GCP Associate Cloud Engineer Google Certification -150 Demos

Based on the detailed curriculum you've outlined, it seems you're aiming to cover a wide array of topics within Google Cloud Platform (GCP), including Kubernetes Engine (GKE) management and services, IAM, Virtual Private Cloud (VPC), Cloud Load Balancing, Cloud Run and Cloud Functions, as well as data solutions like Cloud SQL, Cloud Spanner, and Big Data tools like Cloud Dataproc. Additionally, you're planning to cover monitoring with Cloud Monitoring and logging with Cloud Logging.

Here's a brief summary of each topic based on the curriculum structure you've provided:

1. Kubernetes NodePort Service: A type of service that exposes a node port on the cluster's edge router for external access to a service on a specific node.

2. Kubernetes ClusterIP Service: A default virtual IP address (VIP) that is mapped to a selection of container ports and is only accessible within the cluster.

3. Kubernetes Headless Service: A service without a stable endpoint for clients to communicate with, often used in conjunction with jobs.

4. Kubernetes Ingress Service: An API object that manages external access to the services in a cluster, typically HTTP/HTTPS traffic.

5. GKE Kubernetes Jobs: A resource that runs to completion and is often used for short-lived tasks (e.g., cron jobs).

6. GKE Cluster Management: Includes managing node pools with Node Selectors, which allow you to specify labels that nodes must match in order to be selected for the job.

7. GKE Cluster Types: Different types of GKE clusters including regional and zonal clusters, each with its own characteristics.

8. Kubernetes CronJobs: Schedules Jobs to run at specific intervals (cron expressions).

9. IAM (Identity and Access Management): Managing permissions and access controls for users and services to resources in GCP.

10. Virtual Private Cloud (VPC): Manages the virtual networks, subnetworks, routes, firewalls, and VPN connections for your Google Compute Engine instances, Container-Optimized VMs, App Engine apps, and Kubernetes Engine clusters.

11. Cloud Load Balancing: Distributes incoming traffic across multiple resources (such as VM instances or container replicas) across multiple geographic and regions.

12. Cloud Run Services and Jobs: Serverless compute platform that automatically scales your stateless containers.

13. Cloud Functions - HTTP and Events: Write single-purpose functions that respond to events, such as HTTP requests or messages from IoT devices.

14. Google Cloud Data Solutions: A suite of services for storing, processing, analyzing, and visualizing data at scale.

15. Cloud Monitoring: Provides insights into the performance and health of your applications and infrastructure using metrics, events, and traces.

16. Cloud Logging: A tool that aggregates, analyzes, and acts on logs from your cloud and on-premises resources.

For each topic, you've outlined a series of practical demos to guide learners through the concepts, ensuring they not only understand the theory but also have hands-on experience with real-world applications. Additionally, you mention that each course comes with friendly support in the Q&A section and a 30-day money-back guarantee.

This curriculum is comprehensive and covers a wide range of skills needed to work with Google Cloud Platform. It's designed to provide learners with a solid foundation in GCP services and Kubernetes, as well as practical experience in deploying, managing, and monitoring applications on the platform.