Hybrid AI Deployment: Docker, Cloud, and Edge Integration Training Course

This instructor-led, live training session, available via US (online or onsite), is designed for engineering professionals seeking to expand their expertise in Docker. The program focuses on deploying applications at scale while ensuring strict operational control.

Upon completion of this coursework, participants will be equipped to:

• Create custom Docker images.
• Deploy and manage a high volume of Docker-based applications.
• Assess various container orchestration platforms and select the optimal solution for their environment.
• Establish continuous integration workflows specifically for Docker deployments.
• Integrate Docker solutions with existing continuous integration frameworks, providing robust tools for government agencies.
• Implement security best practices to protect Docker applications.

Upon completion of this instructional module, participants will demonstrate proficiency in the following areas:

• Construct custom Docker container images.
• Deploy and manage high volumes of Docker-based applications.
• Assess various container orchestration platforms to select the most appropriate solution for organizational needs.
• Establish continuous integration workflows tailored for Docker environments.
• Integrate Docker applications with existing CI/CD toolchains.
• Implement security best practices for Docker workloads.
• Utilize Kubernetes to deploy and manage diverse environments within a single cluster.
• Secure, scale, and monitor Kubernetes clusters effectively.

Docker serves as a containerization framework that facilitates the creation of consistent, portable, and reproducible environments for artificial intelligence and machine learning applications.

This instructor-led training session, available online or at a designated location, is designed for intermediate-level practitioners seeking to package ML codebases, dependencies, and models using Docker to ensure reliable transitions from development to production within government operations.

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

• Constructing and managing Docker images specifically optimized for AI and ML initiatives.
• Containerizing machine learning pipelines, tools, and associated dependencies.
• Enhancing Docker environments to improve performance and portability for government use cases.
• Deploying containerized ML services across diverse runtime environments.

Course Delivery Format

• Conceptual demonstrations accompanied by guided analysis.
• Practical exercises targeting real-world containerization requirements.
• Implementation strategies utilizing live-lab Docker environments.

Customization for Government Entities

• To tailor this training to your specific organizational needs, please contact us to arrange a schedule that fits government workflows.

Continuous Integration and Continuous Delivery for artificial intelligence represents a systematic methodology for automating the packaging, validation, containerization, and deployment of models through established CI/CD pipelines.

This instructor-led program, available in online or onsite formats, targets intermediate professionals seeking to automate end-to-end AI model delivery processes utilizing Docker and CI/CD platforms.

Upon completion of this training, participants will demonstrate the ability to:

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

Course Format

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

Customization Options

• For government entities requiring customized pipeline workflows or specific platform integrations, please contact us to tailor this course.

The Certified Kubernetes Administrator (CKA) credential is administered by The Linux Foundation in partnership with the Cloud Native Computing Foundation (CNCF).

Kubernetes has established itself as a premier platform for container orchestration.

NobleProg has provided Docker and Kubernetes instruction since 2015. Having successfully completed over 360 training initiatives, the organization is recognized globally as a leading provider of expertise in containerization solutions for government and public sector workflows.

Since 2019, we have assisted clients in validating their Kubernetes proficiency by preparing them for the CKA and CKAD certification examinations.

This instructor-led live training, available either online or onsite, is designed for system administrators and Kubernetes practitioners seeking to validate their expertise through the CKA examination process.

Additionally, the curriculum emphasizes practical administrative skills; therefore, participation is recommended even for those who do not plan to pursue official certification.

Course Format

• Interactive lectures and facilitated discussions.
• Extensive exercises and practice opportunities.
• Hands-on implementation within a live laboratory environment.

Customization Options

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

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

This instructor-led live training, available online or on-site, is designed for Developers seeking to validate their proficiency in designing, building, configuring, and exposing cloud native applications within Kubernetes environments.

Furthermore, the program emphasizes practical application development skills; participation is recommended for professional development, regardless of an intent to sit for the CKAD examination.

NobleProg has provided Docker and Kubernetes training since 2015. With over 360 successfully completed projects, the organization has become a leading provider globally in containerization education. Since 2019, we have assisted clients in demonstrating their capabilities within k8s environments by preparing them to pass the CKA and CKAD exams.

Course Format

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

Customization Options

• To arrange customized training for this course, please contact our team.
• For additional information regarding CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

This professional development resource is designed for government agencies and contractors seeking to enhance their technical capabilities.

Docker provides an open-source framework designed to automate the construction, distribution, and execution of applications within containerized environments.

This instructor-led live training, available online or on-site, is intended for engineering personnel seeking to utilize Docker for deploying and managing software as containers rather than relying on conventional standalone architectures. The program supports federal workforce development for government entities and their contractors.

Upon completion of this curriculum, participants will be equipped to:

• Install and configure the Docker platform.
• Comprehend and apply software containerization principles.
• Administer applications built on Docker technology.
• Establish network connectivity among Dockerized applications and systems.
• Navigate and modify Docker registries.

Course Structure

• Incorporates interactive lectures and policy-aligned discussions.
• Features extensive exercises and practical application.
• Provides hands-on implementation within a secure live-lab environment.

Customization Availability

• To request a tailored training module for this course, please contact the administration to arrange logistics.
• For additional information regarding Docker capabilities, visit: https://www.docker.com

This comprehensive five-day instructional program provides federal personnel with the necessary expertise to construct, implement, and manage containerized infrastructure utilizing Docker, Kubernetes, and OpenShift technologies. The curriculum delivers rigorous, practical instruction on critical domains including container image management, Kubernetes workload orchestration, cluster networking configurations, persistent storage solutions, security protocols, monitoring frameworks, and operational administration of OpenShift environments. By completing this training for government professionals, attendees will acquire the competencies required to sustain contemporary container platforms and effectively diagnose application issues within both development and production workflows.

During this instructor-led live training conducted in US (either onsite or remotely), attendees will acquire the skills necessary to create and administer Docker containers and subsequently deploy a sample application within such an environment. The curriculum also covers the automation, scaling, and management of containerized workloads within a Kubernetes cluster. Furthermore, the instruction addresses advanced subjects, guiding participants through the procedures for securing, expanding capacity, and monitoring Kubernetes infrastructure. This comprehensive approach ensures that personnel are equipped with the technical expertise required for effective government operations and is designed specifically for government use cases.

Upon completion of this course, participants will demonstrate the ability to:

• Configure and operate Docker containers.
• Deploy containerized servers and web-based applications.
• Construct and oversee Docker images.
• Establish a combined Docker and Kubernetes cluster environment.
• Utilize Kubernetes to deploy and manage clustered web applications.
• Implement security measures, scaling protocols, and monitoring systems for a Kubernetes cluster.

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

This instructor-led live training, available via online or onsite delivery, targets intermediate to advanced technical personnel seeking to containerize and operationalize end-to-end machine learning pipelines utilizing Docker technology. The program is structured to meet the specific requirements for government agencies adopting these methodologies.

Upon successful completion of this instruction, participants will demonstrate proficiency in:

• Containerizing machine learning training, validation, and inference workloads.
• Designing and orchestrating complete machine learning pipelines using Docker and complementary tools.
• Implementing version control, reproducibility standards, and continuous integration/continuous deployment (CI/CD) for machine learning components.
• Deploying, monitoring, and scaling machine learning services within containerized infrastructures.

Course Format

• Interactive lectures supplemented by practical demonstrations.
• Hands-on exercises focused on constructing real-world machine learning pipeline components.
• Live laboratory sessions for implementing end-to-end containerized workflows.

Customization Options

• For tailored training aligned with specific machine learning infrastructure requirements, please contact the program administrators to discuss available options.

Graphics processing unit (GPU) acceleration is a critical component for executing high-performance deep learning workloads in a scalable and efficient manner within federal IT environments.

This instructor-led live training, available in online or onsite formats, targets intermediate technical personnel responsible for configuring, optimizing, and deploying GPU-enabled artificial intelligence workloads within Docker containers for government applications.

Upon completion of this course, participants will demonstrate the ability to:

• Construct and operate GPU-accelerated containers to support training and inference processes.
• Configure CUDA, device drivers, and runtime libraries to support containerized AI operations.
• Optimize resource allocation and isolation protocols for GPU-intensive applications.
• Deploy scalable, containerized deep learning services within production-grade environments.

Course Structure

• Interactive instruction reinforced by practical demonstrations.
• Exercise-focused practice emphasizing GPU-enabled development techniques.
• Practical implementation through a live-lab simulation environment.

Customization Options

• To arrange customized training aligned with specific agency infrastructure or GPU stack requirements, please contact the training provider.

This instructor-led live training, offered in US via onsite or remote delivery, provides participants with the skills to deploy sample servers within containers and automate their scaling and management within a Kubernetes environment. The curriculum further addresses advanced operational requirements, guiding attendees through essential processes for securing, networking, and monitoring a Kubernetes cluster. This program is designed for government audiences requiring robust infrastructure management capabilities.

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

• Establish and operate Docker containers.
• Deploy containerized databases and server applications.
• Configure integrated Docker and Kubernetes clusters.
• Leverage Kubernetes to orchestrate multiple environments within a single cluster.
• Implement security protocols, scaling strategies, and monitoring systems for Kubernetes clusters.

This instructor-led, hands-on training session in US provides a comprehensive overview of developing microservices architectures via Spring Cloud and Docker. The curriculum blends theoretical concepts with practical application, requiring participants to demonstrate competency through guided exercises and the sequential creation of sample microservice components.

Upon completion of this program, attendees will be equipped to:

• Demonstrate a foundational understanding of microservices principles.
• Utilize Docker to construct containers for microservice-based applications.
• Develop and deploy containerized microservices utilizing Spring Cloud and Docker technologies.
• Implement integrations between microservices, discovery mechanisms, and the Spring Cloud API Gateway.
• Conduct end-to-end integration testing through the use of Docker Compose.