Google Cloud Platform Fundamentals: Core Infrastructure

Asim Zahid
4 min readJan 11, 2020
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It is an honor I have given a chance by DSC SEA Google to learn Google cloud fundamentals. I am thankful to my manager Shad Roi for giving me this awesomeness opportunity.

GCP Core Infrastructure Certificate

In this article, I will describe briefly what I learned and why should you take this course.

GCP Fundamentals

This course is the best for someone who want to get a holistic view of Google cloud platform. What GCP do?, what services it offer?, and how they interact and function?

Google Cloud Platform offers four main kinds of services: Compute, Storage, Big Data, and Machine Learning. This course focuses mostly on the first two, together with Google Virtual Private Cloud (VPC) networking.

Introducing Google Cloud Platform

First module orients learners to the basics of the Google Cloud Platform. It traces the evolution of cloud computing and explains what is unique about Google’s approach to it. The module introduces the key structural concepts of regions and zones.

Getting Started with Google Cloud Platform

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GCP customers use projects to organize the resources they use. They use Google Cloud Identity and Access Management, also called “IAM,” to control who can do what with those resources. They use any of several technologies to connect with GCP. The second module covers each of these topics, and it introduces a service called Cloud Launcher that is an easy way to get started with GCP.

Virtual Machines in the Cloud

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Compute Engine lets you run virtual machines on Google’s global infrastructure. Third module covers how Compute Engine works, with a focus on Google virtual networking.

Storage in the Cloud

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Every application needs to store data. Different applications and workloads require different storage and database solutions. This module describes and differentiates among GCP’s core storage options: Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Datastore, and Google Bigtable.

Containers in the Cloud

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Containers are simple and interoperable, and they enable seamless, fine-grained scaling. Kubernetes is an orchestration layer for containers. Kubernetes Engine is Kubernetes as a service, a scalable managed offering that runs on Google’s infrastructure. You direct the creation of a cluster, and Kubernetes Engine schedules your containers into the cluster and manages them automatically, based on requirements you define. This module explains how Kubernetes Engine works and how it helps deploy applications in containers.

Applications in the Cloud

App Engine is a Platform-as-a-Service (“PaaS”) offering. The App Engine platform manages the hardware and networking infrastructure required to run your code. App Engine provides built-in services that many web applications need. This module describes how App Engine works.

Developing, Deploying and Monitoring in the Cloud

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Popular tools for development, deployment, and monitoring just work in GCP. Customers also have options for tools in each of these three areas that are tightly integrated with GCP. This module covers those tools.

Big Data and Machine Learning in the Cloud

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GCP’s big-data and machine learning offerings are intended to help customers get the most out of data. These tools are intended to be simple and practical to embed in your applications. This module describes the available big-data and machine learning services and explains the usefulness of each.



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The author is a research scientist with a passion to build meaningful impact-oriented products. He is a dual Kaggle expert. He is a former Google Developer Student Club Lead(GDSC) and AWS educate cloud ambassador. He loves to connect with people. If you like his work, Say Hi to him.



Asim Zahid

I can brew up algorithms with a pinch of math, an ounce of Python and piles of data to power your business applications.