Kubernetes Training in Radom

Edge AI is a paradigm focused on running machine learning inference close to data sources to achieve low-latency, efficient, and scalable processing.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level practitioners who wish to deploy, orchestrate, and optimize AI workloads on Kubernetes-based edge environments.

By completing this course, participants will be able to:

• Set up lightweight Kubernetes distributions for edge deployments.
• Deploy AI inference workloads effectively across constrained edge nodes.
• Manage connectivity challenges and synchronization patterns.
• Optimize performance, storage, and networking for real-world edge scenarios.

Format of the Course

• Guided presentations supported by real-world examples.
• Scenario-based labs and practical edge deployment exercises.
• Hands-on experience with Kubernetes edge frameworks.

Course Customization Options

• To request a customized training tailored to your edge platform needs, 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 AI and machine learning techniques to optimize Kubernetes resource usage, scheduling decisions, and autoscaling strategies.

At the completion of this program, participants will be able to:

• Apply AI/ML models to improve 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 cost 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, please contact us for customization.

MLOps on Kubernetes is a framework for automating the training, validation, packaging, and deployment of machine learning models using containerized pipelines and GitOps workflows.

This instructor-led, live training (online or onsite) is aimed at intermediate-level practitioners who wish to build automated, scalable MLOps pipelines on Kubernetes.

After completing 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 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.

Kubeflow is an open-source platform designed to streamline building, training, and deploying machine learning workloads on Kubernetes.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to build reliable ML workflows using Kubeflow.

Upon completion of this training, attendees will gain the skills to:

• Navigate the Kubeflow ecosystem and 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.

Kubernetes is a scalable platform for deploying, serving, and managing machine learning models in production environments.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to operationalize ML models reliably on Kubernetes.

Upon completing this training, participants will gain the skills to:

• Containerize and prepare ML models for efficient deployment.
• Serve models using modern inference frameworks.
• Optimize workloads with autoscaling, GPU configuration, and resource tuning.
• Implement model rollout strategies such as A/B testing and canary deployments.

Format of the Course

• Blended lecture, architectural analysis, and guided discussion.
• Extensive practical exercises with real-world deployment scenarios.
• Hands-on implementation using a live Kubernetes environment.

Course Customization Options

• If you need this course tailored to your environment or toolchain, please contact us to discuss customization options.

This instructor-led, live training in Radom (online or onsite) is aimed at advanced-level Kubernetes administrators and DevOps engineers who wish to enhance their monitoring skills for Kubernetes clusters using Prometheus and Grafana.

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

• Set up Prometheus and Grafana for Kubernetes monitoring.
• Monitor key metrics for pods, nodes, and services.
• Create 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.

Kubernetes is an open-source platform for automating deployment, scaling, and management of containerized applications.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level IT professionals who wish to learn the core concepts and components of Kubernetes and use it to manage containerized applications at scale.

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

• Understand Kubernetes architecture and components.
• Deploy and manage containers in a Kubernetes cluster.
• Configure networking, storage, and scaling for workloads.
• Troubleshoot common issues and follow best practices for cluster operations.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Radom (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.

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 the command line tools.
• Get a hands-on experience from basic to advanced Kubernetes operations and administration.

In this instructor-led, live training in Radom (onsite or remote), participants will learn how to deploy a collection of sample servers inside containers, then automate, scale, and manage their containerized servers within a Kubernetes cluster. The training goes on to more advanced topics, walking participants through the process of securing, networking and monitoring a Kubernetes cluster.

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

• Set up and run a Docker container.
• Deploy containerized databases and servers.
• Set up a Docker and Kubernetes cluster.
• Use Kubernetes to deploy and manage different environments under the same cluster.
• Secure, scale and monitor a Kubernetes cluster.

This instructor-led, live training in Radom (online or onsite) is aimed at intermediate-level professionals who wish to effectively deploy, manage, and scale containerized applications using Kubernetes.

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 Radom (online or onsite) is aimed at advanced-level platform engineers and DevOps professionals who wish to master scaling applications using microservices and Kubernetes.

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.

DO180 is an introduction to containers, Kubernetes fundamentals, and Red Hat OpenShift platform concepts focused on hands-on skills.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level technical professionals who wish to learn container workflows, Kubernetes primitives, and how to deploy and operate applications on OpenShift.

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

• Build and manage container images and registries with best practices for reproducibility and security.
• Deploy and manage Kubernetes objects such as pods, deployments, and services in OpenShift.
• Use OpenShift features including routes, buildconfigs, and the web console to streamline application delivery.
• Implement persistent storage, configuration management, and secrets handling for stateful workloads.
• Apply basic security, RBAC, and monitoring practices to maintain healthy clusters and applications.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs in a live OpenShift environment every day.
• Scenario-driven exercises and troubleshooting workshops.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Radom (online or onsite) is aimed at beginner-level developers who wish to learn the basics of Kubefirst and how it simplifies, secures, and accelerates Kubernetes and Swarm cluster management at enterprise scale.

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

• Set up a Kubefirst development environment.
• Write and run a basic Kubefirst program.
• Annotate code with Kubefirst directives and clauses.
• Use Kubefirst API and libraries.
• Profile and debug Kubefirst programs.

This instructor-led, live training in Radom (online or onsite) is aimed at intermediate-level developers and DevOps engineers who wish to use Minikube as a part of their development workflow.

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.
• Optimize their development process using Minikube's advanced features.
• Apply best practices for local Kubernetes development.

This instructor-led, live training in Radom (online or onsite) is aimed at beginner to intermediate-level developers, system administrators, and DevOps engineers who wish to understand Kubernetes and cloud-native principles.

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

• Set up a development environment that includes Kubernetes.
• Create a microservices application using Kubernetes.
• Deploy, manage, and scale applications in Kubernetes.
• Debug common issues in Kubernetes environments.

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

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

In this instructor-led, live training in Radom (onsite or remote), participants will learn how to create and manage Docker containers, then deploy a sample application inside a container. Participants will also learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. Finally, the training goes on to more advanced topics, walking participants through the process of securing, scaling and monitoring a Kubernetes cluster.

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.

The Certified Kubernetes Administrator (CKA) program was created by The Linux Foundation and the Cloud Native Computing Foundation (CNCF).

Kubernetes is nowadys a leading platform used for containers orchestration.

NobleProg have been delivering Docker & Kubernetes training from 2015. With more than 360 successfully completed training projects, we became one of the best known training companies worldwide in field of containerization.

Since 2019 we are also helping our customers to confirm their performance in k8s environment by preparing them and encouraging to pass CKA and CKAD exams.

This instructor-led, live training (online or onsite) is aimed at System Administrators, Kubernetes users who wish to confirm their knowledge by passing CKA exam.

On the other hand, training is focused also on gaining practical experience in Kubernetes Administration, so we recommend taking part in it, even if you don't intend to take CKA exam.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

In this instructor-led, live training in Radom (online or onsite), participants will learn how to set up and manage a production-scale container environment using Kubernetes on 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 AKS cloud.
• Integrate Kubernetes with third-party continuous integration (CI) software.
• Ensure high availability and disaster recovery in Kubernetes.

The objective of this practical course is to provide all the tools that address the practical aspects of Docker and Kubernetes, in order that the participants can count on the necessary skills for the proper management of the program.

In this instructor-led, live training in Radom, participants will learn how to manage Red Hat OpenShift Container Platform.

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

• Create, configure, manage, and troubleshoot OpenShift clusters.
• Deploy containerized applications on-premise, in public cloud or on a hosted cloud.
• Secure OpenShift Container Platform
• Monitor and gather metrics.
• Manage storage.

In this instructor-led, live training in Radom, participants will learn how to use OpenShift Container Platform to deploy containerized applications.

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

• Create and configure an OpenShift setup.
• Quickly deploy applications on-premise, in public cloud or on a hosted cloud.

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.

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
• Lots of exercises and practice
• 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), the host of Kubernetes.

This instructor-led, live training (online or onsite) is aimed at Developers who wish to confirm their skills in design, build, configure, and expose cloud native applications for Kubernetes. 

On the other hand, training is also focused on gaining practical experience in Kubernetes application development, so we recommend taking part in it, even if you don't intend to take CKAD exam.

NobleProg have been delivering Docker & Kubernetes training from 2015. With more than 360 successfully completed training projects, we became one of the best known training company worldwide in field of containerization. Since 2019 we are also helping our customers to confirm their performance in k8s environment by preparing them and encouraging to pass CKA and CKAD exams.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.
• To learn more about CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

This instructor-led, live course in Radom provides participants with an overview of Rancher and demonstrates through hands-on practice how to deploy and manage a Kubernetes cluster with Rancher.

Istio is an open-source service mesh that runs on Kubernetes to provide secure, observable, and manageable connectivity between microservices. By leveraging Istio’s Envoy-based sidecar proxies, teams can enforce policies, secure communications with mTLS, gain deep observability into traffic, and improve reliability at scale.

This instructor-led, live training (online or onsite) is aimed at intermediate-level engineers who wish to deploy, secure, and manage microservices applications using Istio on Kubernetes.

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 with Prometheus, Grafana, and Jaeger.
• Integrate Istio with Calico for advanced network policies and security.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

EKS is a self-managed Kubernetes-as-a-service offering from AWS. EKS is fully scalable and customizable and allows a Kubernetes deployment to mimic and/or integrate with an existing on-premise Kubernetes setup.

In this instructor-led, live training, participants will learn how to set up and manage a production-scale container environment using Kubernetes on EKS. 

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

• Configure and manage Kubernetes on EKS
• Migrate an existing Kubernetes environment from on-premise to AWS cloud
• Integrate Kubernetes with third-party continuous integration (CI) software
• Ensure high availability and disaster recovery in Kubernetes
• Understand and adopt the tools available to efficiently manage EKS

Audience

• Developers
• System Administrators
• DevOps Engineers

Format of the Course

• Part lecture, part discussion, exercises and heavy hands-on practice in a live-lab environment.

Note

• To request a customized training for this course, please contact us to arrange.

The evolution of microservices and containers in recent years has significantly changed how we design, develop, deploy and run software. Modern applications must be optimized for scalability, elasticity, failure, and change. Driven by these new demands, modern architectures require a different set of patterns and practices. In this training, we examine ways to identify, understand and adjust to these new requirements.

Audience
This training is intended for people who are somewhat familiar with container technology and with Kubernetes concepts but are perhaps lacking the real world experience. It is based on use cases, and lessons learnt from real life projects with the intention of making people inspired to create and manage even better cloud native applications.

• Developers
• Operations
• DevOps
• QA Engineers
• IT Project Managers

Format of the Course

• Interactive lecture and discussion
• Lots of exercises and practice
• Handson implementation in a live-lab environment

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Radom (online or onsite) is aimed at engineers who wish to evaluate, select and deploy the most appropriate Kubernetes solution for their specific situation.

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

• Install and configure a Kubernetes cluster on premise and in the cloud.
• Evaluate different cloud-hosted Kubernetes solutions and understand the advantages over an self-hosted approach.
• Compare different tools for testing, managing, and monitoring a Kubernetes cluster.

This instructor-led, live training in Radom (online or onsite) is aimed at engineers who wish to use Helm to streamline the process of installing and managing Kubernetes applications.

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 Radom (online or onsite) is aimed at system administrators and developers who wish to use Prometheus to monitor Kubernetes clusters.

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

• Install and configure Prometheus.
• Monitor dynamic cloud environments.
• Gain better insight into their Kubernetes clusters.
• Set up alerts that are precise and insightful.

This instructor-led, live training in Radom (online or onsite) is aimed at DevOps engineers who wish to use Kubernetes and Gitlab to automate the DevOps lifecycle.

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

• Automate application builds, tests, and deployments.
• Create an automated build infrastructure.
• Deploy an application to a containerized cloud environment.

This instructor-led, live training in Radom (online or onsite) is aimed at engineers who wish to optimize networking for Kubernetes clusters.

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

• Install and configure Calico.
• Understand how Calico differs from traditional overlay networks.
• Understand how Calico combines internet routing protocols with consensus-based data stores.
• Use Calico to create a container networking solution for Kubernetes clusters.
• Use Calico to provide network policy for Kubernetes.

In this instructor-led, live training in Radom, participants will learn how to set up and manage a production-scale container environment using Kubernetes on Google Cloud. 

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

• Configure and manage Kubernetes on Google Cloud.
• Deploy, manage and scale a Kubernetes cluster.
• Deploy containerized (Docker) applications on Google Cloud.
• Migrate an existing Kubernetes environment from on-premise to Google Cloud.
• Integrate Kubernetes with third-party continuous integration (CI) software.
• Ensure high availability and disaster recovery in Kubernetes.

During the training "Introduction to Microsoft Azure and Azure Kubernetes Service," participants will acquire skills for creating applications in the Microsoft Azure cloud computing environment, using containerization (Docker) and Azure Kubernetes Service (AKS). The course covers an overview of Microsoft Azure architecture, application hosting strategies, resource group creation, and service configuration. Participants will also learn modern application development practices using Git repositories, Docker containers, CI/CD pipelines, and AKS. Practical deployment examples will be conducted during the training, along with discussions on Docker, Kubernetes, and integration with Azure DevOps tools.

In this instructor-led, live training in Radom (onsite or remote), participants will learn how to how to install, configure, and manage OKD on-premise or in the cloud.

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

• Create, configure, manage, and troubleshoot an OKD cluster.
• Secure OKD.
• Deploy containerized applications on OKD.
• Monitor the performance of an application running in OKD.
• Manage data storage.
• Quickly deploy applications on-premise or on a public cloud such as AWS.

This instructor-led, live training in Radom (online or onsite) is aimed at Kubernetes practitioners who wish to prepare for the 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 instructor-led, live training in Radom (online or onsite) is aimed at developers and DevOps engineers who wish to utilize a serverless approach for building enterprise applications in Kubernetes.

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

• Setup and configure the Kubernetes system to start developing with a serverless architecture.
• Understand the concepts and principles foundational to serverless environments.
• Operate toolchains necessary to serverless development and integrate it with Kubernetes components.
• Practice their skill in Python programming language and apply it to implement  serverless systems.
• Secure enterprise applications that are deployed through a serverless framework on Kubernetes.
• Utilize modern cloud computing methods in optimizing DevOps task processing workflows.

This instructor-led, live training in Radom (online or onsite) is aimed at engineers who wish to secure a Kubernetes cluster beyond the default security settings.

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

• Understand the vulnerabilities that are exposed by a default Kubernetes installation.
• Prevent unauthenticated access to the Kubernetes API, database, and other services.
• Protect a Kubernetes cluster from accidental or malicious access.
• Put together a comprehensive security policy and set of best practices.

The "Advanced Docker and Kubernetes" course is a comprehensive training covering the Kubernetes platform and its ecosystem. It is designed for participants with varying levels of experience, offering a full range of both fundamental and advanced Kubernetes features. The course covers key concepts such as Pods, Labels, Controllers, Services, Secrets, Persistent Data Volumes, Claims, Namespaces, Quotas, the Container Networking Model, Service Discovery, Scaling, Load Balancing, Cluster Management, Kubernetes Installation, Cluster Security, Access Control, High Availability of the Control Plane, Monitoring and Logging, Application Auto-Scaling, Advanced Scheduling, Microservices-Based Applications, Application Design Patterns, and Application Deployment on a Kubernetes Cluster.

This instructor-led, live training in (online or onsite) is aimed at engineers who wish to evaluate each of these services to make an informed decisions about which to deploy within their organization.

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

• Set up a development environment that includes all needed libraries, packages and frameworks needed to start developing.
• Set up, configure and deploy a series of demo containers using a number of different approaches.
• Understand the architectural and design differences among different Docker/Kubernetes solutions within AWS.
• Automate the deployment of Docker containers.
• Set up a continuous integration and deployment pipeline.
• Integrate Docker and Kubernetes into an existing continuous integration system.

This 7-day programme provides a comprehensive, hands-on journey into designing, deploying, and operating cloud-native applications using modern DevOps practices.

Participants will explore how to design scalable microservices architectures, optimise container environments, and manage production workloads using Kubernetes. The course covers advanced deployment strategies, GitOps-based automation, and observability practices to ensure system reliability and performance.

A strong focus is placed on real-world operational challenges, including incident response, failure simulation, and root cause analysis. The programme concludes with the use of AI-powered tools to support troubleshooting and accelerate 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.

This instructor-led, live training in Radom (online or onsite) is aimed at DevOps engineers and developers who wish to use Fedora CoreOS to reduce the maintenance and upgrade costs of running  containerized applications on Kubernetes.

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

• Install and configure Fedora CoreOS.
• Set up Kubernetes cluster on Fedora CoreOS.
• Run and manage Kubernetes deployments on Fedora CoreOS.
• Automatically update Fedora OS with the latest OS improvements, bug fixes, and security updates.

This instructor-led, live training in Radom (online or onsite) is aimed at DevOps engineers who wish to set up, deploy and manage a Git-based software deployment workflow for their Kubernetes applications.

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

• Install and configure Spinnaker and Terraform.
• Understand the benefits of GitOps over traditional CI/CD and Infrastructure-as-Code (IAC).
• Move away from maintaining scripts. Configure and execute well-defined deployment process.
• Apply best practices for cloud-native deployment, management, and monitoring.
• Recover deployments from partial failures without manual intervention.
• Create a GitOps strategy for application development.

This instructor-led, live training Radom (online or onsite) is aimed at DevOps engineers and developers who wish to use Java and Kubernetes (K8s) to create, build, test, debug and deploy high-performance and scalable applications.

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

• Set up the necessary development environment to build Java applications.
• Understand the features and architecture of Kubernetes.
• Learn about the key concepts and tools for DevOps.
• Get a refresher on Java programming fundamentals.
• Containerize Java microservices using Docker.
• Build, scale, and deploy Java applications on Kubernetes.

Kubernetes is an open-source platform for automating all development stages of containerized applications. Design patterns are iterable solutions to software development problems pertinent to software design. Kubernetes extensions are utilized for configuring and supporting Kubernetes clusters. With the help of Kubernetes design patterns and extensions, users of the platform can achieve CI/CD approaches while maintaining scalability and flexibility of software applications.

This instructor-led, live training (online or onsite) is aimed at developers and DevOps engineers who wish to leverage Kubernetes design patterns and extensions to create enterprise applications on Kubernetes clusters.

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

• Set up a Kubernetes cluster and configure the necessary DevOps tools.
• Understand the fundamentals of software design patterns and Kubernetes extensions.
• Utilize Kubernetes extensions and design patterns when interacting with Kubernetes API.
• Develop customized Kubernetes resources and apply dynamic controllers to a cluster.
• Manage and secure any Kubernetes environment with the help of Kubernetes plugins.
• Integrate DevOps networking models to existing and prospective Kubernetes projects.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Kubernetes Persistence refers to the capability within Kubernetes to manage stateful data for containerized applications. In Kubernetes, this is primarily achieved through the use of Persistent Volumes (PVs) and Persistent Volume Claims (PVCs). Persistent Volumes are pieces of storage in the cluster that have been provisioned by an administrator or dynamically through Storage Classes. They provide a way for applications to persist data beyond the lifecycle of individual pods, ensuring data durability across pod restarts and deployments. This is crucial for stateful applications like databases that need to maintain data across updates and restart

This instructor-led, live training in Radom (online or onsite) is aimed at DevOps engineers and developers who wish to deploy and manage OpenStack services on cloud infrastructures using Kubernetes.

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

• Deploy, configure, and manage MOS and its components.
• Access OpenStack APIs.
• Perform common OpenStack operations tasks (backup, restore, etc.).
• Upgrade OpenStack deployments.

This instructor-led, live training in Radom (onsite or remote) is aimed at developers who wish to use OpenFaas to create, build, test, debug and deploy event-driven functions without needing to worry about managing the underlying server infrastructure.

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

• Install and configure OpenFaas.
• Package any binary or code as a serverless function without repetitive boiler-plate coding.
• Decouple from AWS Lambda to avoid lock-in.
• Deploy event-driven functions to an on-premise server or to the cloud.

This instructor-led, live training in Radom (online or onsite) is aimed at developers and DevOps engineers who wish to leverage Tekton Pipelines for supporting complex software development workflows and building automated CI/CD pipelines.

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

• Install and configure Tekton Pipelines and other foundational Tekton components.
• Design and create the building blocks of pipelines for software development in Tekton.
• Automate existing pipelines and development processes using Tekton framework concepts and principles.
• Run and manage Tekton Pipelines for various workload types across multiple platforms.
• Implement CI/CD systems based on the Tekton framework to enhance future software development projects.