As technology continues to advance and become a significant part of our everyday lives, cloud computing has, as well. There are several different cloud providers to choose from, and it can be a bit overwhelming at first. Google Cloud Platform (GCP) is a widely used cloud computing platform for several reasons, including their convenient, easy-to-use tools and services. Our comprehensive guide will explore Google Cloud Platform in more detail, which also serves as an introduction to cloud computing technology in general.
The following are the topics covered in this article include:
- What is cloud computing?
- Why use Google Cloud Platform?
- What is Google Cloud Platform?
- Google Cloud Platform components
- Ferrero use case
- Hands-on GCP exercise
What Is Cloud Computing?
Cloud computing is the use of hardware and software components in an off-premises location to deliver a service to a network. Users can access files and applications from any device that can access the internet.
Some features and capabilities include:
- Cloud providers can pull the computing resources to provide services to multiple customers with the help of a multi-tenant model
- Cloud computing proves an on-demand self-service, which helps administrators monitor performance
- Servers are maintained easily and there is nearly zero downtime
- Users can access cloud data and upload it on the cloud from any device with a solid internet connection
- Cloud environments can be modified according to the user's requirements and is easily accessible
- Clouds are highly secure, making data breaches more unlikely
- Migrating to the cloud eliminates the need to buy on-premises infrastructure
- It offers pay-as-you-go pricing, meaning you only pay for the resources you use
Why Use Google Cloud Platform?
GCP is popular for many reasons, including:
1. Competitive Pricing
- Pricing is one of the significant factors that make Google Cloud stand out among the other cloud providers
- Google Cloud offers a monthly pricing plan
- Google Cloud pricing provides committed use discounts
- In this plan, if you commit to purchasing a specific amount of vCPUs and memory for one or three years, you can get a discount of up to 57 percent
- Google Cloud provides its Google Cloud and Google App customers network speeds of up to 10Tbs
- The network has connections throughout the world in United States, Europe, main cities in Japan, major hubs in Asia and much more.
- The low-latency network processes data in less time, leading to high customer satisfaction
3. Big Data
- Google has many innovative tools for cloud warehousing like BigQuery and real-time data processing tools like Google Cloud Dataflow
- BigQuery is a data warehouse that enables massive processing of data at high speeds
- Google has also launched new machine learning and Artificial Intelligence tools
What Is Google Cloud Platform?
Google Cloud Platform is a set of cloud computing services that Google offers, which runs on the same infrastructure that Google uses for its end-user products, such as YouTube, Gmail, and more. Google Cloud Platform offers a variety of services, including:
- Machine learning and AI
- Big data processing
Google Cloud Platform Components
Several components and services are an important feature of Google Cloud Platform; let’s dive into each one individually and learn more about what they provide.
The compute service enables compute and hosting the cloud. The various services under this are as follows:
- App Engine
- Compute Engine
- Kubernetes Engine
- Cloud Functions
- Cloud Run
2. Storage and Database
The storage and database service enables the application to store media files, backups, or other file-like objects. The services include:
- Cloud Storage
- Cloud SQL
- Cloud Bigtable
- Cloud Spanner
- Cloud Datastore
The networking service enables us to load-balance traffic across resources, create DNS records, and much more. Some of the services include:
- Cloud Load Balancing
- Cloud Armor
- Cloud CDN
- Cloud Interconnect
- Cloud DNS
- Network Service Tiers
4. Big Data
The big data service enables us to process and query big data in the cloud. A few of the included services are the following::
- Cloud Dataproc
- Cloud Datalab
- Cloud Data Studio
5. Developer Tools
The developer tools service includes tools that enable software and application development.
- Artifact Registry (beta)
- Cloud SDK
- Cloud Code
- Cloud Scheduler
- Cloud Tasks
6. Identity and Security
This service deals with security and authentication:
- Cloud Identity
- Cloud IAM
- Cloud Data Loss Prevention API
- Security Key Enforcement
7. Internet of Things(IoT)
You can leverage GCP to create IoT environments with the following tools:
- Cloud IoT Core
- Edge TPU
- Cloud IoT
8. Cloud AI
Cloud AI comprises services related to machine learning, which also encompasses:
- Cloud AutoML
- Cloud Natural Language
- Cloud Speech-to-Text
- Cloud Text-to-Speech
- Cloud Translation API
- Cloud Vision API
- Cloud Video Intelligence
9. Management Tools
This domain includes services related to management and monitoring. The services under this are as follows:
- Cloud Deployment Manager
- Cloud Console
- Cloud Shell
- Cloud APIs
10. API Platform
The few services under this are as follows:
- Maps Platform
- Developer Portal
- API Analytics
- Apigee Sense
- Cloud Endpoints
Ferrero Use Case
Ferrero is one of the most famous chocolate brands and ranks third among worldwide chocolate and confectionery producers. It was founded in 1946 in Italy.
- Ferrero is sold in nearly every supermarket and is known for its high quality. As the success of the brand increased, several challenges arose
- The company needed data storage, processing, and an analysis system for their vast customer database
- There was a significant gap between the company and its customers because the company relied on data provided by third-party sales partners and distributors
- Ferrero wanted to create a digital ecosystem where there was a direct point of contact with its customers and also a foundation for an innovative, data-driven marketing strategy
- BigQuery was the answer to Ferrero's challenges since it was capable of super-fast and efficient data analysis
- Using Google Cloud Platform’s BigQuery, business analysts at Ferrero were able to store and analyze massive data sets in a very reliable, fast, and affordable manner
- Reports on consumer behavior and sales patterns were easy to build and automate
- The analysis also enabled Ferrero to adapt advertising across various marketing channels to serve the customers’ needs in a better way
- Ferrero could divide its database into real-time, actionable consumer clusters to generate more accurate user profiles
- Ferrero also personalized its marketing strategies to match the users’ preferences and needs
- Google Cloud Platform completely tailored the website, mobile content, and advertising
- Google Cloud Platform created very cost-effective media buying strategies
Let's create something on GCP!
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Creating a Linux virtual machine instance in Compute Engine using the Google Cloud Console:
- In the cloud console and on the project selector page, select or create a cloud project.
- Make sure that billing is enabled for your Google Cloud project
- Enable the Compute Engine API
Create a virtual machine instance
- In the cloud console, go to the VM Instances page
- Click Create instance.
- Fill in the specifications as follows:
- In the “Boot disk” section, click “Change” to begin configuring your boot disk.
- On the “Public images” tab, choose “Ubuntu.” Choose “Ubuntu 18.04” and click “Select.”
- In the “Firewall” section, select “Allow HTTP traffic.”
- Download the required version of PuTTY that you’ll need
- Go to puttygen and click on “generate” to generate a public/private key pair
- Enter a username and password and save the private key
- Go back to Google Cloud console and click “Create” to create the instance.
The instance will start shortly after. Once it is ready, it is listed on the VM instances page with a green status icon.
Connect to Your Instance
- In Cloud Console, go to the VM instances page
- In the list of virtual machine instances, click “SSH” in the row of the instance that you want to connect to—the SSH button is located next to the instance name
- Go to the VM instances page in the Google Cloud Console
- Click the name of the instance you created
- At the top of the instance's details page, click “Delete”
To perform basic tasks in cloud storage using the Google Cloud Console:
- In the cloud console, which is located on the project selector page, select or create a cloud project.
- Go to the project selector page
- Confirm that billing is enabled for your Google Cloud project
Create a bucket
- Open the cloud storage browser in Google Cloud Console.
- Click “Create bucket” to open the bucket creation form.
- Enter your bucket information and click “Continue” to complete each step
- Enter a unique name for your bucket. In this example, the bucket will be named “mydataimp.”
- Select “Region” for location type and us-east1 (South Carolina) for location.
- Select “Standard” for default storage class.
- Select “Uniform” for access control.
- Click Create.
Upload an Object to the Bucket
- In the cloud storage browser, click on the name of the bucket that you created.
- Click the “Upload files” button in the “Objects” tab.
- Download an image and keep it in a designated folder
- In the file dialog, navigate to the file that was downloaded and select it.
After the upload completes, you should see the file name and details, such as its size and type.
Download the Object
- Click the drop-down menu associated with the image. The drop-down menu appears as three vertical dots to the far right.
- Click “Download.”
The image is saved to your local system.
Share the Object
- Click the “Permissions” tab above the list of files.
- Click the “Add members” button.
- In the “New members” text field, enter “allUsers”
- In the “Select a role” drop-down, select Storage > Storage Object Viewer.
- Click “Save.”
When you click on the “Objects” tab and return to the list of objects, you should see that the image is publicly accessible and has a link icon. The link icon reveals a shareable URL that looks like:
To remove public access from the bucket and stop sharing the image publicly:
- Click the “Permissions” tab above the list of objects.
- Find the entry that has “allUsers” listed in the “Members” column.
- Click the trash can icon that is associated with the allUsers entry.
- Click “Remove.”
You should see that the image no longer has a link icon associated with it.
- Click “Create folder.”
- Enter “Immedata” for name and click “Create.”
You should see the folder in the bucket with an image of a folder icon to distinguish it from objects.
Create a subfolder and upload a file to it:
- Click immedata.
- Click “Create” folder.
- Enter folder2 for name and click “Create.”
- Click folder2.
- Click “Upload files.”
- In the file dialog, navigate to the screenshot that you downloaded and select it.
After the upload completes, you should see the file name and information about the file, such as its size and type.
Delete the Objects
- Click the buckets link to return to the buckets level.
- Select the bucket.
- Select the checkbox next to folder1.
- Click on the “Delete” button.
- Click “OK” to permanently delete the folder, including all objects and subfolders inside the folder.
- Clean up.
We hope that this blog was informative and helpful in explaining Google Cloud Platform. We discussed an array of topics, including the basics of cloud computing, the benefits of Google Cloud Platform, and we explored what Google Cloud Platform offers in more detail. We also went over the different services in GCP and explored a case study in detail, which demonstrates how a real customer uses GCP. Finally, we went over two thorough GCP demos. In the first demo, we created a Linux virtual machine instance on Compute Engine using the Google Cloud Console and in the second demo, we performed basic tasks in cloud storage using the Google Cloud Console.
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