Google Cloud Platform (GCP): Complete Study Guide for Cloud Exam

Google Cloud Platform (GCP) Basics
Google Cloud Platform (GCP) is a suite of cloud computing services provided by
Google, offering a wide range of tools and services to help businesses and
developers build, deploy, and scale applications in a secure and efficient manner.
With services ranging from compute and storage to networking and machine
learning, GCP enables users to create highly flexible, scalable, and cost-effective
solutions for various business needs.

In this section, we will explore the core features of GCP, highlighting key services,
use cases, and advantages of adopting Google Cloud technologies.



1. Introduction to Google Cloud Platform (GCP)
Google Cloud Platform (GCP) provides cloud-based services for computing,
storage, data analytics, machine learning, networking, and more. GCP competes
with other major cloud providers like Amazon Web Services (AWS) and Microsoft
Azure, and it stands out with its strong focus on artificial intelligence (AI), machine
learning (ML), and big data processing.

 Key Benefits of GCP:
o Scalability and Flexibility: GCP allows users to scale their
infrastructure dynamically as needed, ensuring that resources are
allocated efficiently.
o Advanced Machine Learning and AI Tools: GCP offers specialized
tools for developing, training, and deploying machine learning
models, making it ideal for data scientists and AI practitioners.
o Global Infrastructure: Google Cloud runs on the same infrastructure
that powers Google Search, Gmail, and YouTube, ensuring high
availability, low latency, and superior performance.
o Security and Compliance: Google Cloud provides a strong security
framework, including end-to-end encryption, access control, and a
range of compliance certifications, ensuring that applications and
data are secure.

, 2. Core Services of GCP
Google Cloud Platform provides a variety of services, each designed to meet the
needs of different workloads, whether they are focused on computing, storage,
networking, or machine learning.

a) Compute Services: Google Compute Engine and Google Kubernetes Engine

 Google Compute Engine (GCE): Google Compute Engine provides
Infrastructure-as-a-Service (IaaS) that enables users to run virtual machines
(VMs) on Google’s infrastructure. GCE allows businesses to run a wide
range of applications on Google’s secure and high-performance
infrastructure.
o Key Features:
 Customizable VMs with flexible configurations.
 Integrated with other GCP services like Cloud Storage and Load
Balancing.
 Automatic scaling and load balancing.
o Use Cases:
 Hosting websites and applications.
 Running large-scale compute workloads (e.g., simulations,
rendering).
 Development and testing environments.
 Google Kubernetes Engine (GKE): Google Kubernetes Engine is a fully
managed service for running containerized applications using Kubernetes,
an open-source container orchestration platform. GKE allows developers to
deploy, manage, and scale applications seamlessly.
o Key Features:
 Automated Kubernetes cluster management.
 Integrated with Google’s monitoring and security services.
 Horizontal scaling and container orchestration.
o Use Cases:
 Managing microservices-based applications.
 Building scalable and resilient cloud-native applications.
 Automating application deployments and scaling.