Requirements:

1. Basic Knowledge of Containers: Understanding what containers are and their basic functionalities (e.g., Docker).
2. Linux Fundamentals: Familiarity with basic Linux commands and operations.
3. Networking: Understanding of networking concepts (e.g., IP addresses, ports, DNS).
4. Virtualization: Basic knowledge of virtual machines and virtualization concepts.

Prerequisites:

1. Programming Skills: While not always mandatory, familiarity with programming (especially in languages like Python, Go, or Java) can be beneficial.
2. Operating Systems: Comfortable using and navigating through Linux-based operating systems.
3. Command Line Interface (CLI): Proficiency in using the command line interface to execute commands and manage files.
4. Cloud Concepts: Basic understanding of cloud computing concepts (e.g., virtual machines, cloud providers).

Additional Considerations:

• Experience with DevOps Tools: Familiarity with tools and practices related to DevOps (e.g., CI/CD pipelines, version control systems like Git).
• Understanding of Microservices Architecture: Knowledge about microservices architecture can provide context for how Kubernetes fits into modern application deployment and management strategies.

Courses on Kubernetes often vary in depth and complexity, so while these are general prerequisites, specific courses may have additional or slightly different requirements depending on their target audience and content focus.

The job prospects for Kubernetes professionals are currently very promising and are expected to continue growing in the foreseeable future. Kubernetes has become the de facto standard for container orchestration in modern cloud-native application development and deployment. Here are some key factors contributing to the strong job prospects:

1.Increased Adoption: Many organizations are adopting Kubernetes to manage their containerized applications due to its scalability, portability, and automation capabilities. This widespread adoption creates a high demand for professionals who can effectively implement and manage Kubernetes clusters.

2.Cloud-Native Development: As companies transition towards cloud-native architectures, Kubernetes skills are becoming essential. Understanding Kubernetes allows organizations to leverage cloud resources efficiently and manage applications at scale.

3.DevOps Integration: Kubernetes is closely integrated with DevOps practices, such as continuous integration/continuous deployment (CI/CD) pipelines and infrastructure as code (IaC). Professionals with Kubernetes knowledge are often sought after to streamline and automate deployment workflows.

4.Job Roles: There are various job roles and titles related to Kubernetes, such as Kubernetes Administrator, Kubernetes Engineer, Site Reliability Engineer (SRE) specializing in Kubernetes, DevOps Engineer with Kubernetes expertise, and Kubernetes Developer. These roles often command competitive salaries due to the specialized knowledge required.

5.Certifications: Kubernetes certifications, such as Certified Kubernetes Administrator (CKA) and Certified Kubernetes Application Developer (CKAD), are recognized in the industry and can enhance job prospects by demonstrating proficiency and expertise.

6.Community and Ecosystem: Kubernetes has a vibrant community and a rapidly evolving ecosystem of tools and platforms. Professionals who stay updated with the latest developments and contribute to the community often have an edge in the job market.

Overall, the demand for Kubernetes skills spans across various industries, including technology, finance, healthcare, e-commerce, and more. As cloud-native and containerization trends continue to grow, proficiency in Kubernetes is expected to remain highly valuable in the job market. Kubernetes offers several advantages that make it a popular choice for container orchestration in modern cloud-native application development. Here are some key advantages of Kubernetes and its applications:

1. Container Orchestration: Kubernetes automates the deployment, scaling, and management of containerized applications. It abstracts away the complexities of infrastructure management, allowing developers to focus on application development rather than deployment logistics.

2. Scalability: Kubernetes provides automated scaling of applications based on resource usage or custom metrics. It ensures that applications can handle varying loads without manual intervention, thus optimizing resource utilization.

3. High Availability: Kubernetes supports automatic restarts, self-healing, and rolling updates, ensuring that applications remain available and responsive even in the event of failures or updates.

4. Portability: Kubernetes offers a consistent environment across different infrastructure providers (public clouds, private data centers, hybrid clouds). This portability allows applications to be easily moved between environments without modification.

5. Resource Efficiency: Kubernetes optimizes resource usage by scheduling containers onto nodes with available resources. It supports resource limits and requests, ensuring efficient utilization of CPU and memory.

6. Service Discovery and Load Balancing: Kubernetes has built-in support for service discovery and load balancing. It assigns a stable IP address and DNS name to services, enabling other applications to discover and communicate with them reliably.

7. Automated Rollouts and Rollbacks: Kubernetes facilitates automated deployment strategies such as rolling updates and rollbacks, ensuring smooth application updates with minimal downtime and the ability to revert changes if necessary.

8. Declarative Configuration: Kubernetes uses declarative YAML manifests to define the desired state of applications and infrastructure. This approach allows for version control, easier collaboration, and reproducibility of deployments.

1. Microservices Orchestration: Kubernetes is well-suited for managing microservices-based architectures. It allows teams to deploy, scale, and update individual microservices independently, facilitating agility and flexibility in development.

2. Continuous Integration and Continuous Deployment (CI/CD): Kubernetes integrates seamlessly with CI/CD pipelines, enabling automated testing, building, and deployment of applications. It supports blue-green deployments and canary releases for gradual rollout of changes.

3. Hybrid and Multi-cloud Deployments: Kubernetes provides a consistent platform across different cloud providers and on-premises environments. Organizations can leverage Kubernetes to build hybrid and multi-cloud strategies, ensuring flexibility and avoiding vendor lock-in.

4. Edge Computing: Kubernetes has applications in edge computing scenarios where computing resources are distributed across geographically dispersed locations. It allows for efficient management of edge nodes and applications at scale.

5. Batch Processing and Big Data Workloads: Kubernetes can orchestrate batch processing jobs and big data workloads using frameworks like Apache Spark, Apache Flink, and TensorFlow. It provides resource isolation and scheduling capabilities for such workloads.

6. Internet of Things (IoT): Kubernetes can manage IoT deployments by orchestrating containerized edge devices and managing communication between devices and cloud services.

1. Master Components:

• API Server: Acts as the central management point that exposes the Kubernetes API, which allows users and other components to interact with Kubernetes.
• Scheduler: Responsible for assigning workloads (pods) to nodes based on resource availability and constraints.
• Controller Manager: Manages various controllers that regulate the state of the cluster, such as node controller, replication controller, and endpoint controller.
• etcd: Distributed key-value store used by Kubernetes to store all cluster data, including configuration, state, and metadata.

2. Node Components:

• Kubelet: Agent that runs on each node in the cluster and ensures that containers are running in a pod.
• Kube Proxy: Handles network proxying and load balancing across application services running in a Kubernetes cluster.
• Container Runtime: Software responsible for running containers, such as Docker, containerd, or CRI-O.

3. Networking:

• Pod Network: Network of communication between containers within the same pod.
• Cluster Network: Network that allows communication between different pods and services across the Kubernetes cluster.
• DNS: Provides DNS-based service discovery for Kubernetes services.

4. Add-Ons:

• Dashboard: Web-based UI for managing and monitoring Kubernetes clusters.
• Ingress Controller: Manages external access to services within a Kubernetes cluster.
• Metrics Server: Collects resource usage data and provides metrics to support cluster autoscaling.

1. Introduction to Containers and Kubernetes:

• Understanding containerization concepts (e.g., Docker).
• Overview of Kubernetes architecture and components.

2. Deployments and Pods:

• Creating and managing pods, which are the smallest deployable units in Kubernetes.
• Using deployments for managing application lifecycle and rolling updates.

3. Services and Networking:

• Service types (ClusterIP, NodePort, LoadBalancer) and their use cases.
• Networking concepts within Kubernetes, including DNS resolution and service discovery.

4. Storage Management:

• PersistentVolumes (PVs) and PersistentVolumeClaims (PVCs) for persistent storage.
• Storage Classes and dynamic provisioning of storage resources.

5. Configuration and Secrets:

• ConfigMaps and Secrets for managing configuration data and sensitive information.
• Using environment variables and volumes to inject configuration into containers.

6. Scaling and Load Balancing:

• Horizontal Pod Autoscaler (HPA) for automatic scaling based on CPU or custom metrics.
• Load balancing applications using Kubernetes services and ingress controllers.

7. Monitoring and Logging:

• Monitoring cluster and application health using metrics and dashboards.
• Collecting and analyzing logs from Kubernetes pods and components.

8. Security and Access Control:

• Role-Based Access Control (RBAC) for controlling access to Kubernetes resources.
• Network policies for restricting traffic between pods and services.

9. Advanced Topics:

• StatefulSets for managing stateful applications (e.g., databases) in Kubernetes.
• Deploying applications with Helm charts for package management and templating.

10. CI/CD Integration

• Integrating Kubernetes with CI/CD pipelines for automated testing, building, and deployment.
• Using tools like Jenkins, GitLab CI, or Tekton for CI/CD workflows.

Online Weekend Sessions: 08-10 | Duration: 25 to 27 Hours
1: Introduction to Kubernetes
•    Overview of containerization and its benefits.
•    Evolution of Kubernetes.
•    Key features and advantages of Kubernetes.
•    Comparison with other container orchestration tools (e.g., Docker Swarm).
2: Kubernetes Architecture
•    Components of Kubernetes architecture:
1.    Master node: API server, scheduler, controller-manager, etc
2.    Worker nodes: kubelet, kube-proxy, container runtime.
•    Understanding the role of each component in the cluster.
3: Setting Up Kubernetes Cluster
•    Requirements and prerequisites for setting up a Kubernetes cluster.
•    Installation methods:
1.    Using kubeadm.
2.    Minikube for local development.
3.    Managed Kubernetes services (e.g., AWS EKS, GCP GKE, Azure AKS).
•    Configuring networking and storage for Kubernetes.
4: Pods and Containers
•    Understanding Pods:
1.    What is a Pod?
2.    Pod lifecycle.
3.    Multi-container Pods.
•    Managing containers within Pods:
1.    Creating Pods.
2.    Interacting with Pods.
5: Deployments and ReplicaSets
•    Deploying applications with Deployments.
•    Scaling applications using ReplicaSets.
•    Updating applications with rolling updates and rollbacks.
6: Services and Networking
•    Kubernetes networking model:
1.    Cluster networking.
2.    Service discovery and load balancing.
•    Service types:
1.    ClusterIP, NodePort, LoadBalancer.
•    Network policies for controlling traffic between Pods.
7: Persistent Storage
•    Storage options in Kubernetes:
1.    Volumes.
2.    Persistent Volumes (PVs) and Persistent Volume Claims (PVCs).
•    StatefulSets for managing stateful applications.
8: ConfigMaps and Secrets
•    Managing configuration data with ConfigMaps.
•    Storing sensitive information securely with Secrets.
9: Security in Kubernetes
•    Role-Based Access Control (RBAC) in Kubernetes.
•    Securing Kubernetes components and APIs.
•    Implementing network policies for pod-to-pod communication.
10: Monitoring and Logging
•    Monitoring cluster health:
1.    Metrics collection.
2.    Using Prometheus for monitoring.
•    Logging best practices:
1.    Centralized logging solutions.
11: Advanced Networking
•    Ingress controllers and Ingress resources.
•    Service meshes for advanced networking and traffic management (e.g., Istio, Linkerd).
12: Helm and Package Management
•    Introduction to Helm for managing Kubernetes applications.
•    Creating and managing Helm charts.
•    Using Helm to deploy applications and manage releases.
13: CI/CD with Kubernetes
•    Integrating Kubernetes with Continuous Integration/Continuous Deployment (CI/CD) pipelines.
•    Automating application deployment and updates.
•    Best practices for CI/CD in Kubernetes environments.
14: Kubernetes Ecosystem and Tools
•    Overview of additional Kubernetes tools and extensions:
1.    Operators and Custom Resource Definitions (CRDs).
2.    Kubernetes Dashboard.
3.    Logging and monitoring tools (e.g., Fluentd, Grafana).
15: Hybrid and Multi-Cloud Kubernetes
•    Managing Kubernetes clusters across multiple cloud providers.
•    Strategies for hybrid cloud deployments.
16: Kubernetes Best Practices and Troubleshooting
•    Best practices for deploying applications on Kubernetes.
•    Common troubleshooting scenarios and solutions.
•    Performance tuning and optimization techniques.
17: Practical Labs and Hands-On Exercises
•    Hands-on labs covering deployment, scaling, and management of applications on Kubernetes.
•    Real-world scenarios to reinforce concepts learned throughout the course.