Advanced Kubernetes

Course Summary

This course builds on existing Kubernetes knowledge by exploring multi-cluster operations, service mesh strategies, advanced security practices, and the deployment of specialized workloads like AI/ML. Learners will explore strategies for scaling, optimizing, and securing Kubernetes clusters in production, with a focus on modern tools and practices for enterprise-grade environments.

Prerequisites

In order to succeed in this course, you will need:

Strong understanding of Kubernetes concepts and cluster operations
Hands-on experience deploying and managing workloads in Kubernetes
Familiarity with Helm, GitOps, and observability tools (Prometheus, Grafana, etc.)

Purpose	Learn advanced Kubernetes concepts including multi-cluster operations, service mesh, and enterprise security
Audience	Senior DevOps engineers, SREs, platform engineers, and security professionals managing Kubernetes at scale
Role	Senior DevOps Engineer \| SRE \| Platform Engineer \| Security Architect
Skill Level	Advanced
Style	Targeted Topic - Hands-on Workshops
Duration	3 Days
Related Technologies	Kubernetes \| Service Mesh \| Istio \| GitOps \| Security

Course Objectives

Manage multi-cluster and hybrid Kubernetes environments
Implement service mesh architectures for traffic management, security, and observability
Secure workloads using supply chain security and runtime protection techniques
Optimize costs and performance with advanced autoscaling strategies
Apply advanced troubleshooting and chaos engineering practices

What You'll Learn:

In the Advanced Kubernetes training course, you'll learn:

Multi-Cluster and Hybrid Environments
- Multi-cluster use cases and architectures
- Cluster API and KubeFed for federation
- Anthos, OpenShift, and hybrid models
- Connecting and managing multiple clusters
Service Mesh and Advanced Networking
- Istio, Linkerd, and Ambient Mesh overview
- Traffic shaping, retries, and circuit breaking
- mTLS for service-to-service security
- Deploying a service mesh and configuring traffic policies
Advanced Security Practices
- Software supply chain security (Sigstore, SLSA, SBOMs)
- Image scanning and admission controllers (OPA/Gatekeeper, Kyverno)
- Runtime security with Falco or similar tools
- Implementing supply chain and runtime security controls
Scaling and Optimization
- Horizontal Pod Autoscaler (HPA) advanced patterns
- Vertical Pod Autoscaler (VPA)
- Cluster Autoscaler for node scaling strategies
- Node pools and GPU scheduling
AI/ML Workloads on Kubernetes
- Overview of ML workloads in Kubernetes
- Kubeflow, Ray, and distributed training
- Running GPU workloads and inference services
- Deploying a simple ML inference pipeline
Observability and Reliability Engineering
- Advanced observability with OpenTelemetry
- Chaos engineering with LitmusChaos or Chaos Mesh
- Debugging complex workloads across clusters
- Incident response patterns in Kubernetes environments

Real-World Content

Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.

Expert Practitioners

Industry experts that bring their battle scars into the classroom.

Experiential Learning

More coding than lecture, coupled with architectural and design discussions.

Tailored Outlines

One-size-fits-all doesn't apply to training teams. That's where we come in!

“I appreciated the instructor's technique of writing live code examples rather than using fixed slide decks to present the material.”

VMware

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Advanced Kubernetes

Course Summary

Purpose

Audience

Role

Skill Level

Style

Duration

Related Technologies