Kubernetes Easy to Learn and Practice Labs end2end

Kubernetes Easy to Learn and Practice Labs end2end

Index:

  1. Kubernetes Cluster Setup
  2. Kubernetes Workload and Configuration 
  • Kubernetes Workload 
  • – Workload Overview 
  • – Kubernetes Pods 
  • – Deployments
  • – DaemonSets
  • – StatefulSets
  • – ReplicaSets
  • – Job and Cron Jobs
  • – Stateful vs Stateless
  • – Application Health Checks
  • – Resources Requests and Limits 
  • Service and Ingress
  • – Services Overview 
  • – ClusterIP Overview 
  • – NodePort Service 
  • – LoadBalancer Service 
  • – ExternalName Service
  • – Kubernetes Ingress 
  • – Ingress Controller 
  • – Nginx Ingress Controller 
  • – SSL – Self Signed 
  • – SSL – Let’s Encrypt  
  • API Gateway and Service Mesh 
  • Configurations
  • – Secrets 
  • – ConfigMaps
  • – Command and Arguments
  • – Objects Metadata
  • – Labels & Selectors
  • – Node Lablabels and Selector 
  • Volumes 
  • –  Volumes Overview 
  • –  Persistent Volumes 
  • –  Persistent Volumes Claims
  1. Kubernetes Security and Management 
  • AutoScaling 
  • Resource Quotas
  • RBAC Authorization
  • Network Policy 
  • Cluster Upgrade
  • Kubectl Commands
  • Troubleshooting 
  1. Kubernetes Monitoring and Logging 
  • Monitoring Overview 
  • Kubernetes Dashboard 
  • Prometheus Operator 
  • Logging Overview 
  • Elastic Stack 
  • New Relic Integration

A. Kubernetes Cluster Setup and Other Knowledge that you need

  1. Self-Hosted Cluster Setup with Kubadm Step-by-Step for your Lab-Setup 
  2. Kubernetes Learning Roadmap 
  3. Kubernetes Cheatsheet 
  4. CKA Exam Prep
  5. Mastering YAML for Kubernetes 
  6. Enhancing Microservices Architecture with Service Mesh and API Gateway 

B. Kubernetes Workload and Configuration 

Kubernetes Workload:

  • Workload Overview: Understand various types of workloads managed by Kubernetes.
  • Kubernetes Pods: Basic building blocks of Kubernetes, encapsulating an application’s container(s).
  • Deployments: Manage deployment and scaling of Pods, ensuring high availability.
  • DaemonSets: Ensure each node runs a copy of a Pod, typically for system-level tasks.
  • StatefulSets: Manage stateful applications, ensuring stable, unique network identifiers and persistent storage.
  • ReplicaSets: Maintain a set number of identical Pods, ensuring fault tolerance and scalability.
  • Job and Cron Jobs: Run short-lived tasks or batch jobs once or on a schedule.
  • Stateful vs Stateless: Understand the difference between stateful and stateless applications in Kubernetes.
  • Application Health Checks: Monitor and maintain application health with liveness and readiness probes.
  • Resources Requests and Limits: Define resource requirements and constraints for Pods.

Service and Ingress:

  • Services Overview: Abstract and expose application functionality within the cluster or to external sources.
  • ClusterIP Overview: Provide internal access to services within the cluster.
  • NodePort Service: Expose a service on each node’s IP at a static port.
  • LoadBalancer Service: Expose a service externally using the cloud provider’s load balancer.
  • ExternalName Service: Map a service to an external DNS name.
  • Kubernetes Ingress: Expose HTTP and HTTPS routes from outside the cluster to services within.
  • Ingress Controller: Manage and configure traffic routing within the Kubernetes cluster.
  • Nginx Ingress Controller: Specific implementation of an Ingress controller using NGINX.
  • SSL – Self-Signed: Implement self-signed SSL certificates for securing communication.
  • SSL – Let’s Encrypt: Automatic provisioning and renewal of SSL certificates using Let’s Encrypt.

API Gateway and Service Mesh Configurations:

  • Secrets: Securely manage sensitive information such as passwords, OAuth tokens, and SSH keys.
  • ConfigMaps: Store configuration data separately from Pods.
  • Command and Arguments: Specify commands and arguments for executing containers.
  • Objects Metadata: Information about Kubernetes objects, including labels, annotations, and more.
  • Labels & Selectors: Attach identifying attributes to Kubernetes objects and select objects based on labels.
  • Node Labels and Selector: Associate labels with nodes and select nodes based on labels.

Volumes:

  • Volumes Overview: Manage data persistence in Kubernetes.
  • Persistent Volumes: Abstract storage from the underlying storage implementation.
  • Persistent Volumes Claims: Request storage resources from a Persistent Volume.

            C Kubernetes Security and Management 

AutoScaling: Automatically adjust the number of running instances or resources based on demand or predefined metrics, ensuring optimal performance and cost efficiency.

Resource Quotas: Set limits on the amount of CPU, memory, storage, and other resources that namespaces or users can consume within a Kubernetes cluster, preventing resource contention and ensuring fair resource allocation.

RBAC Authorization: Role-Based Access Control (RBAC) defines permissions for users or groups within a Kubernetes cluster, allowing administrators to control access to resources based on roles and privileges.

Network Policy: Define rules for network communication between Pods and external resources within a Kubernetes cluster, enhancing security and controlling traffic flow.

Cluster Upgrade: Upgrade a Kubernetes cluster to a newer version, ensuring access to new features, bug fixes, and security patches while minimizing downtime and disruptions.

Kubectl Commands: Command-line interface for interacting with Kubernetes clusters, allowing users to manage resources, deploy applications, and troubleshoot issues.

Troubleshooting: Identify and resolve issues within a Kubernetes environment, such as misconfigured resources, network problems, or application errors, to maintain system reliability and performance.

               D. Kubernetes Monitoring and Logging 

Monitoring Overview: Gain insight into the health and performance of Kubernetes clusters and applications through real-time metrics, alerts, and dashboards.

Kubernetes Dashboard: Web-based user interface for visually monitoring and managing Kubernetes clusters, providing insights into resource usage, deployment status, and more.

Prometheus Operator: Automate the deployment and management of the Prometheus monitoring tool in Kubernetes clusters, facilitating metrics collection, storage, and querying.

Logging Overview: Capture and store log data generated by Kubernetes applications and infrastructure components, enabling analysis, troubleshooting, and compliance.

Elastic Stack: Comprehensive logging and monitoring solution that includes Elasticsearch for log storage and search, Logstash for log processing, and Kibana for visualization and analytics.

New Relic Integration: Integrate the New Relic monitoring and analytics platform with Kubernetes to gain visibility into application performance, infrastructure health, and user experience.

The remaining content is currently being processed and will be incorporated into our existing document.

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