Building Microservices with Spring Cloud and Docker 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 platform that facilitates consistent, portable, and reproducible operational environments for artificial intelligence and machine learning tasks.

This instructor-led, live training program (available online or onsite) is designed for intermediate-level professionals seeking to standardize the packaging of machine learning codebases, dependencies, and models using Docker for reliable development-to-production workflows.

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

• Construct and maintain Docker images specifically tailored for artificial intelligence and machine learning applications.
• Standardize machine learning pipelines, tools, and dependencies through containerization.
• Enhance Docker environments to optimize performance and ensure portability.
• Deploy containerized machine learning services across diverse runtime environments.

Course Delivery Method

• Conceptual demonstrations accompanied by structured professional discussion.
• Practical exercises emphasizing real-world containerization objectives.
• Applied implementation utilizing live-lab Docker environments.

Customization Options for Organizational Needs

• To adapt this training to meet specific organizational requirements, please contact us to coordinate.

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 platform for establishing reproducible, portable, and scalable environments for ML systems.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced technical professionals seeking to containerize and operationalize end-to-end ML pipelines using Docker.

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

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

Instructional Format

• Interactive lectures accompanied by practical demonstrations.
• Hands-on exercises dedicated to constructing functional ML pipeline components.
• Live-lab implementation for end-to-end containerized workflows.

Customization Options

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

Graphical processing unit acceleration is critical for executing high-performance deep learning tasks in a scalable and resource-efficient framework.

This instructor-led, live training program (delivered online or on-site) is designed for intermediate-level technical specialists intending to configure, optimize, and operate GPU-enabled artificial intelligence workloads within Docker container environments.

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

• Construct and execute containers with graphical processing capabilities for both training and inference phases.
• Configure CUDA, drivers, and runtime libraries to support containerized artificial intelligence workflows for government applications.
• Optimize resource allocation and isolation strategies for applications with intensive graphical processing requirements.
• Deploy scalable, containerized deep learning services suitable for production environments.

Course Delivery Methodology

• Interactive instruction reinforced by practical, real-world demonstrations.
• Exercise-based practical sessions centered on graphical processing unit-enabled development.
• Direct implementation activities conducted within a live laboratory environment.

Customization Options for the Course

• For training specifically aligned with your infrastructure or graphical processing stack, please contact our office for coordination.

This facilitated instructional program in US (virtual or location-based) is designed for mid-level Java engineers seeking to engineer, implement, operate, and sustain application architectures leveraging microservices through Spring Boot and Spring Cloud. This curriculum is intended for government audiences.

Upon completion, learners will be equipped to:

• Comprehend the foundational concepts and advantages inherent in microservices design.
• Create and release microservices utilizing Java and the Spring Boot framework.
• Execute service discovery protocols, centralized configuration administration, and API gateway implementations.
• Ensure the security, observability, and scalability of microservice deployments.
• Orchestrate microservice containerization and deployment via Docker and Kubernetes environments.

This instructor-led, live training in US (online or onsite) is designed for intermediate-level developers and DevOps engineers who intend to build, deploy, and manage microservices utilizing Spring Cloud and Docker. This program provides essential knowledge for government applications.

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

• Creating microservices with Spring Boot and Spring Cloud.
• Containerizing applications using Docker and Docker Compose.
• Configuring service discovery, API gateways, and inter-service communication.
• Monitoring and securing microservices within production environments.
• Deploying and orchestrating microservices via Kubernetes.