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Kubernetes Advanced Concepts

Elevate your Kubernetes expertise through this comprehensive course focused on advanced concepts.

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Certificate :

After Completion

Start Date :

10-Jan-2025

Duration :

30 Days

Course fee :

$150

COURSE DESCRIPTION:

  1. Elevate your Kubernetes expertise through this comprehensive course focused on advanced concepts.
  2. Gain skills in designing, deploying, and managing large-scale containerized applications.
  3. Delve into multi-cluster management, advanced networking, custom resources, and security for production environments.

CERTIFICATION:

  1. Earn a Certified Kubernetes Advanced Practitioner credential, showcasing your proficiency in managing and optimizing Kubernetes clusters.

LEARNING OUTCOMES:

By the conclusion of the course, participants will possess the skills to:

  1.  Utilize sophisticated scheduling methods such as affinity, anti-affinity, and taints/tolerations.

  2. Oversee multi-cluster Kubernetes setups and facilitate cross-cluster interactions.

  3. Enhance Kubernetes capabilities through Custom Resource Definitions (CRDs) and Operators while ensuring security and monitoring.

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Course Curriculum

Kubernetes Architecture Deep Dive
  1. Advanced Components
    • Kubernetes API Server: Detailed workflows and advanced configuration.
    • Etcd: Best practices for cluster state management.
    • Controller Manager: Advanced controllers and custom logic.
    • Kube-Scheduler: Scheduling policies and priorities.
  2. Cluster Internals
    • Node communication and runtime details.
    • Pod lifecycle hooks and advanced scheduling.
Kubernetes Networking
  1. Service Mesh
    • Introduction to service mesh architecture (Istio, Linkerd).
    • Traffic shaping, observability, and security with service mesh.
  2. Network Policies
    • Creating fine-grained network policies.
    • Managing inter-pod and pod-to-service communication.
  3. Advanced Ingress
    • Using custom ingress controllers (NGINX, Traefik).
    • Configuring TLS termination and load balancing strategies.
  4. DNS and CoreDNS
    • Customizing CoreDNS for advanced DNS resolutions.
Advanced Workloads and Scheduling
  1. Custom Resource Definitions (CRDs)
    • Creating and managing CRDs for domain-specific workloads.
    • Operators: Automating repetitive tasks with Kubernetes Operators.
  2. Taints and Tolerations
    • Configuring workloads to tolerate node taints.
  3. Affinity and Anti-Affinity
    • Optimizing pod placement using affinity rules.
  4. DaemonSets, StatefulSets, and Jobs
    • Advanced use cases and configuration for persistent and ephemeral workloads.
Kubernetes Storage
  1. Persistent Volume Claims (PVC)
    • Dynamic provisioning and storage classes.
    • Advanced PVC configurations for performance and scalability.
  2. CSI Drivers
    • Using Container Storage Interface (CSI) drivers for custom storage backends.
  3. Data Backup and Restore
    • Implementing disaster recovery with Velero and other tools.
Kubernetes Security
  1. RBAC and Policies
    • Advanced Role-Based Access Control (RBAC) setups.
    • Kubernetes Pod Security Standards (PSS).
  2. Secrets Management
    • Encrypting and securely managing secrets in Kubernetes.
  3. Security Tools
    • Integrating tools like Falco, Trivy, and Aqua Security for threat detection.
  4. Pod and Cluster Security
    • Configuring Pod Security Policies and enforcing compliance.
Kubernetes Autoscaling
  1. Horizontal Pod Autoscaler (HPA)
    • Configuring HPA with custom metrics using Prometheus.
  2. Vertical Pod Autoscaler (VPA)
    • Automatically adjusting resource requests/limits.
  3. Cluster Autoscaler
    • Scaling nodes based on workloads.
  4. Advanced Use Cases
    • Autoscaling with custom metrics and predictive scaling.
Kubernetes Monitoring and Observability
  1. Prometheus and Grafana
    • Setting up Prometheus for metrics collection.
    • Building custom dashboards in Grafana.
  2. Logging
    • Centralized logging with Fluentd, Fluent Bit, and Elasticsearch.
    • Troubleshooting with advanced log queries.
  3. Tracing
    • Distributed tracing with Jaeger or Zipkin.
    • Understanding service latencies and dependencies.
Capstone Project
  1. Complex Kubernetes Architecture
    • Deploy a multi-tier application using advanced Kubernetes features:
      • Implement custom CRDs and Operators.
      • Configure autoscaling with custom metrics.
      • Set up monitoring with Prometheus and Grafana.
      • Use advanced networking policies and service mesh for traffic control.
      • Enable multi-cluster communication for redundancy.

Training Features

Real-World Use Cases

Hands-on projects involving production-grade Kubernetes setups.

Advanced Toolchain

Integration of tools like Helm, ArgoCD, Prometheus, and Fluentd.

Focused on Security

Detailed exploration of cluster and application security practices.

Cloud and Hybrid Expertise

Insights into running Kubernetes on cloud platforms and hybrid setups.

Scalability and Performance

Emphasis on autoscaling, HA setups, and performance tuning.

Certification

Preparation for certifications like CKA (Certified Kubernetes Administrator) and CKAD (Certified Kubernetes Application Developer).

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