Introduction to Docker Training Course

This instructor-led, live training in US (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.

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.

The implementation of Continuous Integration and Continuous Delivery (CI/CD) for artificial intelligence constitutes a systematic methodology for automating the packaging, validation, containerization, and deployment of machine learning models. This instructor-led professional development program, available in online or onsite formats, is designed for mid-career practitioners seeking to streamline end-to-end AI model delivery through Docker integration and CI/CD frameworks. Upon successful completion of the curriculum, participants will demonstrate proficiency in: * Establishing automated workflows for the construction and testing of AI model containers. * Enforcing version control standards and reproducibility measures throughout the model lifecycle. * Executing automated deployment strategies for AI-driven services. * Applying CI/CD best practices specifically aligned with machine learning operations (MLOps). **Instructional Format** * Instructor-facilitated technical briefings and analytical discussions. * Interactive laboratory sessions involving hands-on implementation exercises. * Simulated CI/CD workflow operations conducted within a secure, controlled environment. **Program Adaptation** Organizations requiring bespoke pipeline configurations or specific platform integrations are encouraged to contact program administrators to arrange tailored training solutions for government and enterprise needs.

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

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 comprehensive five-day instructional module provides federal personnel with the technical competencies required to construct, deploy, and manage containerized infrastructure utilizing Docker, Kubernetes, and OpenShift. The curriculum focuses on essential operational domains, including container image management, workload orchestration, cluster networking protocols, persistent storage solutions, security postures, monitoring mechanisms, and practical OpenShift administration. Designed for government agencies seeking to modernize their IT architecture, this training equips participants with the expertise necessary to maintain robust container platforms and resolve application incidents across diverse development and production lifecycle phases.

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.

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.

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

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.

The strategic implementation of hybrid artificial intelligence involves executing inference tasks across distributed cloud, on-premises, and edge infrastructures through standardized containerized workflows. This professional development opportunity, available in online or onsite formats for government teams, targets senior technical specialists tasked with architecting and managing complex AI systems within heterogeneous operational environments.

Upon successful completion of this curriculum, participants will demonstrate the capability to:

• Develop secure, scalable containerized AI services tailored for multi-site deployments.
• Deploy AI inference workloads across cloud platforms, local server farms, and edge devices utilizing Docker technologies.
• Implement orchestration frameworks to automate and manage distributed AI operations.
• Enhance inference latency, system reliability, and operational resilience across diverse infrastructure landscapes.

Instructional Methodology

• Federated presentations and expert-led technical discussions.
• Comprehensive hands-on laboratories and applied practical exercises.
• Simulation of real-world operational scenarios within a controlled live-lab environment.

Program Customization

• To align this training with specific agency infrastructure requirements or mission use cases, please contact our coordination team for customized solutions for government applications.

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

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