کتاب صوتی بهینه‌سازی مقیاس‌پذیری در محیط کوبرنتیز

🎓 دوره آموزشی جامع

📚 اطلاعات دوره

عنوان دوره: دوره بهینه‌سازی مقیاس‌پذیری در محیط کوبرنتیز

موضوع کلی: مدیریت و بهینه‌سازی سیستم‌های نرم‌افزاری

موضوع میانی: معماری و پیاده‌سازی راهکارهای مقیاس‌پذیر

📋 سرفصل‌های دوره

• 1. مقدمه‌ای بر مقیاس‌پذیری سیستم‌های نرم‌افزاری
• 2. مفاهیم اساسی مقیاس‌پذیری عمودی و افقی
• 3. معماری‌های نرم‌افزاری مناسب برای مقیاس‌پذیری
• 4. اصول طراحی سیستم‌های توزیع‌شده
• 5. مقدمه‌ای بر کوبرنتیز و نقش آن در مقیاس‌پذیری
• 6. مفهوم کلاستر کوبرنتیز و اجزای اصلی آن
• 7. نودها، پادها و سرویس‌ها در کوبرنتیز
• 8. مدیریت منابع در کوبرنتیز
• 9. پیکربندی و استقرار برنامه‌ها در کوبرنتیز
• 10. Scaling strategies in Kubernetes
• 11. Vertical Pod Autoscaler (VPA)
• 12. Horizontal Pod Autoscaler (HPA)
• 13. Cluster Autoscaler
• 14. Deployment strategies for scalability
• 15. Rolling updates and canary deployments
• 16. Blue-green deployments
• 17. Zero-downtime deployments
• 18. Resource management and optimization in Kubernetes
• 19. CPU and memory limits and requests
• 20. Quality of Service classes
• 21. Namespaces and resource quotas
• 22. Storage management for scalable applications
• 23. Persistent Volumes and Persistent Volume Claims
• 24. Storage classes and dynamic provisioning
• 25. Network management for scalable applications
• 26. Services and Ingress controllers
• 27. Load balancing strategies in Kubernetes
• 28. Network policies for security and isolation
• 29. Observability in Kubernetes
• 30. Logging and log aggregation
• 31. Monitoring and metrics collection
• 32. Distributed tracing
• 33. Performance tuning for Kubernetes clusters
• 34. Optimizing node performance
• 35. Tuning kubelet and container runtime
• 36. Network performance optimization
• 37. Database scaling in a Kubernetes environment
• 38. Strategies for scaling relational databases
• 39. Strategies for scaling NoSQL databases
• 40. Caching strategies for performance
• 41. Message queueing systems for decoupling and scaling
• 42. Kafka and RabbitMQ in Kubernetes
• 43. Asynchronous processing patterns
• 44. Microservices architecture and scalability
• 45. Designing microservices for independent scaling
• 46. Inter-service communication patterns
• 47. API Gateway implementation for microservices
• 48. Security considerations for scalable Kubernetes systems
• 49. Authentication and authorization
• 50. Network security and encryption
• 51. Pod security policies
• 52. Cost optimization in Kubernetes
• 53. Rightsizing resources
• 54. Spot instances and preemptible VMs
• 55. Resource utilization monitoring
• 56. Best practices for building scalable applications on Kubernetes
• 57. Application design patterns for scalability
• 58. Code optimization for performance
• 59. Testing for scalability and resilience
• 60. Disaster recovery and business continuity planning
• 61. Backup and restore strategies
• 62. High availability configurations
• 63. Chaos engineering for resilience testing
• 64. Future trends in Kubernetes scalability
• 65. Serverless computing on Kubernetes
• 66. Edge computing and Kubernetes
• 67. AI/ML workloads on Kubernetes
• 68. DevOps and GitOps for scalable systems
• 69. Continuous integration and continuous delivery (CI/CD)
• 70. Infrastructure as Code (IaC)
• 71. Automated deployments and rollbacks
• 72. Understanding Kubernetes networking models
• 73. CNI plugins and their impact on performance
• 74. Service Mesh for microservices scalability
• 75. Istio and Linkerd
• 76. Traffic management and observability with Service Mesh
• 77. Advanced deployment patterns for resilience
• 78. Multi-cluster Kubernetes deployments
• 79. Federation and multi-cluster management
• 80. Disaster recovery across multiple clusters
• 81. Performance analysis and bottleneck identification
• 82. Profiling applications in Kubernetes
• 83. Using Prometheus and Grafana for deep insights
• 84. Troubleshooting performance issues
• 85. Security best practices for production Kubernetes
• 86. RBAC and access control
• 87. Network segmentation and isolation
• 88. Image security and vulnerability scanning
• 89. Cost-effective storage solutions for Kubernetes
• 90. Optimizing persistent storage costs
• 91. Leveraging object storage
• 92. Data backup and disaster recovery strategies
• 93. Scalable application resilience patterns
• 94. Circuit breaker pattern
• 95. Bulkhead pattern
• 96. Retry pattern
• 97. Rate limiting and throttling mechanisms
• 98. Protecting against overload conditions
• 99. Throttling API requests
• 100. Load shedding techniques