Kubernetes and Cloud Native Systems immerses developers in the Kubernetes ecosystem and the tooling teams need to adopt cloud native environments. The course runs across five hands-on days. Each day breaks into four modules, and every module includes a hands-on lab that reinforces the lecture material. Day one opens with containers themselves, covering image construction and registries before introducing orchestration concepts and Kubernetes architecture. Day two moves into Pods and Controllers, contrasting basic Pod usage with deeper Pod architecture. It then works through Deployments and the batch operations and Jobs that run workloads to completion rather than indefinitely.
Day three covers services and storage, configuring Services, network policy, and application configuration alongside the stateful primitives that back durable workloads. Day four turns to observability and testing, walking through core observability concepts, metrics collection, and Prometheus-based monitoring. It closes with troubleshooting techniques for diagnosing failing workloads. Day five closes the course with namespaces, security, and service mesh. It covers RBAC for namespace-based access control, along with service mesh fundamentals and tracing. The day finishes with the public cloud features that extend Kubernetes on managed platforms.
Attendees explore container-based microservice packaging and dynamic application management throughout, examining best practices and architecture patterns along the way. By the end of the course, they can design, build, deploy, and debug applications in a Kubernetes environment. They come away with a clear understanding of how to get the most from microservice-based solutions in a cloud native setting.
Who Should Attend
Developers, DevOps staff, data engineers
What Attendees Will Learn
Upon completing Kubernetes and Cloud Native Systems, attendees will be able to:
- Explain container fundamentals and Kubernetes architecture
- Define Pod architecture and manage Pods with Controllers and Deployments
- Run batch workloads using Kubernetes Jobs
- Configure Kubernetes Services, network policy, and application configuration
- Manage stateful workloads using Kubernetes primitives
- Apply Kubernetes observability, including metrics and Prometheus monitoring
- Troubleshoot Kubernetes workloads
- Apply Kubernetes RBAC and namespace-based security
- Explain service mesh concepts and distributed tracing
- Apply public cloud Kubernetes features and functions
Prerequisites
The course focuses on Kubernetes, so it requires no specific programming language expertise. Attendees should have experience with at least one programming language and basic familiarity with microservice architecture. Code examples appear in Go and Python.