HIGAET Kubernetes Engineering
Operate Kubernetes workloads with confidence across pods, deployments, services, ingress, and storage, then package with Helm, observe clusters, and manage upgrades and reliability.
Duration
8 weeks · 6-8 hours/week
Level
Advanced
Delivery
Online
Status
Open for enrollment
Why this technology matters.
Kubernetes is the standard way to run many containerized services together: it places your workloads, restarts failed ones, routes traffic, and scales capacity up and down. Learning it means you can take an application from a single container to a resilient cluster that handles updates and failures gracefully. It matters now because microservices and cloud-native platforms overwhelmingly run on Kubernetes.
Kubernetes engineers define pods with probes and resource controls, run rolling and staged updates with deployments, route traffic with services and ingress, and add persistent storage for stateful workloads. It solves bin-packing, self-healing, service discovery, and repeatable rollouts. It does not fix bad application architecture or missing observability, and Helm charts do not replace capacity planning and upgrade discipline.
By the end you will be able to build a health-checked pod deployment with rolling updates, a service discovery and ingress routing setup for internal and external traffic, and a stateful workload with persistent volumes plus Helm packaging and cluster observation.
Why this course exists
The gap is between running a sample app on a local cluster and operating upgrades, storage, and reliability in a shared production cluster. This course follows the arc from workload definition to deployment to networking to storage to observation to upgrade and reliability. You leave able to operate Kubernetes workloads with confidence.
Know exactly what you're signing up for.
Who is this for
Prerequisites
- Familiarity with containers and command line
- Basic networking and YAML concepts
- Understanding of application deployment basics
Technologies & tools
Skills you'll gain
A 8 weeks arc, module by module.
- Module 01
Module 01 — Kubernetes Foundations and Cluster Architecture
- Module 02
Module 02 — Pods, Scheduling, and Configuration
- Module 03
Module 03 — Deployments, Scaling, and Update Strategies
- Module 04
Module 04 — Services, Ingress, and Traffic Routing
- Module 05
Module 05 — Storage, Volumes, and Stateful Workloads
- Module 06
Module 06 — Helm Packaging and Release Management
- Module 07
Module 07 — Observability, Troubleshooting, and Autoscaling
- Module 08
Module 08 — Cluster Operations, Security, and Upgrades
- Module 09
Module 09 — Capstone: Operate a Production-Grade Kubernetes Service
Practical Training Flow
Learning → Guided Labs → Independent Practice → Industry Project → Capstone → Portfolio → Career Preparation. Practical hours are tracked alongside instructional hours and surfaced on the certificate.
Delivery as HIGAET Practical Training / Experiential Learning.
What you'll be able to do.
- Build pod specifications with probes, resources, and lifecycle controls.
- Deploy rolling and staged application updates using deployments and replicasets.
- Design service discovery and ingress routing for internal and external traffic.
- Integrate persistent volumes and storage classes into stateful workloads.
- Automate application packaging and releases with Helm charts and values.
- Evaluate cluster and workload health using metrics, logs, and traces.
- Secure workloads with RBAC, namespaces, network policies, and secrets handling.
- Optimize cluster operations with upgrades, autoscaling, and backup procedures.
You will build.
Every project ships as HIGAET Practical Training / Experiential Learning — portfolio-ready work, not exercises.
- Project 01
Hardened pod specs with probes and resources
- Project 02
Rolling application update with deployments
- Project 03
Service discovery with ingress routing
- Capstone
Observable stateful cluster with Helm and upgrades
Speak the language first.
- Pods and containers
- The smallest deployable units in Kubernetes, grouping containers that run and scale together.
- Probes and resource limits
- Health checks and CPU-memory boundaries that keep workloads stable and schedulable.
- Deployments and ReplicaSets
- Controllers that keep the desired number of pod copies running through updates and failures.
- Rolling updates
- A strategy that replaces pods gradually so the application stays available during upgrades.
- Services and service discovery
- Stable network endpoints that route traffic to changing pod addresses inside the cluster.
- Ingress routing
- Rules that direct external web traffic to the correct service inside the cluster.
- Persistent volumes and storage classes
- Durable storage that survives pod restarts, provisioned by class for stateful workloads.
- Helm packaging
- Templated bundles that install and version a full application stack reproducibly.
- Cluster observability and upgrades
- Monitoring plus planned version upgrades that keep nodes and workloads reliable.
Fix, check, and go deeper.
Troubleshooting & common mistakes
Pod stuck in CrashLoopBackOff
Read pod logs and events, fix the failing command or missing env variable, and verify readiness probes.
Service reachable inside cluster but not externally
Inspect service type, ingress rules, and DNS names, then correct the selector or ingress path.
Stateful app loses data after restart
Confirm the volume claim is bound to a persistent volume and not ephemeral storage, then reattach correctly.
Rolling update never completes
Describe the ReplicaSet for image pull or probe failures, fix the image tag or thresholds, and resume the rollout.
Helm upgrade fails with conflicting values
Diff current versus new values, render templates locally, then upgrade with corrected values.
Node pressure evicts pods unexpectedly
Check node CPU-memory pressure and missing resource requests, then set requests and limits per workload.
Before you move on, you should be able to
- Build pod specifications with probes, resources, and lifecycle controls
- Deploy rolling and staged updates using deployments and ReplicaSets
- Design service discovery and ingress routing for cluster traffic
- Integrate persistent volumes and storage classes into stateful workloads
- Package applications with Helm for repeatable installs
- Observe clusters and manage upgrades for reliability
Start your application.
Share a few details and a HIGAET advisor will reach out within one business day with next steps.
Common questions
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Ready to start HIGAET Kubernetes Engineering?
A 8 weeks course — Cloud & Platform Engineering.