COURSE FORMAT & DELIVERY DETAILS Self-Paced, Immediate Online Access with Lifetime Value and Zero Risk
You begin the moment you're ready. This course is designed for professionals who demand flexibility without compromise. It is fully self-paced, allowing you to learn at your own speed, on your own schedule, with immediate online access upon enrollment. There are no fixed class dates, no weekly deadlines, and no time constraints. Whether you're balancing a demanding job, international time zones, or personal commitments, the structure respects your reality and empowers your progress. Realistic Timeline, Real Results – Fast
Most learners complete the core modules within 6 to 8 weeks when dedicating focused time each week. However, you can begin applying foundational cloud native principles to your work in as little as 72 hours. The architecture patterns, design frameworks, and deployment strategies are structured for immediate applicability – meaning you’ll see tangible results in your system designs, team workflows, or infrastructure decisions long before you finish the entire curriculum. This is not theoretical knowledge. This is operational leverage you deploy from day one. Lifetime Access, Forever Updated
Once you enroll, you own perpetual access to the full course content. This includes every update, enhancement, and expansion we release in the future – at no additional cost. The cloud native landscape evolves rapidly. New tools emerge, best practices shift, and regulatory demands increase. We continuously refine the material to reflect the latest standards and innovations. You’ll never need to repurchase or resubscribe. Your investment compounds over time, protecting your skills and relevance for years to come. Available Anywhere, Anytime – Desktop & Mobile Optimised
Access your learning platform 24/7 from any device, anywhere in the world. Our system is fully mobile-friendly and responsive, allowing you to study during commutes, lunch breaks, or remote work sessions. Whether on a tablet, smartphone, or laptop, your experience remains seamless, intuitive, and professional-grade. Direct Instructor Support & Guided Learning Paths
You are not alone. Throughout the course, you receive ongoing guidance through structured feedback channels, curated resources, and expert-reviewed insights. Our instructional team provides clear, actionable responses to learner inquiries, ensuring you overcome obstacles and deepen your mastery. This isn’t an isolated reading assignment – it’s a supported journey built on real-world mentorship and industry-tested wisdom. Certificate of Completion Issued by The Art of Service
Upon finishing the course, you earn a formal Certificate of Completion issued by The Art of Service. This credential is globally recognised and signifies a benchmark of excellence in cloud native architecture. It validates your commitment to high standards, technical precision, and future-ready engineering. Many graduates report using this certification to justify promotions, win client contracts, or transition into high-impact cloud roles. It is not just a digital badge – it’s a career asset designed for serious advancement. Transparent Pricing – No Hidden Fees, Ever
What you see is exactly what you pay. There are no surprise charges, recurring fees, or upsells. The listed price includes full access to all modules, tools, frameworks, updates, and your official certificate. We believe in integrity and clarity. You should know exactly what you’re investing in – and this course delivers maximum value with complete financial transparency. Accepted Payment Methods
- Visa
- Mastercard
- PayPal
Full Money-Back Guarantee – Satisfied or Refunded
We eliminate all risk with a firm commitment: if you're not satisfied with your experience, you can request a full refund at any time. There are no complicated conditions, time windows, or hoops to jump through. This is a satisfied or refunded promise because we are confident in the course’s transformational value. You have nothing to lose and everything to gain. Clear Enrollment & Access Process
After enrollment, you will receive a confirmation email acknowledging your registration. Shortly afterward, your access credentials and personal entry details will be sent separately, once your course materials are fully prepared and activated within the learning environment. This ensures a smooth, secure, and professional onboarding experience for every learner. Will This Work for Me? Absolutely – Even If…
You’ve tried other programs that were too abstract, too slow, or too disconnected from real engineering demands. This course works even if you’re not currently working in a cloud-centric role. It works even if your organisation hasn’t fully adopted containerisation yet. It works even if you come from a traditional IT background and feel behind in the cloud revolution. We’ve guided software engineers, DevOps leads, system architects, and technical managers through this exact transformation. One learner, a backend developer in Frankfurt, applied the auto-scaling patterns in Module 4 to re-architect their legacy monolith and reduced server costs by 41% – a result documented in their year-end review. Another, a solutions architect in Melbourne, used the observability frameworks to lead her team’s migration to Kubernetes and earned a promotion within four months. Social proof confirms the impact. 94% of learners report measurable improvements in their design capabilities, deployment confidence, or team leadership after completing just the first three modules. The methodology is role-agnostic, principle-based, and engineered for outcomes – not just completion. Your Confidence is Protected – Risk Reversal Built In
We reverse the risk equation. Instead of you betting on us, we bet on you. You get lifetime access, future updates, mobile flexibility, expert support, and a globally respected certificate – all backed by a full refund promise. You gain clarity, competitive advantage, and undeniable ROI without gambling your time or budget. This is the safest, most valuable step you can take toward mastering cloud native architecture.
EXTENSIVE & DETAILED COURSE CURRICULUM
Module 1: Foundations of Cloud Native Architecture - Defining cloud native vs traditional cloud computing
- Core principles of cloud native design
- Understanding the shift from monolithic to microservices
- Event-driven architecture essentials
- The role of automation in cloud native systems
- Benefits of resilience, scalability, and agility
- Decoupling services for independent deployment
- Stateless vs stateful components in cloud environments
- Service discovery and dynamic networking fundamentals
- Immutable infrastructure concepts and advantages
- GitOps as a foundational practice
- Designing for failure from day one
- Establishing observability as a first-class concern
- Introduction to twelve-factor app methodology
- Architectural trade-offs in distributed systems
- Understanding latency, consistency, and availability
Module 2: Core Cloud Native Design Patterns - Sidecar pattern for modularity and isolation
- Adapter pattern for integration with legacy systems
- Leader election for distributed coordination
- Work queue pattern for asynchronous processing
- Scatter gather for parallel data collection
- Circuit breaker pattern for fault tolerance
- Retry with exponential backoff strategies
- Bulkhead pattern to isolate system failures
- Anti-corruption layer for bounded context protection
- Event sourcing for state reconstruction
- Command Query Responsibility Segregation (CQRS)
- Service mesh integration patterns
- Backpressure handling in streaming systems
- Rate limiting and throttling at scale
- Idempotency design for safe retries
- Token bucket and leaky bucket algorithms
Module 3: Containerisation and Orchestration Frameworks - Docker architecture and image lifecycle
- Creating efficient and secure container images
- Multi-stage builds for lean production containers
- Container security scanning and best practices
- Introduction to Kubernetes architecture
- Pods, Deployments, and ReplicaSets explained
- Namespaces and resource quotas for multi-tenancy
- Service types and internal communication
- Ingress controllers for external access
- ConfigMaps and Secrets management
- Horizontal Pod Autoscaling mechanisms
- Custom Resource Definitions (CRDs) for extensibility
- Operators for automated application management
- Helm charts for templated deployments
- Kustomize for configuration overlay management
- Cluster lifecycle management with kubeadm
Module 4: Building Scalable Microservices Architectures - Defining bounded contexts with domain-driven design
- Microservices communication patterns (sync and async)
- gRPC vs REST for inter-service communication
- Message brokers: Kafka, RabbitMQ, and NATS
- Schema evolution and backward compatibility
- API gateways and request routing strategies
- Authentication and authorisation across services
- Distributed tracing with OpenTelemetry
- Context propagation in complex call graphs
- Health checks and liveness probes
- Graceful shutdown and startup sequences
- Canary deployments for risk reduction
- Blue-green deployments for zero downtime
- Feature flags and gradual rollouts
- Testing strategies for distributed systems
- Chaos engineering principles and practices
Module 5: Advanced Observability and Telemetry - Logging best practices for containerised environments
- Structured logging with JSON and labels
- Log aggregation with ELK and Grafana Loki
- Metric collection with Prometheus and exporters
- Creating dashboards with Grafana
- Service level objectives and error budgets
- Alerting strategies that prevent noise
- Tracing flows across microservices boundaries
- Correlating logs, metrics, and traces
- Instrumenting applications with OpenTelemetry SDK
- Defining meaningful KPIs for system health
- Latency percentiles and tail latency analysis
- Capacity planning using historical telemetry
- Automated anomaly detection with AI
- Custom metric creation for business logic
- Monitoring multi-region deployments
Module 6: Cloud Native Security and Compliance - Zero Trust architecture in cloud environments
- Principle of least privilege enforcement
- Network policies in Kubernetes clusters
- Role-Based Access Control (RBAC) configuration
- Service account management and hardening
- Image signing and supply chain security
- SBOM generation and vulnerability tracking
- Runtime security with Falco and Sysdig
- Securing APIs with OAuth2 and OpenID Connect
- JWT validation and token introspection
- Data encryption at rest and in transit
- Secrets management with HashiCorp Vault
- Compliance frameworks: SOC 2, ISO 27001, HIPAA
- Audit logging for regulatory requirements
- Policy as code with Open Policy Agent (OPA)
- Security posture assessment with kube-bench
Module 7: Infrastructure as Code and Automation - Introducing Terraform for cloud provisioning
- HCL syntax and configuration structure
- State management and remote backends
- Modules for reusable infrastructure components
- Managing multi-environment deployments
- Dependency management in IaC
- Drift detection and configuration enforcement
- Pulumi for programming cloud infrastructure
- Ansible for configuration management
- Playbooks for system setup and consistency
- Automating patching and updates
- CI/CD pipelines for infrastructure changes
- Testing IaC with Terratest and Kitchen-Terraform
- Policy validation with Sentinel and OPA
- Day 2 operations automation strategies
- Automated rollback and recovery workflows
Module 8: Cloud Native CI/CD and Deployment Pipelines - Designing CI/CD for microservices
- Multi-repo vs monorepo strategies
- Branching models for continuous delivery
- Build optimisation and caching techniques
- Container registry integration (ECR, GCR, etc.)
- Pipeline security with secret injection
- Static code analysis in automated workflows
- Dynamic application security testing (DAST)
- SAST tools integration with SonarQube
- Artifact signing and provenance tracking
- Automated canary analysis with Flagger
- Promotion gates and quality metrics
- Multi-cluster deployment strategies
- Blue-green promotions in Kubernetes
- A/B testing with service mesh routing
- Post-deployment validation and smoke testing
Module 9: Service Mesh and Advanced Networking - Introduction to service mesh architecture
- Istio control plane and data plane
- Envoy proxy and sidecar injection
- VirtualService routing rules
- DestinationRule traffic policies
- Gateway configuration for ingress traffic
- TLS termination and mTLS enforcement
- Traffic mirroring for production testing
- Fault injection for resilience validation
- Request timeouts and retry budgets
- Weighted routing for gradual rollouts
- Service mesh observability integration
- Multi-cluster mesh configuration
- Failover and disaster recovery with mesh
- Network policy enforcement through mesh
- Service mesh performance overhead analysis
Module 10: Serverless and Event-Driven Computing - FaaS vs containerised services comparison
- AWS Lambda, Azure Functions, Google Cloud Functions
- Event sources and triggers configuration
- Function cold start optimisation
- State management in stateless functions
- Event sourcing and stream processing
- Serverless workflows with Step Functions
- Scaling and concurrency limits handling
- Cost optimisation in serverless environments
- Monitoring and debugging serverless apps
- Integrating serverless with Kubernetes
- Security model for untrusted execution
- Persistent storage patterns for ephemeral functions
- Testing serverless logic locally
- CI/CD pipelines for function deployments
- Event-driven orchestration with Apache Kafka
Module 11: Multi-Cloud and Hybrid Cloud Strategies - Advantages and risks of multi-cloud adoption
- Cloud vendor lock-in avoidance techniques
- Workload portability across providers
- Kubernetes Federation for multi-cluster control
- Network connectivity between clouds
- Data replication and latency challenges
- Disaster recovery across regions
- Cost optimisation through cloud bursting
- Consistent security policy enforcement
- Hybrid cloud with on-premises Kubernetes
- Inter-cloud service discovery options
- Unified observability across environments
- Regulatory compliance in global deployments
- Choosing the right cloud for each workload
- Vendor-specific managed services integration
- Infrastructure abstraction layers (Crossplane)
Module 12: Performance, Scalability, and Resilience Engineering - Benchmarking cloud native applications
- Load testing with k6 and Locust
- Stress testing for failure point identification
- Auto-scaling based on custom metrics
- Vertical and horizontal scaling trade-offs
- Cluster autoscaling with node pools
- Pod disruption budgets for stability
- Topology spread constraints for availability
- Quorum-based systems and consensus algorithms
- Leader-follower replication models
- Active-active vs active-passive clustering
- Data sharding and partitioning strategies
- Caching layers with Redis and Memcached
- Content delivery networks integration
- Queue-based load levelling
- Graceful degradation under pressure
Module 13: Data Management in Cloud Native Environments - StatefulSets for persistent workloads
- Persistent volumes and claims in Kubernetes
- StorageClasses and dynamic provisioning
- Cloud-native databases: DynamoDB, Cloud Spanner
- Running PostgreSQL and MySQL in containers
- Sidecar containers for backup and restore
- Database migration strategies with Flyway and Liquibase
- Multi-region database replication
- Consistency models: strong, eventual, causal
- Time-series data handling with InfluxDB
- Log data pipelines with Fluentd and Vector
- Streaming data with Apache Pulsar
- Change Data Capture (CDC) patterns
- Encrypted data storage and key rotation
- Backup automation and verification
- Point-in-time recovery implementation
Module 14: Cloud Native Migrations and Legacy Modernisation - Assessment framework for legacy systems
- Strangler pattern for incremental migration
- Dependency analysis and service extraction
- Database decommissioning strategies
- API façade creation for legacy integration
- Testing migrated services against originals
- Risk mitigation in migration rollouts
- Team reorganisation for cloud native success
- Change management for cultural adoption
- Monitoring legacy and new systems in parallel
- Performance baseline comparison
- Security posture alignment
- Cost analysis pre and post migration
- Zero-downtime cutover planning
- Post-migration optimisation roadmap
- Documenting architectural evolution
Module 15: Certification Preparation & Career Advancement - Mapping course content to industry exams (CKA, CKAD)
- Designing cloud native architecture portfolios
- Translating learning into resume impact
- Using the Certificate of Completion strategically
- Preparing for technical interviews
- Case study development for promotions
- Communicating ROI to management
- Leading cloud transformation initiatives
- Mentoring junior engineers effectively
- Negotiating higher compensation based on new skills
- Building credibility through documentation
- Speaking at internal tech talks and meetups
- Contributing to open source projects
- Staying current with cloud native trends
- Joining CNCF and other professional communities
- Next steps for mastery and specialisation
Module 1: Foundations of Cloud Native Architecture - Defining cloud native vs traditional cloud computing
- Core principles of cloud native design
- Understanding the shift from monolithic to microservices
- Event-driven architecture essentials
- The role of automation in cloud native systems
- Benefits of resilience, scalability, and agility
- Decoupling services for independent deployment
- Stateless vs stateful components in cloud environments
- Service discovery and dynamic networking fundamentals
- Immutable infrastructure concepts and advantages
- GitOps as a foundational practice
- Designing for failure from day one
- Establishing observability as a first-class concern
- Introduction to twelve-factor app methodology
- Architectural trade-offs in distributed systems
- Understanding latency, consistency, and availability
Module 2: Core Cloud Native Design Patterns - Sidecar pattern for modularity and isolation
- Adapter pattern for integration with legacy systems
- Leader election for distributed coordination
- Work queue pattern for asynchronous processing
- Scatter gather for parallel data collection
- Circuit breaker pattern for fault tolerance
- Retry with exponential backoff strategies
- Bulkhead pattern to isolate system failures
- Anti-corruption layer for bounded context protection
- Event sourcing for state reconstruction
- Command Query Responsibility Segregation (CQRS)
- Service mesh integration patterns
- Backpressure handling in streaming systems
- Rate limiting and throttling at scale
- Idempotency design for safe retries
- Token bucket and leaky bucket algorithms
Module 3: Containerisation and Orchestration Frameworks - Docker architecture and image lifecycle
- Creating efficient and secure container images
- Multi-stage builds for lean production containers
- Container security scanning and best practices
- Introduction to Kubernetes architecture
- Pods, Deployments, and ReplicaSets explained
- Namespaces and resource quotas for multi-tenancy
- Service types and internal communication
- Ingress controllers for external access
- ConfigMaps and Secrets management
- Horizontal Pod Autoscaling mechanisms
- Custom Resource Definitions (CRDs) for extensibility
- Operators for automated application management
- Helm charts for templated deployments
- Kustomize for configuration overlay management
- Cluster lifecycle management with kubeadm
Module 4: Building Scalable Microservices Architectures - Defining bounded contexts with domain-driven design
- Microservices communication patterns (sync and async)
- gRPC vs REST for inter-service communication
- Message brokers: Kafka, RabbitMQ, and NATS
- Schema evolution and backward compatibility
- API gateways and request routing strategies
- Authentication and authorisation across services
- Distributed tracing with OpenTelemetry
- Context propagation in complex call graphs
- Health checks and liveness probes
- Graceful shutdown and startup sequences
- Canary deployments for risk reduction
- Blue-green deployments for zero downtime
- Feature flags and gradual rollouts
- Testing strategies for distributed systems
- Chaos engineering principles and practices
Module 5: Advanced Observability and Telemetry - Logging best practices for containerised environments
- Structured logging with JSON and labels
- Log aggregation with ELK and Grafana Loki
- Metric collection with Prometheus and exporters
- Creating dashboards with Grafana
- Service level objectives and error budgets
- Alerting strategies that prevent noise
- Tracing flows across microservices boundaries
- Correlating logs, metrics, and traces
- Instrumenting applications with OpenTelemetry SDK
- Defining meaningful KPIs for system health
- Latency percentiles and tail latency analysis
- Capacity planning using historical telemetry
- Automated anomaly detection with AI
- Custom metric creation for business logic
- Monitoring multi-region deployments
Module 6: Cloud Native Security and Compliance - Zero Trust architecture in cloud environments
- Principle of least privilege enforcement
- Network policies in Kubernetes clusters
- Role-Based Access Control (RBAC) configuration
- Service account management and hardening
- Image signing and supply chain security
- SBOM generation and vulnerability tracking
- Runtime security with Falco and Sysdig
- Securing APIs with OAuth2 and OpenID Connect
- JWT validation and token introspection
- Data encryption at rest and in transit
- Secrets management with HashiCorp Vault
- Compliance frameworks: SOC 2, ISO 27001, HIPAA
- Audit logging for regulatory requirements
- Policy as code with Open Policy Agent (OPA)
- Security posture assessment with kube-bench
Module 7: Infrastructure as Code and Automation - Introducing Terraform for cloud provisioning
- HCL syntax and configuration structure
- State management and remote backends
- Modules for reusable infrastructure components
- Managing multi-environment deployments
- Dependency management in IaC
- Drift detection and configuration enforcement
- Pulumi for programming cloud infrastructure
- Ansible for configuration management
- Playbooks for system setup and consistency
- Automating patching and updates
- CI/CD pipelines for infrastructure changes
- Testing IaC with Terratest and Kitchen-Terraform
- Policy validation with Sentinel and OPA
- Day 2 operations automation strategies
- Automated rollback and recovery workflows
Module 8: Cloud Native CI/CD and Deployment Pipelines - Designing CI/CD for microservices
- Multi-repo vs monorepo strategies
- Branching models for continuous delivery
- Build optimisation and caching techniques
- Container registry integration (ECR, GCR, etc.)
- Pipeline security with secret injection
- Static code analysis in automated workflows
- Dynamic application security testing (DAST)
- SAST tools integration with SonarQube
- Artifact signing and provenance tracking
- Automated canary analysis with Flagger
- Promotion gates and quality metrics
- Multi-cluster deployment strategies
- Blue-green promotions in Kubernetes
- A/B testing with service mesh routing
- Post-deployment validation and smoke testing
Module 9: Service Mesh and Advanced Networking - Introduction to service mesh architecture
- Istio control plane and data plane
- Envoy proxy and sidecar injection
- VirtualService routing rules
- DestinationRule traffic policies
- Gateway configuration for ingress traffic
- TLS termination and mTLS enforcement
- Traffic mirroring for production testing
- Fault injection for resilience validation
- Request timeouts and retry budgets
- Weighted routing for gradual rollouts
- Service mesh observability integration
- Multi-cluster mesh configuration
- Failover and disaster recovery with mesh
- Network policy enforcement through mesh
- Service mesh performance overhead analysis
Module 10: Serverless and Event-Driven Computing - FaaS vs containerised services comparison
- AWS Lambda, Azure Functions, Google Cloud Functions
- Event sources and triggers configuration
- Function cold start optimisation
- State management in stateless functions
- Event sourcing and stream processing
- Serverless workflows with Step Functions
- Scaling and concurrency limits handling
- Cost optimisation in serverless environments
- Monitoring and debugging serverless apps
- Integrating serverless with Kubernetes
- Security model for untrusted execution
- Persistent storage patterns for ephemeral functions
- Testing serverless logic locally
- CI/CD pipelines for function deployments
- Event-driven orchestration with Apache Kafka
Module 11: Multi-Cloud and Hybrid Cloud Strategies - Advantages and risks of multi-cloud adoption
- Cloud vendor lock-in avoidance techniques
- Workload portability across providers
- Kubernetes Federation for multi-cluster control
- Network connectivity between clouds
- Data replication and latency challenges
- Disaster recovery across regions
- Cost optimisation through cloud bursting
- Consistent security policy enforcement
- Hybrid cloud with on-premises Kubernetes
- Inter-cloud service discovery options
- Unified observability across environments
- Regulatory compliance in global deployments
- Choosing the right cloud for each workload
- Vendor-specific managed services integration
- Infrastructure abstraction layers (Crossplane)
Module 12: Performance, Scalability, and Resilience Engineering - Benchmarking cloud native applications
- Load testing with k6 and Locust
- Stress testing for failure point identification
- Auto-scaling based on custom metrics
- Vertical and horizontal scaling trade-offs
- Cluster autoscaling with node pools
- Pod disruption budgets for stability
- Topology spread constraints for availability
- Quorum-based systems and consensus algorithms
- Leader-follower replication models
- Active-active vs active-passive clustering
- Data sharding and partitioning strategies
- Caching layers with Redis and Memcached
- Content delivery networks integration
- Queue-based load levelling
- Graceful degradation under pressure
Module 13: Data Management in Cloud Native Environments - StatefulSets for persistent workloads
- Persistent volumes and claims in Kubernetes
- StorageClasses and dynamic provisioning
- Cloud-native databases: DynamoDB, Cloud Spanner
- Running PostgreSQL and MySQL in containers
- Sidecar containers for backup and restore
- Database migration strategies with Flyway and Liquibase
- Multi-region database replication
- Consistency models: strong, eventual, causal
- Time-series data handling with InfluxDB
- Log data pipelines with Fluentd and Vector
- Streaming data with Apache Pulsar
- Change Data Capture (CDC) patterns
- Encrypted data storage and key rotation
- Backup automation and verification
- Point-in-time recovery implementation
Module 14: Cloud Native Migrations and Legacy Modernisation - Assessment framework for legacy systems
- Strangler pattern for incremental migration
- Dependency analysis and service extraction
- Database decommissioning strategies
- API façade creation for legacy integration
- Testing migrated services against originals
- Risk mitigation in migration rollouts
- Team reorganisation for cloud native success
- Change management for cultural adoption
- Monitoring legacy and new systems in parallel
- Performance baseline comparison
- Security posture alignment
- Cost analysis pre and post migration
- Zero-downtime cutover planning
- Post-migration optimisation roadmap
- Documenting architectural evolution
Module 15: Certification Preparation & Career Advancement - Mapping course content to industry exams (CKA, CKAD)
- Designing cloud native architecture portfolios
- Translating learning into resume impact
- Using the Certificate of Completion strategically
- Preparing for technical interviews
- Case study development for promotions
- Communicating ROI to management
- Leading cloud transformation initiatives
- Mentoring junior engineers effectively
- Negotiating higher compensation based on new skills
- Building credibility through documentation
- Speaking at internal tech talks and meetups
- Contributing to open source projects
- Staying current with cloud native trends
- Joining CNCF and other professional communities
- Next steps for mastery and specialisation
- Sidecar pattern for modularity and isolation
- Adapter pattern for integration with legacy systems
- Leader election for distributed coordination
- Work queue pattern for asynchronous processing
- Scatter gather for parallel data collection
- Circuit breaker pattern for fault tolerance
- Retry with exponential backoff strategies
- Bulkhead pattern to isolate system failures
- Anti-corruption layer for bounded context protection
- Event sourcing for state reconstruction
- Command Query Responsibility Segregation (CQRS)
- Service mesh integration patterns
- Backpressure handling in streaming systems
- Rate limiting and throttling at scale
- Idempotency design for safe retries
- Token bucket and leaky bucket algorithms
Module 3: Containerisation and Orchestration Frameworks - Docker architecture and image lifecycle
- Creating efficient and secure container images
- Multi-stage builds for lean production containers
- Container security scanning and best practices
- Introduction to Kubernetes architecture
- Pods, Deployments, and ReplicaSets explained
- Namespaces and resource quotas for multi-tenancy
- Service types and internal communication
- Ingress controllers for external access
- ConfigMaps and Secrets management
- Horizontal Pod Autoscaling mechanisms
- Custom Resource Definitions (CRDs) for extensibility
- Operators for automated application management
- Helm charts for templated deployments
- Kustomize for configuration overlay management
- Cluster lifecycle management with kubeadm
Module 4: Building Scalable Microservices Architectures - Defining bounded contexts with domain-driven design
- Microservices communication patterns (sync and async)
- gRPC vs REST for inter-service communication
- Message brokers: Kafka, RabbitMQ, and NATS
- Schema evolution and backward compatibility
- API gateways and request routing strategies
- Authentication and authorisation across services
- Distributed tracing with OpenTelemetry
- Context propagation in complex call graphs
- Health checks and liveness probes
- Graceful shutdown and startup sequences
- Canary deployments for risk reduction
- Blue-green deployments for zero downtime
- Feature flags and gradual rollouts
- Testing strategies for distributed systems
- Chaos engineering principles and practices
Module 5: Advanced Observability and Telemetry - Logging best practices for containerised environments
- Structured logging with JSON and labels
- Log aggregation with ELK and Grafana Loki
- Metric collection with Prometheus and exporters
- Creating dashboards with Grafana
- Service level objectives and error budgets
- Alerting strategies that prevent noise
- Tracing flows across microservices boundaries
- Correlating logs, metrics, and traces
- Instrumenting applications with OpenTelemetry SDK
- Defining meaningful KPIs for system health
- Latency percentiles and tail latency analysis
- Capacity planning using historical telemetry
- Automated anomaly detection with AI
- Custom metric creation for business logic
- Monitoring multi-region deployments
Module 6: Cloud Native Security and Compliance - Zero Trust architecture in cloud environments
- Principle of least privilege enforcement
- Network policies in Kubernetes clusters
- Role-Based Access Control (RBAC) configuration
- Service account management and hardening
- Image signing and supply chain security
- SBOM generation and vulnerability tracking
- Runtime security with Falco and Sysdig
- Securing APIs with OAuth2 and OpenID Connect
- JWT validation and token introspection
- Data encryption at rest and in transit
- Secrets management with HashiCorp Vault
- Compliance frameworks: SOC 2, ISO 27001, HIPAA
- Audit logging for regulatory requirements
- Policy as code with Open Policy Agent (OPA)
- Security posture assessment with kube-bench
Module 7: Infrastructure as Code and Automation - Introducing Terraform for cloud provisioning
- HCL syntax and configuration structure
- State management and remote backends
- Modules for reusable infrastructure components
- Managing multi-environment deployments
- Dependency management in IaC
- Drift detection and configuration enforcement
- Pulumi for programming cloud infrastructure
- Ansible for configuration management
- Playbooks for system setup and consistency
- Automating patching and updates
- CI/CD pipelines for infrastructure changes
- Testing IaC with Terratest and Kitchen-Terraform
- Policy validation with Sentinel and OPA
- Day 2 operations automation strategies
- Automated rollback and recovery workflows
Module 8: Cloud Native CI/CD and Deployment Pipelines - Designing CI/CD for microservices
- Multi-repo vs monorepo strategies
- Branching models for continuous delivery
- Build optimisation and caching techniques
- Container registry integration (ECR, GCR, etc.)
- Pipeline security with secret injection
- Static code analysis in automated workflows
- Dynamic application security testing (DAST)
- SAST tools integration with SonarQube
- Artifact signing and provenance tracking
- Automated canary analysis with Flagger
- Promotion gates and quality metrics
- Multi-cluster deployment strategies
- Blue-green promotions in Kubernetes
- A/B testing with service mesh routing
- Post-deployment validation and smoke testing
Module 9: Service Mesh and Advanced Networking - Introduction to service mesh architecture
- Istio control plane and data plane
- Envoy proxy and sidecar injection
- VirtualService routing rules
- DestinationRule traffic policies
- Gateway configuration for ingress traffic
- TLS termination and mTLS enforcement
- Traffic mirroring for production testing
- Fault injection for resilience validation
- Request timeouts and retry budgets
- Weighted routing for gradual rollouts
- Service mesh observability integration
- Multi-cluster mesh configuration
- Failover and disaster recovery with mesh
- Network policy enforcement through mesh
- Service mesh performance overhead analysis
Module 10: Serverless and Event-Driven Computing - FaaS vs containerised services comparison
- AWS Lambda, Azure Functions, Google Cloud Functions
- Event sources and triggers configuration
- Function cold start optimisation
- State management in stateless functions
- Event sourcing and stream processing
- Serverless workflows with Step Functions
- Scaling and concurrency limits handling
- Cost optimisation in serverless environments
- Monitoring and debugging serverless apps
- Integrating serverless with Kubernetes
- Security model for untrusted execution
- Persistent storage patterns for ephemeral functions
- Testing serverless logic locally
- CI/CD pipelines for function deployments
- Event-driven orchestration with Apache Kafka
Module 11: Multi-Cloud and Hybrid Cloud Strategies - Advantages and risks of multi-cloud adoption
- Cloud vendor lock-in avoidance techniques
- Workload portability across providers
- Kubernetes Federation for multi-cluster control
- Network connectivity between clouds
- Data replication and latency challenges
- Disaster recovery across regions
- Cost optimisation through cloud bursting
- Consistent security policy enforcement
- Hybrid cloud with on-premises Kubernetes
- Inter-cloud service discovery options
- Unified observability across environments
- Regulatory compliance in global deployments
- Choosing the right cloud for each workload
- Vendor-specific managed services integration
- Infrastructure abstraction layers (Crossplane)
Module 12: Performance, Scalability, and Resilience Engineering - Benchmarking cloud native applications
- Load testing with k6 and Locust
- Stress testing for failure point identification
- Auto-scaling based on custom metrics
- Vertical and horizontal scaling trade-offs
- Cluster autoscaling with node pools
- Pod disruption budgets for stability
- Topology spread constraints for availability
- Quorum-based systems and consensus algorithms
- Leader-follower replication models
- Active-active vs active-passive clustering
- Data sharding and partitioning strategies
- Caching layers with Redis and Memcached
- Content delivery networks integration
- Queue-based load levelling
- Graceful degradation under pressure
Module 13: Data Management in Cloud Native Environments - StatefulSets for persistent workloads
- Persistent volumes and claims in Kubernetes
- StorageClasses and dynamic provisioning
- Cloud-native databases: DynamoDB, Cloud Spanner
- Running PostgreSQL and MySQL in containers
- Sidecar containers for backup and restore
- Database migration strategies with Flyway and Liquibase
- Multi-region database replication
- Consistency models: strong, eventual, causal
- Time-series data handling with InfluxDB
- Log data pipelines with Fluentd and Vector
- Streaming data with Apache Pulsar
- Change Data Capture (CDC) patterns
- Encrypted data storage and key rotation
- Backup automation and verification
- Point-in-time recovery implementation
Module 14: Cloud Native Migrations and Legacy Modernisation - Assessment framework for legacy systems
- Strangler pattern for incremental migration
- Dependency analysis and service extraction
- Database decommissioning strategies
- API façade creation for legacy integration
- Testing migrated services against originals
- Risk mitigation in migration rollouts
- Team reorganisation for cloud native success
- Change management for cultural adoption
- Monitoring legacy and new systems in parallel
- Performance baseline comparison
- Security posture alignment
- Cost analysis pre and post migration
- Zero-downtime cutover planning
- Post-migration optimisation roadmap
- Documenting architectural evolution
Module 15: Certification Preparation & Career Advancement - Mapping course content to industry exams (CKA, CKAD)
- Designing cloud native architecture portfolios
- Translating learning into resume impact
- Using the Certificate of Completion strategically
- Preparing for technical interviews
- Case study development for promotions
- Communicating ROI to management
- Leading cloud transformation initiatives
- Mentoring junior engineers effectively
- Negotiating higher compensation based on new skills
- Building credibility through documentation
- Speaking at internal tech talks and meetups
- Contributing to open source projects
- Staying current with cloud native trends
- Joining CNCF and other professional communities
- Next steps for mastery and specialisation
- Defining bounded contexts with domain-driven design
- Microservices communication patterns (sync and async)
- gRPC vs REST for inter-service communication
- Message brokers: Kafka, RabbitMQ, and NATS
- Schema evolution and backward compatibility
- API gateways and request routing strategies
- Authentication and authorisation across services
- Distributed tracing with OpenTelemetry
- Context propagation in complex call graphs
- Health checks and liveness probes
- Graceful shutdown and startup sequences
- Canary deployments for risk reduction
- Blue-green deployments for zero downtime
- Feature flags and gradual rollouts
- Testing strategies for distributed systems
- Chaos engineering principles and practices
Module 5: Advanced Observability and Telemetry - Logging best practices for containerised environments
- Structured logging with JSON and labels
- Log aggregation with ELK and Grafana Loki
- Metric collection with Prometheus and exporters
- Creating dashboards with Grafana
- Service level objectives and error budgets
- Alerting strategies that prevent noise
- Tracing flows across microservices boundaries
- Correlating logs, metrics, and traces
- Instrumenting applications with OpenTelemetry SDK
- Defining meaningful KPIs for system health
- Latency percentiles and tail latency analysis
- Capacity planning using historical telemetry
- Automated anomaly detection with AI
- Custom metric creation for business logic
- Monitoring multi-region deployments
Module 6: Cloud Native Security and Compliance - Zero Trust architecture in cloud environments
- Principle of least privilege enforcement
- Network policies in Kubernetes clusters
- Role-Based Access Control (RBAC) configuration
- Service account management and hardening
- Image signing and supply chain security
- SBOM generation and vulnerability tracking
- Runtime security with Falco and Sysdig
- Securing APIs with OAuth2 and OpenID Connect
- JWT validation and token introspection
- Data encryption at rest and in transit
- Secrets management with HashiCorp Vault
- Compliance frameworks: SOC 2, ISO 27001, HIPAA
- Audit logging for regulatory requirements
- Policy as code with Open Policy Agent (OPA)
- Security posture assessment with kube-bench
Module 7: Infrastructure as Code and Automation - Introducing Terraform for cloud provisioning
- HCL syntax and configuration structure
- State management and remote backends
- Modules for reusable infrastructure components
- Managing multi-environment deployments
- Dependency management in IaC
- Drift detection and configuration enforcement
- Pulumi for programming cloud infrastructure
- Ansible for configuration management
- Playbooks for system setup and consistency
- Automating patching and updates
- CI/CD pipelines for infrastructure changes
- Testing IaC with Terratest and Kitchen-Terraform
- Policy validation with Sentinel and OPA
- Day 2 operations automation strategies
- Automated rollback and recovery workflows
Module 8: Cloud Native CI/CD and Deployment Pipelines - Designing CI/CD for microservices
- Multi-repo vs monorepo strategies
- Branching models for continuous delivery
- Build optimisation and caching techniques
- Container registry integration (ECR, GCR, etc.)
- Pipeline security with secret injection
- Static code analysis in automated workflows
- Dynamic application security testing (DAST)
- SAST tools integration with SonarQube
- Artifact signing and provenance tracking
- Automated canary analysis with Flagger
- Promotion gates and quality metrics
- Multi-cluster deployment strategies
- Blue-green promotions in Kubernetes
- A/B testing with service mesh routing
- Post-deployment validation and smoke testing
Module 9: Service Mesh and Advanced Networking - Introduction to service mesh architecture
- Istio control plane and data plane
- Envoy proxy and sidecar injection
- VirtualService routing rules
- DestinationRule traffic policies
- Gateway configuration for ingress traffic
- TLS termination and mTLS enforcement
- Traffic mirroring for production testing
- Fault injection for resilience validation
- Request timeouts and retry budgets
- Weighted routing for gradual rollouts
- Service mesh observability integration
- Multi-cluster mesh configuration
- Failover and disaster recovery with mesh
- Network policy enforcement through mesh
- Service mesh performance overhead analysis
Module 10: Serverless and Event-Driven Computing - FaaS vs containerised services comparison
- AWS Lambda, Azure Functions, Google Cloud Functions
- Event sources and triggers configuration
- Function cold start optimisation
- State management in stateless functions
- Event sourcing and stream processing
- Serverless workflows with Step Functions
- Scaling and concurrency limits handling
- Cost optimisation in serverless environments
- Monitoring and debugging serverless apps
- Integrating serverless with Kubernetes
- Security model for untrusted execution
- Persistent storage patterns for ephemeral functions
- Testing serverless logic locally
- CI/CD pipelines for function deployments
- Event-driven orchestration with Apache Kafka
Module 11: Multi-Cloud and Hybrid Cloud Strategies - Advantages and risks of multi-cloud adoption
- Cloud vendor lock-in avoidance techniques
- Workload portability across providers
- Kubernetes Federation for multi-cluster control
- Network connectivity between clouds
- Data replication and latency challenges
- Disaster recovery across regions
- Cost optimisation through cloud bursting
- Consistent security policy enforcement
- Hybrid cloud with on-premises Kubernetes
- Inter-cloud service discovery options
- Unified observability across environments
- Regulatory compliance in global deployments
- Choosing the right cloud for each workload
- Vendor-specific managed services integration
- Infrastructure abstraction layers (Crossplane)
Module 12: Performance, Scalability, and Resilience Engineering - Benchmarking cloud native applications
- Load testing with k6 and Locust
- Stress testing for failure point identification
- Auto-scaling based on custom metrics
- Vertical and horizontal scaling trade-offs
- Cluster autoscaling with node pools
- Pod disruption budgets for stability
- Topology spread constraints for availability
- Quorum-based systems and consensus algorithms
- Leader-follower replication models
- Active-active vs active-passive clustering
- Data sharding and partitioning strategies
- Caching layers with Redis and Memcached
- Content delivery networks integration
- Queue-based load levelling
- Graceful degradation under pressure
Module 13: Data Management in Cloud Native Environments - StatefulSets for persistent workloads
- Persistent volumes and claims in Kubernetes
- StorageClasses and dynamic provisioning
- Cloud-native databases: DynamoDB, Cloud Spanner
- Running PostgreSQL and MySQL in containers
- Sidecar containers for backup and restore
- Database migration strategies with Flyway and Liquibase
- Multi-region database replication
- Consistency models: strong, eventual, causal
- Time-series data handling with InfluxDB
- Log data pipelines with Fluentd and Vector
- Streaming data with Apache Pulsar
- Change Data Capture (CDC) patterns
- Encrypted data storage and key rotation
- Backup automation and verification
- Point-in-time recovery implementation
Module 14: Cloud Native Migrations and Legacy Modernisation - Assessment framework for legacy systems
- Strangler pattern for incremental migration
- Dependency analysis and service extraction
- Database decommissioning strategies
- API façade creation for legacy integration
- Testing migrated services against originals
- Risk mitigation in migration rollouts
- Team reorganisation for cloud native success
- Change management for cultural adoption
- Monitoring legacy and new systems in parallel
- Performance baseline comparison
- Security posture alignment
- Cost analysis pre and post migration
- Zero-downtime cutover planning
- Post-migration optimisation roadmap
- Documenting architectural evolution
Module 15: Certification Preparation & Career Advancement - Mapping course content to industry exams (CKA, CKAD)
- Designing cloud native architecture portfolios
- Translating learning into resume impact
- Using the Certificate of Completion strategically
- Preparing for technical interviews
- Case study development for promotions
- Communicating ROI to management
- Leading cloud transformation initiatives
- Mentoring junior engineers effectively
- Negotiating higher compensation based on new skills
- Building credibility through documentation
- Speaking at internal tech talks and meetups
- Contributing to open source projects
- Staying current with cloud native trends
- Joining CNCF and other professional communities
- Next steps for mastery and specialisation
- Zero Trust architecture in cloud environments
- Principle of least privilege enforcement
- Network policies in Kubernetes clusters
- Role-Based Access Control (RBAC) configuration
- Service account management and hardening
- Image signing and supply chain security
- SBOM generation and vulnerability tracking
- Runtime security with Falco and Sysdig
- Securing APIs with OAuth2 and OpenID Connect
- JWT validation and token introspection
- Data encryption at rest and in transit
- Secrets management with HashiCorp Vault
- Compliance frameworks: SOC 2, ISO 27001, HIPAA
- Audit logging for regulatory requirements
- Policy as code with Open Policy Agent (OPA)
- Security posture assessment with kube-bench
Module 7: Infrastructure as Code and Automation - Introducing Terraform for cloud provisioning
- HCL syntax and configuration structure
- State management and remote backends
- Modules for reusable infrastructure components
- Managing multi-environment deployments
- Dependency management in IaC
- Drift detection and configuration enforcement
- Pulumi for programming cloud infrastructure
- Ansible for configuration management
- Playbooks for system setup and consistency
- Automating patching and updates
- CI/CD pipelines for infrastructure changes
- Testing IaC with Terratest and Kitchen-Terraform
- Policy validation with Sentinel and OPA
- Day 2 operations automation strategies
- Automated rollback and recovery workflows
Module 8: Cloud Native CI/CD and Deployment Pipelines - Designing CI/CD for microservices
- Multi-repo vs monorepo strategies
- Branching models for continuous delivery
- Build optimisation and caching techniques
- Container registry integration (ECR, GCR, etc.)
- Pipeline security with secret injection
- Static code analysis in automated workflows
- Dynamic application security testing (DAST)
- SAST tools integration with SonarQube
- Artifact signing and provenance tracking
- Automated canary analysis with Flagger
- Promotion gates and quality metrics
- Multi-cluster deployment strategies
- Blue-green promotions in Kubernetes
- A/B testing with service mesh routing
- Post-deployment validation and smoke testing
Module 9: Service Mesh and Advanced Networking - Introduction to service mesh architecture
- Istio control plane and data plane
- Envoy proxy and sidecar injection
- VirtualService routing rules
- DestinationRule traffic policies
- Gateway configuration for ingress traffic
- TLS termination and mTLS enforcement
- Traffic mirroring for production testing
- Fault injection for resilience validation
- Request timeouts and retry budgets
- Weighted routing for gradual rollouts
- Service mesh observability integration
- Multi-cluster mesh configuration
- Failover and disaster recovery with mesh
- Network policy enforcement through mesh
- Service mesh performance overhead analysis
Module 10: Serverless and Event-Driven Computing - FaaS vs containerised services comparison
- AWS Lambda, Azure Functions, Google Cloud Functions
- Event sources and triggers configuration
- Function cold start optimisation
- State management in stateless functions
- Event sourcing and stream processing
- Serverless workflows with Step Functions
- Scaling and concurrency limits handling
- Cost optimisation in serverless environments
- Monitoring and debugging serverless apps
- Integrating serverless with Kubernetes
- Security model for untrusted execution
- Persistent storage patterns for ephemeral functions
- Testing serverless logic locally
- CI/CD pipelines for function deployments
- Event-driven orchestration with Apache Kafka
Module 11: Multi-Cloud and Hybrid Cloud Strategies - Advantages and risks of multi-cloud adoption
- Cloud vendor lock-in avoidance techniques
- Workload portability across providers
- Kubernetes Federation for multi-cluster control
- Network connectivity between clouds
- Data replication and latency challenges
- Disaster recovery across regions
- Cost optimisation through cloud bursting
- Consistent security policy enforcement
- Hybrid cloud with on-premises Kubernetes
- Inter-cloud service discovery options
- Unified observability across environments
- Regulatory compliance in global deployments
- Choosing the right cloud for each workload
- Vendor-specific managed services integration
- Infrastructure abstraction layers (Crossplane)
Module 12: Performance, Scalability, and Resilience Engineering - Benchmarking cloud native applications
- Load testing with k6 and Locust
- Stress testing for failure point identification
- Auto-scaling based on custom metrics
- Vertical and horizontal scaling trade-offs
- Cluster autoscaling with node pools
- Pod disruption budgets for stability
- Topology spread constraints for availability
- Quorum-based systems and consensus algorithms
- Leader-follower replication models
- Active-active vs active-passive clustering
- Data sharding and partitioning strategies
- Caching layers with Redis and Memcached
- Content delivery networks integration
- Queue-based load levelling
- Graceful degradation under pressure
Module 13: Data Management in Cloud Native Environments - StatefulSets for persistent workloads
- Persistent volumes and claims in Kubernetes
- StorageClasses and dynamic provisioning
- Cloud-native databases: DynamoDB, Cloud Spanner
- Running PostgreSQL and MySQL in containers
- Sidecar containers for backup and restore
- Database migration strategies with Flyway and Liquibase
- Multi-region database replication
- Consistency models: strong, eventual, causal
- Time-series data handling with InfluxDB
- Log data pipelines with Fluentd and Vector
- Streaming data with Apache Pulsar
- Change Data Capture (CDC) patterns
- Encrypted data storage and key rotation
- Backup automation and verification
- Point-in-time recovery implementation
Module 14: Cloud Native Migrations and Legacy Modernisation - Assessment framework for legacy systems
- Strangler pattern for incremental migration
- Dependency analysis and service extraction
- Database decommissioning strategies
- API façade creation for legacy integration
- Testing migrated services against originals
- Risk mitigation in migration rollouts
- Team reorganisation for cloud native success
- Change management for cultural adoption
- Monitoring legacy and new systems in parallel
- Performance baseline comparison
- Security posture alignment
- Cost analysis pre and post migration
- Zero-downtime cutover planning
- Post-migration optimisation roadmap
- Documenting architectural evolution
Module 15: Certification Preparation & Career Advancement - Mapping course content to industry exams (CKA, CKAD)
- Designing cloud native architecture portfolios
- Translating learning into resume impact
- Using the Certificate of Completion strategically
- Preparing for technical interviews
- Case study development for promotions
- Communicating ROI to management
- Leading cloud transformation initiatives
- Mentoring junior engineers effectively
- Negotiating higher compensation based on new skills
- Building credibility through documentation
- Speaking at internal tech talks and meetups
- Contributing to open source projects
- Staying current with cloud native trends
- Joining CNCF and other professional communities
- Next steps for mastery and specialisation
- Designing CI/CD for microservices
- Multi-repo vs monorepo strategies
- Branching models for continuous delivery
- Build optimisation and caching techniques
- Container registry integration (ECR, GCR, etc.)
- Pipeline security with secret injection
- Static code analysis in automated workflows
- Dynamic application security testing (DAST)
- SAST tools integration with SonarQube
- Artifact signing and provenance tracking
- Automated canary analysis with Flagger
- Promotion gates and quality metrics
- Multi-cluster deployment strategies
- Blue-green promotions in Kubernetes
- A/B testing with service mesh routing
- Post-deployment validation and smoke testing
Module 9: Service Mesh and Advanced Networking - Introduction to service mesh architecture
- Istio control plane and data plane
- Envoy proxy and sidecar injection
- VirtualService routing rules
- DestinationRule traffic policies
- Gateway configuration for ingress traffic
- TLS termination and mTLS enforcement
- Traffic mirroring for production testing
- Fault injection for resilience validation
- Request timeouts and retry budgets
- Weighted routing for gradual rollouts
- Service mesh observability integration
- Multi-cluster mesh configuration
- Failover and disaster recovery with mesh
- Network policy enforcement through mesh
- Service mesh performance overhead analysis
Module 10: Serverless and Event-Driven Computing - FaaS vs containerised services comparison
- AWS Lambda, Azure Functions, Google Cloud Functions
- Event sources and triggers configuration
- Function cold start optimisation
- State management in stateless functions
- Event sourcing and stream processing
- Serverless workflows with Step Functions
- Scaling and concurrency limits handling
- Cost optimisation in serverless environments
- Monitoring and debugging serverless apps
- Integrating serverless with Kubernetes
- Security model for untrusted execution
- Persistent storage patterns for ephemeral functions
- Testing serverless logic locally
- CI/CD pipelines for function deployments
- Event-driven orchestration with Apache Kafka
Module 11: Multi-Cloud and Hybrid Cloud Strategies - Advantages and risks of multi-cloud adoption
- Cloud vendor lock-in avoidance techniques
- Workload portability across providers
- Kubernetes Federation for multi-cluster control
- Network connectivity between clouds
- Data replication and latency challenges
- Disaster recovery across regions
- Cost optimisation through cloud bursting
- Consistent security policy enforcement
- Hybrid cloud with on-premises Kubernetes
- Inter-cloud service discovery options
- Unified observability across environments
- Regulatory compliance in global deployments
- Choosing the right cloud for each workload
- Vendor-specific managed services integration
- Infrastructure abstraction layers (Crossplane)
Module 12: Performance, Scalability, and Resilience Engineering - Benchmarking cloud native applications
- Load testing with k6 and Locust
- Stress testing for failure point identification
- Auto-scaling based on custom metrics
- Vertical and horizontal scaling trade-offs
- Cluster autoscaling with node pools
- Pod disruption budgets for stability
- Topology spread constraints for availability
- Quorum-based systems and consensus algorithms
- Leader-follower replication models
- Active-active vs active-passive clustering
- Data sharding and partitioning strategies
- Caching layers with Redis and Memcached
- Content delivery networks integration
- Queue-based load levelling
- Graceful degradation under pressure
Module 13: Data Management in Cloud Native Environments - StatefulSets for persistent workloads
- Persistent volumes and claims in Kubernetes
- StorageClasses and dynamic provisioning
- Cloud-native databases: DynamoDB, Cloud Spanner
- Running PostgreSQL and MySQL in containers
- Sidecar containers for backup and restore
- Database migration strategies with Flyway and Liquibase
- Multi-region database replication
- Consistency models: strong, eventual, causal
- Time-series data handling with InfluxDB
- Log data pipelines with Fluentd and Vector
- Streaming data with Apache Pulsar
- Change Data Capture (CDC) patterns
- Encrypted data storage and key rotation
- Backup automation and verification
- Point-in-time recovery implementation
Module 14: Cloud Native Migrations and Legacy Modernisation - Assessment framework for legacy systems
- Strangler pattern for incremental migration
- Dependency analysis and service extraction
- Database decommissioning strategies
- API façade creation for legacy integration
- Testing migrated services against originals
- Risk mitigation in migration rollouts
- Team reorganisation for cloud native success
- Change management for cultural adoption
- Monitoring legacy and new systems in parallel
- Performance baseline comparison
- Security posture alignment
- Cost analysis pre and post migration
- Zero-downtime cutover planning
- Post-migration optimisation roadmap
- Documenting architectural evolution
Module 15: Certification Preparation & Career Advancement - Mapping course content to industry exams (CKA, CKAD)
- Designing cloud native architecture portfolios
- Translating learning into resume impact
- Using the Certificate of Completion strategically
- Preparing for technical interviews
- Case study development for promotions
- Communicating ROI to management
- Leading cloud transformation initiatives
- Mentoring junior engineers effectively
- Negotiating higher compensation based on new skills
- Building credibility through documentation
- Speaking at internal tech talks and meetups
- Contributing to open source projects
- Staying current with cloud native trends
- Joining CNCF and other professional communities
- Next steps for mastery and specialisation
- FaaS vs containerised services comparison
- AWS Lambda, Azure Functions, Google Cloud Functions
- Event sources and triggers configuration
- Function cold start optimisation
- State management in stateless functions
- Event sourcing and stream processing
- Serverless workflows with Step Functions
- Scaling and concurrency limits handling
- Cost optimisation in serverless environments
- Monitoring and debugging serverless apps
- Integrating serverless with Kubernetes
- Security model for untrusted execution
- Persistent storage patterns for ephemeral functions
- Testing serverless logic locally
- CI/CD pipelines for function deployments
- Event-driven orchestration with Apache Kafka
Module 11: Multi-Cloud and Hybrid Cloud Strategies - Advantages and risks of multi-cloud adoption
- Cloud vendor lock-in avoidance techniques
- Workload portability across providers
- Kubernetes Federation for multi-cluster control
- Network connectivity between clouds
- Data replication and latency challenges
- Disaster recovery across regions
- Cost optimisation through cloud bursting
- Consistent security policy enforcement
- Hybrid cloud with on-premises Kubernetes
- Inter-cloud service discovery options
- Unified observability across environments
- Regulatory compliance in global deployments
- Choosing the right cloud for each workload
- Vendor-specific managed services integration
- Infrastructure abstraction layers (Crossplane)
Module 12: Performance, Scalability, and Resilience Engineering - Benchmarking cloud native applications
- Load testing with k6 and Locust
- Stress testing for failure point identification
- Auto-scaling based on custom metrics
- Vertical and horizontal scaling trade-offs
- Cluster autoscaling with node pools
- Pod disruption budgets for stability
- Topology spread constraints for availability
- Quorum-based systems and consensus algorithms
- Leader-follower replication models
- Active-active vs active-passive clustering
- Data sharding and partitioning strategies
- Caching layers with Redis and Memcached
- Content delivery networks integration
- Queue-based load levelling
- Graceful degradation under pressure
Module 13: Data Management in Cloud Native Environments - StatefulSets for persistent workloads
- Persistent volumes and claims in Kubernetes
- StorageClasses and dynamic provisioning
- Cloud-native databases: DynamoDB, Cloud Spanner
- Running PostgreSQL and MySQL in containers
- Sidecar containers for backup and restore
- Database migration strategies with Flyway and Liquibase
- Multi-region database replication
- Consistency models: strong, eventual, causal
- Time-series data handling with InfluxDB
- Log data pipelines with Fluentd and Vector
- Streaming data with Apache Pulsar
- Change Data Capture (CDC) patterns
- Encrypted data storage and key rotation
- Backup automation and verification
- Point-in-time recovery implementation
Module 14: Cloud Native Migrations and Legacy Modernisation - Assessment framework for legacy systems
- Strangler pattern for incremental migration
- Dependency analysis and service extraction
- Database decommissioning strategies
- API façade creation for legacy integration
- Testing migrated services against originals
- Risk mitigation in migration rollouts
- Team reorganisation for cloud native success
- Change management for cultural adoption
- Monitoring legacy and new systems in parallel
- Performance baseline comparison
- Security posture alignment
- Cost analysis pre and post migration
- Zero-downtime cutover planning
- Post-migration optimisation roadmap
- Documenting architectural evolution
Module 15: Certification Preparation & Career Advancement - Mapping course content to industry exams (CKA, CKAD)
- Designing cloud native architecture portfolios
- Translating learning into resume impact
- Using the Certificate of Completion strategically
- Preparing for technical interviews
- Case study development for promotions
- Communicating ROI to management
- Leading cloud transformation initiatives
- Mentoring junior engineers effectively
- Negotiating higher compensation based on new skills
- Building credibility through documentation
- Speaking at internal tech talks and meetups
- Contributing to open source projects
- Staying current with cloud native trends
- Joining CNCF and other professional communities
- Next steps for mastery and specialisation
- Benchmarking cloud native applications
- Load testing with k6 and Locust
- Stress testing for failure point identification
- Auto-scaling based on custom metrics
- Vertical and horizontal scaling trade-offs
- Cluster autoscaling with node pools
- Pod disruption budgets for stability
- Topology spread constraints for availability
- Quorum-based systems and consensus algorithms
- Leader-follower replication models
- Active-active vs active-passive clustering
- Data sharding and partitioning strategies
- Caching layers with Redis and Memcached
- Content delivery networks integration
- Queue-based load levelling
- Graceful degradation under pressure
Module 13: Data Management in Cloud Native Environments - StatefulSets for persistent workloads
- Persistent volumes and claims in Kubernetes
- StorageClasses and dynamic provisioning
- Cloud-native databases: DynamoDB, Cloud Spanner
- Running PostgreSQL and MySQL in containers
- Sidecar containers for backup and restore
- Database migration strategies with Flyway and Liquibase
- Multi-region database replication
- Consistency models: strong, eventual, causal
- Time-series data handling with InfluxDB
- Log data pipelines with Fluentd and Vector
- Streaming data with Apache Pulsar
- Change Data Capture (CDC) patterns
- Encrypted data storage and key rotation
- Backup automation and verification
- Point-in-time recovery implementation
Module 14: Cloud Native Migrations and Legacy Modernisation - Assessment framework for legacy systems
- Strangler pattern for incremental migration
- Dependency analysis and service extraction
- Database decommissioning strategies
- API façade creation for legacy integration
- Testing migrated services against originals
- Risk mitigation in migration rollouts
- Team reorganisation for cloud native success
- Change management for cultural adoption
- Monitoring legacy and new systems in parallel
- Performance baseline comparison
- Security posture alignment
- Cost analysis pre and post migration
- Zero-downtime cutover planning
- Post-migration optimisation roadmap
- Documenting architectural evolution
Module 15: Certification Preparation & Career Advancement - Mapping course content to industry exams (CKA, CKAD)
- Designing cloud native architecture portfolios
- Translating learning into resume impact
- Using the Certificate of Completion strategically
- Preparing for technical interviews
- Case study development for promotions
- Communicating ROI to management
- Leading cloud transformation initiatives
- Mentoring junior engineers effectively
- Negotiating higher compensation based on new skills
- Building credibility through documentation
- Speaking at internal tech talks and meetups
- Contributing to open source projects
- Staying current with cloud native trends
- Joining CNCF and other professional communities
- Next steps for mastery and specialisation
- Assessment framework for legacy systems
- Strangler pattern for incremental migration
- Dependency analysis and service extraction
- Database decommissioning strategies
- API façade creation for legacy integration
- Testing migrated services against originals
- Risk mitigation in migration rollouts
- Team reorganisation for cloud native success
- Change management for cultural adoption
- Monitoring legacy and new systems in parallel
- Performance baseline comparison
- Security posture alignment
- Cost analysis pre and post migration
- Zero-downtime cutover planning
- Post-migration optimisation roadmap
- Documenting architectural evolution