Businesses across the world have started using the public cloud to increase scalability, collaboration, and flexibility, among other reasons. Although most of the cloud platforms have different names, they utilize similar open-source software and products. 

Let’s dive deeper into understanding one such platform- Google Cloud Platform (GCP) and if it is suitable for your business. 

What is GCP?

GCP Full Form

GCP full form is Google Cloud Platform. GCP means that it is a public cloud vendor offering a prominent suite of cloud services. It offers a range of computing resources and tools hosted in Google’s global data centers which customers can access for free or on a pay-per-use basis. 

With Google Cloud Platform, you can maintain cost management to deliver web and video over the web to AI and machine tools. 

Google Cloud Platform is similar to its competitors like Amazon Web Services (AWS) and Microsoft Azure. It also provides GCP server space on virtual machines, networking capabilities, storage, VPN connection, machine learning solutions (such as Tensor Processing Units or TPUs), as well as SaaS (Software as a Service) applications. 

Although the underlying technology across different vendors remains the same, there are certain distinctions when it comes to the features, pricing features, and customer support. 

History of GCP

The inception of GCP can be traced back to 2008 with the launch of the App Engine which was designed to facilitate web app development and scalability on Google infrastructure. The goal of this App Engine as per Google was to make the process of using a new web app easier and scale it when it’s receiving significant traffic and users.

After a preview phase allowing access to 10,000 developers and implementing feedback for improvement, the App Engine transitioned to an officially supported Google product in 2011. Over the past decade, Google expanded its suite and integrated additional services and products, resulting in the development of the current Google Cloud Platform. 

Some of the noteworthy Google Cloud customers include eBay, UPS, and Twitter. This showcases the widespread adoption and versatility of this platform across various industries. 

What is the Difference Between Google Cloud and Google Cloud Platform?

Google Cloud includes a combination of services that are available over the Internet. These services can help organizations go digital. On the other hand, Google Cloud Platform is a public cloud infrastructure for hosting web-based applications. It is essentially a part of Google Cloud. 

Some of the other services within Google Cloud include:

  • Google Workspace, formerly known as G Suite and Google Apps, offers identity management for organizations, Gmail, and other collaboration tools.
  • Enterprise editions of Android and Chrome serve as operating systems for phones and laptops, connecting users to web-based applications. 
  • Application programming interfaces (APIs) for machine learning and enterprise mapping services, facilitate software-to-software communication. 
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Now that you understand that Google’s GCP cloud infrastructure forms the backbone of applications like Google Workspace, let’s focus our attention back to understanding the Google cloud platform services which include: 

  • Computing and hosting
  • Networking
  • Storage and database
  • Machine learning
  • Big Data

GCP- Infrastructure, Regions, Zones, and Pricing

Google’s global infrastructure has a total of 24 locations worldwide where GCP resources are offered. Regions serve as the starting points where each GCP region has zones that are isolated from a single point of failure. Certain resources like the HTTP (Hypertext Transfer Protocol) load balancer are global and accessible from any Google Edge location or region. 

When it comes to resources like storage, it can be regional. The storage is distributed across multiple zones within a region for redundancy. Lastly, zonal resources, such as compute instances that provide computing power in the cloud for running applications and performing tasks without physical hardware, are limited to specific zones within a region. 

Therefore, selecting the right locations on GCP is crucial. You need to consider your organization’s requirements for performance, reliability, scalability, as well as security when deploying applications. 

Another factor you need to consider is the GCP cost. Google’s prices for virtual machines (VMs) differ with CPU type and memory. The incorrect size or lack of price monitoring can lead to high monthly subscription fees. That is why it is essential to designate someone to master the Google cost calculator to manage cost effectively. 

Once the free trial on a GCP account ends after you have consumed $300 in credits, you need to move to the paid subscription model. 

Products and Services Offered by Google Cloud Platform

There are over a hundred GCP products and services. It includes AI and machine learning, data analytics, networking storage, and security. Let’s look at the products of the Google platform:

  • App Engine

This framework and platform was created for developing and hosting web apps that automatically scale in response to increased demands. This eliminates the need for containers or virtual machines as you can create an application and run on an abstraction of it. 

  • Compute Engine

Google Compute Engine delivers virtual machines (VMs). In simple terms, it provides VMs with a choice of operating systems and hardware sizes, offering flexibility to scale computing resources based on demand. 

Similar to Amazon EC2, Compute Engine makes use of hypervisor technology to create multiple virtual computers from a single hardware resource. Mostly an abstraction of a computer, it imitates a computer but does not have direct access to the screen or disk drive among other components. The biggest advantage is that it optimizes the cost by starting and shutting the VM as required.

  • BigQuery
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BigQuery is a serverless enterprise-level data warehouse that rapidly sets up data warehouses. It enables quick data analysis, thereby processing large amounts of data, even petabytes of data within minutes. BigQuery employs a standard SQL dialect (ANSI:2011) and federated queries to reduce code rewrites and process external data sources.

  • Memorystore for Redis

Cloud Memorystore for Redis is an open-source, in-memory database like Apache Spark or SAP Hana. This database operates faster without disk drives and stores data in memory instead of on a disk. The reason is that disk drives have moving parts, for instance, disk controllers are not as fast as in solid-state storage, like memory. It is suitable for tasks where performance outweighs costs. 

  • Google Tensor Processing Unit (TPU)

Google Cloud TPU is a proprietary processor designed for large-scale mathematical computations. It uses the same technology as the graphics card on your desktop or laptop.TPU is particularly significant in machine learning tasks like neural network development for voice and image recognition, cybersecurity monitoring, and solving extensive computing problems. 

TPUs are an advanced version of GPUs Graphical Processing Units). They enhance the computational speed by significant margins compared to regular CPUs.

  • Persistent Disk

Google Persistent Disk is a block storage for virtual machines. It allows database blocks to be easily resized, backed up, and supported across multiple readers. It is automatically encrypted, therefore, you do not have to worry about security for the cloud data. Moreover, a persistent disk is necessary as VM storage is lost when the machine shuts down. 

  • Cloud Run

With Cloud Run, you can create containers without virtual machines. Therefore, you do not need to spin up a virtual machine followed by spinning up the containers inside. This saves costs and resources as it eliminates the need for unnecessary layers when deploying containers. 

It also offers a minimal operating system to run containers efficiently and does not require file transfer software, encryption software, a system log, and other components that a complete operating system has.

  • Technical Support

The technical support for GCP is available in various tiers, offering free self-service support via platforms like StackOverflow, Stack channels, and Google groups. GCP also provides paid support which includes phone support and optional dedicated account management.

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What are Google Cloud Platform’s Strengths and Limitations?

Google Cloud Platform in cloud computing has numerous strengths and weaknesses:

Strengths of GCP:

  • Modular and Interconnected Services

The architecture of GCP is like assembling LEGO bricks. It is designed with services that seamlessly integrate as well as complement each other, streamlining development. 

  • Top-Tier Documentation

GCPs documentation is second to none. It is highly acclaimed for its clarity and usefulness. It provides a complete overview of GCP along with hands-on implementation guidance, making it a valuable resource for users. 

  • Global Backbone Network

With GCP, you leverage advanced software-defined networking which ensures swift, consistent, and scalable performance. The use of virtual private cloud (VPC) which is the premium version for global traffic routing comes at a slightly higher cost but is seen as a worthwhile option for reliable operations. 

Limitations of GCP:

  • Limited Service Offerings

Compared to its competitors like AWS and Azure, GCP offers fewer services. This potentially limits the choices for users seeking specific functionalities or tools. Moreover, Google’s primary focus lies in investing in GCP rather than aiming for market dominance. This limits its prioritization and growth. 

  • Developer-Centric Approach

GCP’s model tends to cater more to software developers, which might create a learning curve or limitations for users from different backgrounds or expertise. 

Real-World Application of GCP

Now, let’s look at some ideal GCP scenarios where it can be used as an advantage:

  • Efficient Organizational Management

GCP offers a robust organizational hierarchy which is ideal for large organizations requiring streamlined permission settings across various GCP projects. This setup allows different departments to work together efficiently and swiftly while adhering to organizational guidelines.

  • Resource Management

GCP assigns all resources to specific projects. This simplifies the process of resource removal when projects are deleted to prevent lingering costs. Plus, the platform enables the allocation of projects to different billing accounts over time, helping in better financial tracking and management.

  • Advanced Data Utilization

With GCP, organizations can utilize the advanced capabilities of machine learning, Big Data, and analytics. Businesses can efficiently ingest and analyze data to extract key performance indicators (KPIs) for products and services or leverage customer data to offer tailored purchase recommendations based on their past buying behavior. 


Thus, having a proper understanding of Google Cloud Platform can help businesses by offering scalability and flexible solutions. It helps in proficient data management, advanced analytics, and streamlined operations, thereby, cost-effectively fostering innovation and agility. You can learn GCP and get relevant certifications to utilize the GCP platform to the fullest.