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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
- 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
