Kubernetes Networking
Develop the skills to trace and control traffic through a Kubernetes cluster through a learning path centred on Kubernetes Networking. Explore concepts, guided practice and an applied project.
Build practical Kubernetes Networking skills.
Skills and knowledge developed in this course.
- Network model
- Service dataplane
- DNS and discovery
- Ingress and gateways
- Network policies
- Networking lab
About this course
This course develops practical capability in Kubernetes Networking. Its course-specific content covers Network model, Service dataplane, DNS and discovery, Ingress and gateways, followed by an applied project focused on trace and control traffic through a kubernetes cluster. The lessons include concrete configuration, design, testing or operational decisions appropriate to the subject.
Who this is for
Administrators, developers and practitioners who work with Kubernetes Networking or plan to take on responsibilities in this area.
Before you start
Basic computer literacy and a foundational understanding of containers & kubernetes. Prior experience with the named product helps with the practical exercises.
Trace and control traffic through a Kubernetes cluster
Deliver trace and control traffic through a kubernetes cluster. Use the module outcomes to state requirements, demonstrate a working result, test an expected failure or boundary case, and document assumptions and follow-up work.
Course content
Course-specific syllabus and practical exercises. Lab release, access arrangements and final delivery scope are confirmed before enrolment.
01Network model
+
- Pod addresses and CNI interfaces
- Node and Pod connectivity assumptions
Practical exerciseApply network model to the trace and control traffic through a kubernetes cluster and capture the validation evidence.
02Service dataplane
+
- Service types and endpoint selection
- kube-proxy and dataplane alternatives
Practical exerciseApply service dataplane to the trace and control traffic through a kubernetes cluster and capture the validation evidence.
03DNS and discovery
+
- CoreDNS queries and service names
- Search domains and resolution failures
Practical exerciseApply dns and discovery to the trace and control traffic through a kubernetes cluster and capture the validation evidence.
04Ingress and gateways
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- HTTP routing and TLS termination
- Ingress and Gateway API distinctions
Practical exerciseApply ingress and gateways to the trace and control traffic through a kubernetes cluster and capture the validation evidence.
05Network policies
+
- Ingress and egress selectors
- Default-deny design and policy testing
Practical exerciseApply network policies to the trace and control traffic through a kubernetes cluster and capture the validation evidence.
06Networking lab
+
- Trace a request across cluster layers
- Resolve a DNS, service or policy failure
Practical exerciseApply networking lab to the trace and control traffic through a kubernetes cluster and capture the validation evidence.
Technical references
These primary vendor, project or standards sources inform this independent IT Purview outline. Reference pages checked 25 October 2026; current provider documentation and exam objectives take precedence when versions change.
From understanding to application.
Progress by learning milestone. The schedule is agreed around your starting level and learning goals.
- 01Learning milestone 1 In progress
Set the context
Network model · Service dataplane
Establish the Kubernetes Networking scope, baseline concepts and operating assumptions. - 02Learning milestone 2 In progress
Build the working skills
DNS and discovery · Ingress and gateways
Apply the core Kubernetes Networking techniques in the course lab and record the result. - 03Learning milestone 3 In progress
Validate and handle exceptions
Check expected behavior, investigate a failure case and capture evidence for trace and control traffic through a kubernetes cluster. - 04Learning milestone 4 In progress
Deliver the applied project
Complete trace and control traffic through a kubernetes cluster, explain key decisions and identify a practical next step.
Career outlook after this learning path
Typical roles this roadmap can support, with broad salary ranges by relevant work experience.
| Role | 0–3 years | 3–7 years | 7–12+ years |
|---|---|---|---|
| Platform / DevOps Engineer | ₹7–13 LPA | ₹17–30 LPA | ₹34–56 LPA |
Ranges are indicative India-market compensation estimates in ₹ lakh per annum, not a salary promise. They reflect broad market guides and vary by location, employer, skills and role scope; the experience bands refer to relevant work experience, not time since training. Completing this course does not guarantee employment, a role, compensation or career progression. View market reference ↗