated deployment strategies for AI services for government operations.
Apply CI/CD best practices aligned with machine learning operations requirements.
Course Delivery Format
Instructor-led presentations and technical discourse.
Practical laboratories and hands-on implementation exercises.
Simulations of realistic CI/CD workflows within a controlled environment.
Course Customization Opportunities
For organizations requiring bespoke pipeline workflows or platform integrations, contact us to tailor this course.
This instructor-led, live training in Atlanta (available online or onsite) is intended for advanced-level Kubernetes administrators and DevOps engineers seeking to enhance their monitoring proficiency for Kubernetes clusters using Prometheus and Grafana for government operations.
Upon completion of this training, participants will be able to:
Deploy Prometheus and Grafana for Kubernetes monitoring.
Monitor essential metrics for pods, nodes, and services.
Construct 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 implementation involves executing AI inference across cloud, on-premise, and edge domains through standardized container-based procedures.
This instructor-led, live training module (available online or on-site) is designed for senior-level professionals seeking to architect and implement distributed AI inference systems across diverse environments.
Upon completion of this course, participants will possess the ability to:
Develop secure and scalable containerized AI services for multi-site environments.
Deploy AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
Integrate coordination tools to automate distributed AI operations for government purposes.
Enhance inference speed, dependability, and system resilience across varied infrastructure.
Course Delivery Structure
Structured presentations and expert-facilitated dialogue.
Substantial hands-on practice and applied laboratory exercises.
Practical experimentation within a controlled, live laboratory environment.
Course Adaptation Options
To modify this course to align with specific organizational infrastructure or operational use cases, please contact us to customize the training for government requirements.
Kubernetes serves as an open-source platform designed to automate the deployment, scaling, and administration of containerized applications.
This instructor-led, live training session (available online or onsite) is tailored for IT professionals with beginner to intermediate proficiency who seek to master the fundamental concepts and components of Kubernetes for managing containerized workloads at scale.
Upon completion of this training, participants will demonstrate the ability to:
Comprehend the architectural framework and constituent components of Kubernetes.
Deploy and oversee containers within a Kubernetes cluster environment.
Configure networking, storage, and scaling parameters for enterprise workloads.
Diagnose common operational issues and adhere to best practices for cluster governance.
Instructional Methodology
Interactive instruction and facilitated discussion.
Extensive practical exercises and skill reinforcement.
Direct implementation activities within a live-lab environment for government and public sector relevance.
Curriculum Customization Availability
To arrange a customized training program aligned with specific operational needs, please contact the administration to coordinate scheduling and content adjustments.
This instructor-led, live training conducted in Atlanta (online or on-site) is intended for DevOps engineers and developers who aim to leverage Kubernetes to build, deploy, and manage containers and cluster components within a secure and scalable environment for government.
Upon completion, participants will be equipped to:
Comprehend the architecture, fundamental concepts, and constituent elements of the Kubernetes ecosystem.
Establish, install, and configure Kubernetes clusters to support container orchestration.
Execute Kubernetes operational tasks through standard command-line interfaces.
Gain practical experience ranging from foundational to advanced Kubernetes operations and administration.
Docker is a containerization platform employed to establish portable, isolated, and secure deployment environments for AI inference services.
This live, instructor-led training, available online or onsite, is designed for technical professionals with beginner to intermediate proficiency who intend to develop secure, portable AI inference microservices that can be deployed consistently across local workstations, servers, or cloud virtual machines.
Upon completion of this course, participants will be equipped to:
Construct lightweight inference containers suitable for local and cloud environments.
Apply best-practice security measures to containerized AI services.
Establish portable microservice workflows for environmental consistency.
Deploy AI inference endpoints across varied infrastructure architectures.
Instructional Format
Structured lectures accompanied by practical demonstrations.
Practical exercises to reinforce deployment and security protocols.
Interactive laboratory sessions for constructing and executing portable inference services.
Customization Options for Government
To adapt this training to specific infrastructure or AI tooling requirements, please contact the provider for coordination.
This instructor-led, live training is conducted in Atlanta (available onsite or remotely). The curriculum focuses on deploying sample server applications within containers, followed by the automation, scaling, and management of these workloads within a Kubernetes cluster. The course addresses advanced operational topics, guiding participants through the critical processes of securing, networking, and monitoring Kubernetes clusters.
Upon completion, participants will be capable of:
Initializing and operating Docker containers.
Deploying containerized databases and server applications.
Establishing and configuring Docker and Kubernetes clusters.
Utilizing Kubernetes to manage distinct operational environments within a unified cluster.
Implementing security measures, scaling protocols, and monitoring systems for Kubernetes clusters.
GPU acceleration is a critical component for executing high-performance deep learning workloads with scalable and efficient resource management.
This instructor-led, live training program (available online or on-site) is designed for intermediate-level technical professionals tasked with configuring, optimizing, and executing GPU-enabled AI workloads within Docker containers for government use.
Upon completion of this course, participants will be equipped to:
Construct and execute GPU-enabled containers for both training and inference phases.
Configure CUDA, system drivers, and runtime libraries for containerized AI workflows.
Optimize resource allocation and enforce isolation protocols for GPU-intensive applications.
Deploy scalable, containerized deep learning services within production environments.
Course Delivery Format
Interactive instruction reinforced by practical, real-world demonstrations.
Exercise-based practice centered on GPU-enabled development standards.
Hands-on implementation conducted in a secure live-lab environment.
Course Customization Options
For tailored training aligned with specific infrastructure or GPU stack requirements, please contact us to arrange a schedule.
This instructor-led, live training in Atlanta (available online or onsite) is designed for intermediate-level technical professionals seeking to proficiently deploy, manage, and scale containerized workloads for government operations using Kubernetes.
Upon completion of this training, participants will be capable of:
Interpreting the Kubernetes architecture and its constituent components.
Implementing resource isolation strategies using Namespaces.
Managing and customizing workloads via Deployments, StatefulSets, and DaemonSets.
Defining computational resource constraints using Requests and Limits.
Implementing Jobs and CronJobs for automated task scheduling.
Understanding Services and DNS integration within the Kubernetes environment.
Exposing applications to external users via Ingress.
Managing ConfigMaps, Secrets, and Persistent Volumes.
Scaling and upgrading Kubernetes clusters utilizing advanced operational strategies.
Analyzing and resolving common Kubernetes operational issues.
Deploying resources efficiently using Helm Charts.
This instructor-led, live training in Atlanta (delivered online or on-site) is designed for intermediate to advanced developers, DevOps specialists, and architects aiming to design, deploy, and manage resilient applications utilizing microservices, containers, and continuous integration/continuous deployment (CI/CD) pipelines for government systems.
Upon completion of this training, participants will be equipped to:
Comprehend and implement microservices architecture.
Deploy and administer containerized applications using Docker and Kubernetes.
Configure and optimize CI/CD pipelines for automated deployment.
Apply established protocols for security, monitoring, and observability.
This instructor-led, live training session, available online or on-site, is intended for advanced platform engineers and DevOps professionals aiming to master application scaling via microservices and Kubernetes.
Upon completion of this training, participants will be capable of:
Designing and implementing scalable microservices architectures.
Deploying and managing applications on Kubernetes clusters.
Utilizing Helm charts for efficient service deployment.
Monitoring and maintaining the health of microservices in production.
Applying best practices for security and compliance in a Kubernetes environment.
Acquire a solid understanding of container fundamentals, Kubernetes, and OpenShift through a practical, hands-on training program tailored for developers, DevOps engineers, and IT professionals. Participants will master the processes of building containerized applications, deploying workloads, administering Kubernetes resources, and leveraging OpenShift to enhance modern application delivery across cloud and hybrid infrastructure for government and enterprise sectors.
Docker serves as a containerization technology enabling the creation of consistent, portable, and scalable environments for machine learning systems in the public sector.
This instructor-led training session, available remotely or in person, targets intermediate to advanced technical staff seeking to containerize and operationalize full-scale machine learning pipelines for government use.
Upon successfully completing this course, participants will be equipped to:
Encapsulate machine learning training, validation, and inference tasks.
Design and manage comprehensive machine learning workflows using Docker and complementary tools.
Establish version control, reproducibility, and CI/CD practices for machine learning components.
Deploy, oversee, and scale machine learning services within containerized frameworks.
Course Format
Interactive instruction accompanied by practical application demonstrations.
Practical exercises centered on developing functional machine learning pipeline elements.
Live laboratory sessions for executing end-to-end containerized operations.
Customization Opportunities
To align training with specific government machine learning infrastructure requirements, please contact the provider for detailed options.
This instructor-led training in Atlanta provides intermediate professionals with the skills to containerize AI and ML workloads using Docker. Participants will acquire the knowledge to build optimized images, manage dependencies, and deploy reliable pipelines, developing hands-on competencies for consistent and portable production environments.
This instructor-led, live training, conducted in Atlanta (either online or onsite), is designed for beginner-level developers aiming to acquire foundational knowledge of Kubefirst and understand how it streamlines, secures, and accelerates the management of Kubernetes and Swarm clusters at enterprise scale.
Upon completion of this training, participants will be capable of the following:
Establishing a functional Kubefirst development environment.
Authoring and executing a foundational Kubefirst program.
Annotating source code with appropriate Kubefirst directives and clauses.
Utilizing the Kubefirst API and associated libraries.
Conducting profiling and debugging activities for Kubefirst programs.
This instructor-led, live training in Atlanta (available online or on-site) is directed at intermediate-level developers and DevOps engineers intending to utilize Minikube within their development workflows.
Upon completion of this training, participants will be able to:
Configure and administer a local Kubernetes environment using Minikube.
Understand the deployment, management, and debugging of applications on Minikube.
Integrate Minikube into continuous integration and deployment pipelines.
Optimize development processes by leveraging Minikube’s advanced features.
Apply established best practices for local Kubernetes development.
This instructor-led, live training program in Atlanta (available online or onsite) is tailored for intermediate-level system administrators aiming to deploy, manage, and resolve issues in Hyper-V environments for government use.
Upon completion, participants will be capable of:
Comprehending virtualization principles and configuring Hyper-V.
Creating and managing virtual machines, storage systems, and network configurations.
Implementing advanced Hyper-V features and securing environments for government standards.
Monitoring performance and optimizing resource efficiency.
This instructor-led, live training in Atlanta (online or onsite) is directed at intermediate-level developers and DevOps engineers seeking to build, deploy, and manage microservices using Spring Cloud and Docker.
Upon completion of this training, participants will be capable of:
Developing microservices using Spring Boot and Spring Cloud frameworks.
Containerizing applications with Docker and Docker Compose.
Implementing service discovery, API gateways, and inter-service communication mechanisms.
Monitoring and securing microservices in production environments.
Deploying and orchestrating microservices using Kubernetes.
This instructor-led, live training session, offered in Atlanta (online or onsite), is designed for entry-level to mid-level software developers and DevOps specialists seeking to acquire proficiency in establishing and administering local Kubernetes infrastructure using Minikube for government and public sector operations.
Upon successful completion of this program, participants will be equipped to:
Execute the installation and configuration of Minikube on designated local systems.
Demonstrate a comprehensive understanding of Kubernetes fundamental concepts and structural design.
Execute the deployment and management of containerized workloads using kubectl and the Minikube dashboard.
Configure durable storage frameworks and network connectivity solutions within a Kubernetes environment.
Leverage Minikube for the rigorous development, testing, and diagnostic assessment of applications for government systems.
In this instructor-led training session held in Atlanta (onsite or remote), participants will acquire the technical proficiency to create and manage Docker containers, including the deployment of representative applications. The curriculum further instructs on the automation, scaling, and governance of containerized applications within a Kubernetes cluster. The training concludes with advanced topics, guiding participants through the rigorous processes of securing, scaling, and monitoring Kubernetes clusters to meet operational standards.
Upon completion of this training, participants will possess the following capabilities:
Initialization and execution of Docker containers.
Deployment of containerized server and web application stacks.
Construction and administration of Docker image repositories.
Configuration of Docker and Kubernetes cluster infrastructures.
Application of Kubernetes to deploy and oversee clustered web services.
Enforcement of security protocols, scaling adjustments, and continuous monitoring of Kubernetes clusters.
The Certified Kubernetes Administrator (CKA) program is established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF).
Kubernetes has emerged as a predominant platform for container orchestration.
NobleProg has provided Docker and Kubernetes training since 2015. With over 360 successfully completed training engagements, the organization is recognized globally for its expertise in containerization.
Since 2019, NobleProg has supported clients in validating their technical proficiency within Kubernetes environments by facilitating preparation for the CKA and CKAD examinations.
This instructor-led, live training session (available online or onsite) is designed for System Administrators and Kubernetes practitioners who seek to validate their competencies through the CKA examination.
Furthermore, the curriculum emphasizes practical experience in Kubernetes administration; therefore, participation is recommended for individuals seeking to enhance operational capabilities, irrespective of their intent to pursue CKA certification for government initiatives.
Course Format
Interactive instructional sessions and discussions.
Extensive exercises and practical application.
Hands-on implementation within a live-lab environment.
Course Customization Options
Requests for customized training programs for this course may be directed to NobleProg for scheduling.
Detailed information regarding CKA certification is available at: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka
This instructor-led live training, delivered in Atlanta (online or onsite), provides the knowledge required to establish and manage production-scale container environments utilizing Kubernetes on AKS.
Upon completion, participants will be proficient in:
Configuring and managing Kubernetes on AKS.
Deploying, monitoring, and scaling Kubernetes clusters.
Implementing containerized (Docker) applications on Azure.
Migrating existing Kubernetes environments from on-premise to the AKS cloud.
Integrating Kubernetes with third-party continuous integration (CI) platforms.
Ensuring high availability and disaster recovery capabilities 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 for government and troubleshoot applications across development and production environments.
This instructor-led, live training program (available online or onsite) is designed for engineers tasked with automating, securing, and monitoring containerized applications within a large-scale Kubernetes cluster environment for government operations.
Upon completion of this training, participants will demonstrate the ability to:
Leverage Kubernetes to deploy and manage diverse operational environments within a unified cluster
Implement security protocols, scaling strategies, and monitoring capabilities for the Kubernetes cluster
Instructional Methodology
Interactive technical lectures and facilitated discussions
Extensive practical exercises and skill application drills
Hands-on implementation in a live laboratory environment
Course Customization Services
Organizations seeking tailored training programs for government agencies should contact our team to discuss specific requirements and scheduling.
This instructor-led CKAD training in Atlanta prepares developers for the Certified Kubernetes Application Developer examination through practical laboratory exercises. It covers the design, development, and security of cloud-native applications for government use, utilizing core Kubernetes concepts, deployment strategies, and networking fundamentals.
This instructor-led, live training course for government in Atlanta offers an overview of Rancher and demonstrates, through practical exercises, the deployment and management of a Kubernetes cluster.
Istio is an open-source service mesh platform deployed on Kubernetes that facilitates secure, observable, and manageable connectivity among microservices. By utilizing Istio’s Envoy-based sidecar proxies, organizations can enforce governance policies, secure data exchanges via mTLS, achieve comprehensive traffic observability, and enhance system reliability for government and enterprise workloads.
This instructor-led training session, available in online or onsite formats, is designed for intermediate-level technical staff seeking to deploy, secure, and manage microservices applications utilizing Istio on Kubernetes.
Upon completion of this training, participants will demonstrate the ability to:
Install and configure Istio within Kubernetes cluster environments.
Apply service mesh concepts including traffic governance, security enforcement, and observability.
Deploy microservices applications integrated with an Istio service mesh.
Secure inter-service communications using mutual TLS (mTLS) and Zero Trust frameworks.
Monitor, trace, and diagnose microservices using Prometheus, Grafana, and Jaeger.
Integrate Istio with Calico to enforce advanced network policies and security controls.
Training Delivery Format
Interactive instructional sessions and facilitated discussions.
Extensive practical exercises and scenario-based practice.
Hands-on implementation within a controlled live-lab environment.
Customization Options for Training
Requests for customized curricula specific to agency needs should be directed to the training coordination team for arrangement.
This 21-hour training in Atlanta provides an in-depth exploration of essential Kubernetes design patterns for microservices. Participants will acquire foundational, behavioral, structural, and configuration strategies to build resilient, scalable, and cloud-native applications, supported by hands-on live-lab exercises.
This instructor-led, live training in Atlanta (online or onsite) is tailored for engineers aiming to employ Helm to streamline the deployment and administration of Kubernetes applications within government operations.
By the conclusion of this training, participants will be equipped to:
Install and configure Helm.
Establish reproducible builds for Kubernetes applications.
Distribute applications via Helm charts.
Deploy third-party applications encapsulated in Helm charts.
This instructor-led, live training session, offered in Atlanta (online or onsite), is designed for DevOps engineers aiming to utilize Kubernetes and GitLab to automate the DevOps lifecycle for government operations.
By the conclusion of this training, participants will be equipped to:
Automate application builds, testing cycles, and deployment processes.
Construct an automated build infrastructure for public sector use.
Deploy applications to containerized cloud environments with precision.
This instructor-led, live training program in Atlanta (available online or on-site) is designed for Kubernetes practitioners seeking to prepare for the CKS examination.
Upon completion of this training, participants will possess the knowledge to secure Kubernetes environments and container-based applications across various stages of the application life cycle, including build, deployment, and runtime.
This instructor-led, live training in Atlanta (online or onsite) is designed for developers and DevOps engineers responsible for utilizing serverless approaches to build enterprise applications in Kubernetes.
Upon completion of this training, participants will be prepared to:
Configure and establish Kubernetes systems to initiate development within a serverless architecture.
Comprehend the foundational concepts and governing principles of serverless environments.
Execute necessary toolchains for serverless development and integrate them with core Kubernetes components.
Apply Python programming skills to implement and manage serverless systems for government workflows.
Implement security controls for enterprise applications deployed via serverless frameworks on Kubernetes.
Leverage modern cloud computing techniques to optimize DevOps task processing and workflow efficiency.
This instructor-led, live training in Atlanta (delivered online or onsite) is designed for engineers seeking to fortify a Kubernetes cluster beyond its default security parameters.
Upon completion of this training, participants will be equipped to:
Identify vulnerabilities present in a standard Kubernetes installation.
Prevent unauthenticated access to the Kubernetes API, database, and other services.
Safeguard a Kubernetes cluster from accidental or malicious intrusion.
Develop a comprehensive security policy and adhere to best practices.
The "Advanced Docker and Kubernetes" instruction offers a thorough analysis of the Kubernetes platform and its surrounding ecosystem. Tailored for participants with varied levels of technical proficiency, the curriculum covers a complete spectrum of fundamental and advanced features. The course addresses essential concepts including Pods, Labels, Controllers, Services, Secrets, Persistent Data Volumes, Claims, Namespaces, and Resource Quotas. It further examines the Container Networking Model, Service Discovery, Scaling mechanisms, and Load Balancing strategies. Additional topics include Cluster Management, Kubernetes installation procedures, security protocols for cluster protection, access control frameworks, High Availability of the Control Plane, monitoring and logging standards, automatic application scaling, advanced scheduling logic, microservices-based application architectures, specific application design patterns, and the deployment of applications and services on a Kubernetes cluster for government use.
This instructor-led, live training conducted in Atlanta (either online or on-site) is designed for engineers aiming to deepen their expertise in Docker to support the deployment of applications at scale while maintaining robust control.
Upon completion of this training, participants will be equipped to:
Construct custom Docker images.
Deploy and manage large-scale Docker applications.
Evaluate diverse container orchestration solutions to determine the most suitable framework.
Implement continuous integration workflows for Docker applications.
Integrate Docker applications into existing continuous tool integration processes.
Enhance the security posture of Docker applications.
This seven-day program offers a comprehensive, hands-on approach to the design, deployment, and operation of cloud-native applications, incorporating modern DevOps best practices suitable for government use.
Participants will examine methods for designing scalable microservices architectures, optimizing container environments, and managing production workloads within Kubernetes. The curriculum covers advanced deployment strategies, GitOps-driven automation, and observability frameworks essential for ensuring system reliability and performance.
Emphasis is placed on addressing real-world operational challenges, including incident response, failure simulation, and root cause analysis. The program concludes with the integration of AI-powered tools to support troubleshooting and accelerate operational decision-making processes.
Upon completion of the training, participants will possess a clear understanding of how to build, deploy, monitor, and maintain resilient distributed systems within a Kubernetes-based infrastructure.
Docker is an open-source platform designed to automate the construction, distribution, and execution of applications within containerized environments.
This instructor-led, live training (conducted online or on-site) is intended for engineers seeking to utilize Docker for the deployment and administration of software as containers, replacing traditional standalone software models for government use.
Upon completion of this training, participants will be capable of the following:
Installation and configuration of Docker environments.
Implementation of software containerization strategies.
Management of Docker-based applications.
Networking of Docker applications and system components.
Interpretation and modification of Docker registries.
Training Delivery Format
Interactive instruction and facilitated discussion.
Extensive exercises and practical application.
Hands-on implementation within a live laboratory environment.
Customization Options for Training
To request a customized training curriculum for this course, please contact the relevant office for coordination.
To access additional information regarding Docker, please visit: https://www.docker.com
This instructor-led, live training session in Atlanta (available online or onsite) is intended for intermediate to advanced DevOps engineers and system administrators responsible for deploying and managing self-hosted Kubernetes clusters for government use without reliance on commercial cloud dependencies.
Upon completion, participants will be capable of: deploying production-ready Kubernetes clusters using kubeadm on bare-metal or virtual machines; configuring high-availability control planes and etcd clusters; implementing container networking and storage for self-managed environments; and establishing monitoring and observability using self-hosted solutions.
In this instructor-led, live training session conducted in Atlanta, participants will acquire the essential skills for constructing microservices utilizing Spring Cloud and Docker. Learning outcomes are validated through rigorous exercises and the systematic development of sample microservice components.
Upon completion of this program, participants will be capable of:
Analyzing the core principles of microservice architecture.
Employing Docker to engineer containerized environments for microservice applications.
Implementing and deploying containerized microservices using Spring Cloud and Docker frameworks.
Establishing integration between microservices, discovery services, and the Spring Cloud API Gateway.
Conducting comprehensive end-to-end integration testing via Docker Compose.
OpenShift is a prominent Kubernetes-based platform for the deployment and management of containerized applications within cloud, hybrid, and on-premises environments.
This practical training provides participants with the skills to install, administer, and troubleshoot OpenShift clusters while adhering to security, networking, and storage standards. Through applied exercises, participants acquire the capabilities necessary to confidently manage production-grade OpenShift environments for government.
Red Hat OpenShift Administration II: Configuring a Production Cluster (DO280) provides OpenShift Cluster Administrators with the essential skills to manage daily operational tasks on clusters supporting applications from internal and external sources. The course instructs administrators on implementing role-based self-service models and deploying applications with specific privilege requirements, such as CI/CD tools, monitoring systems, and security scanners. Primary emphasis is placed on configuring multi-tenancy, enforcing security controls, and managing operator-based extensions within OpenShift for government use cases.
Acquire the skills to develop, deploy, and manage containerized applications using OpenShift, a premier Kubernetes-based platform for cloud-native development. This practical training encompasses application deployment, containerization, networking, CI/CD, and DevOps workflows, equipping participants with the capabilities to build and maintain modern applications in production environments for government use.
This advanced Atlanta course covers storage, backup, high availability, and security in Proxmox VE. Through practical exercises, participants learn to manage clusters, integrate Ceph and ZFS, and implement effective and secure disaster recovery strategies.
This instructor-led, live training in Atlanta (delivered online or on-site) is intended for intermediate-level virtualization administrators seeking to utilize open-source platforms to transition away from VMware.
Upon completion 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 protocols.
Optimize performance in open-source virtualization environments.
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Testimonials (7)
multi-tiered, structured course programme.
Bert Paelinckx - Cube SoftwareSolutions
Course - Introduction to Docker
CI/CD Best Practices (gitflow and gitops), Application strategies, idempotency and drift, remote state management, Pod Disruption Budgets and Best Practices
McKayla Fusco - NSWC Dahlgren Division - DNA
Course - Resilient Architecture: Microservices, Containers, and CI/CD
basic understanding of container/kubernetes and how they interact
features of the openshift plattform
Eric Scholze - NOW IT GmbH
Course - Introduction to Containers, Kubernetes & OpenShift
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
The training met expectations with its clear explanations, real-world examples, and hands-on labs that made complex topics easy to understand. It provided valuable insights into container orchestration, security, scaling and many other advanced topics.
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