Course Outline

Course Outline:

Introduction to Kuma Integration and Kubernetes

  • Overview of Kuma service mesh and its role in Kubernetes
  • Kuma: Features and architecture overview
  • Understanding the Benefits of Integrating Kuma with Kubernetes
  • Comparison of different service mesh solutions in the ecosystem Kubernetes
  • Understanding the need for a service mesh in modern microservices architecture
  • Installing Kuma on clusters Kubernetes
  • Exploring Kuma's control plane and data plane components

Deployment and Configuration of Kuma in Kubernetes

  • Installing Kuma Control Panel components within clusters Kubernetes
  • Deploying Kuma data plane proxies alongside pods Kubernetes
  • Integration with Kubernetes API server and control panel synchronization
  • Validating and testing Kuma deployment within environments Kubernetes

Service Discovery and Traffic Routing with Kuma

  • Configuring service discovery with the Kuma Service Catalog
  • Implementing traffic routing policies using Kuma traffic routing resources
  • Hands-on exercises: Configuring traffic routing for various deployment scenarios
  • Load balancing strategies in Kuma: Layer 4 and Layer 7 load balancing

 

Advanced Traffic Management with Kuma

  • Insight into Kuma's traffic policies
  • Kuma traffic routing, splitting and shaping techniques
  • Weighted routing, fault injection and circuit breaking
  • Canary and blue-green distributions with Kuma in Kubernetes

Traffic Observability and Security with Kuma

  • Implementing telemetry and observability features with Kuma data plane proxies
  • Introducing Kuma's traffic metrics, tracking and logging capabilities
  • Secure service-to-service communication with mTLS encryption
  • Traffic policy enforcement and access control with Kuma Traffic Policies

 

Enhanced Security with Kuma in Kubernetes

  • Implementation of mutual TLS (mTLS) authentication between services
  • Role-based access control (RBAC) policies for fine-grained access control
  • Encryption and data protection in the Kuma service mesh within clusters Kubernetes

Observability and Monitoring with Kuma

  • Using Prometheus and Grafana to monitor Kuma metrics
  • Logging and tracking with Kuma for improved observability
  • Troubleshooting and debugging Kuma deployments in environments Kubernetes

Multi-Cluster Distribution Strategies

  • Federated service mesh architecture with Kuma across multiple clusters Kubernetes.
  • Service mesh replication and synchronization across clusters
  • Disaster recovery planning and high availability considerations with Kuma in multi-cluster environments

Performance Optimization and ScalaKuma's abilities in Kubernetes

  • Optimized Kuma control panel and data plane components for performance
  • Scalaability of Kuma distributions in clusters Kubernetes
  • Load balancing and performance tuning strategies for Kuma service mesh

 

 

 

Advanced Topics and Best Practices

  • Implementation of failure injection and circuit breaking for resilience testing
  • Advanced traffic routing techniques: traffic shifting and mirroring
  • Kuma integration with external service meshes (e.g. Istio, Linkerd)
  • Best practices for deploying and managing Kuma in production environments
  • Troubleshooting common problems and debugging techniques

 

Practical laboratories:

  • Configuring clusters Kubernetes for Kuma deployment
  • Deploy microservice applications with advanced traffic management policies
  • Implementation of security measures with mTLS and RBAC
  • Tracking Kuma Deployments Using Prometheus and Grafana
  • Multi-cluster deployment scenario and disaster recovery testing
  • Performance tuning and scaling exercises for Kuma in Kubernetes

 

Project and Final Exam (Optional)

  • Wrapping Up Project: Design and implementation of a service mesh architecture using Kuma for a sample microservices application
  • NobleProg Certification Exam: Evaluates participants' understanding of Kuma concepts, configuration, and best practices

Requirements

Prerequisite:

 

  • Previous experience with the fundamentals of Kubernetes and containerization concepts
  • Proficiency in using the command line interface of Linux
  • Knowledge of containerization technologies (Docker, container runtime)
  • Knowledge of the fundamentals of networks
  • Knowledge of networking principles and service mesh concepts is helpful but not essential

Audience

  • Engineers DevOps
  • Administrators Kubernetes
  • Software developers
  • System architects
 35 Hours

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