Introduction to Google Compute Engine

Pre-requisites: GCP, Virtual machines 

Google Cloud Platform offered by Google is a suite of Cloud Computing Services that runs on the same infrastructure that Google uses internally for its end-user products such as Google Search, Gmail, File storage, and YouTube.  Along with the set of management tools, it also provides a series of modular cloud services including 

• Computing 
• Data Storage
• Data Analytics
• Machine Learning

What is Google Compute Engine?

Google Compute Engine is an IaaS component of Google Cloud Platform (GCP). It is built on the global infrastructure that runs Google’s  Search Engine, Gmail, YouTube, and other Big Services.  Google’s Compute Engine is a part of the computer platform Google service component of Google Cloud Platform which is built on the global infrastructure that runs Google’s Search Engine, YouTube, and Other Services.

GCE is part of Compute Platform in Google Cloud.  Google Compute Engine offers Virtual Machines running in Google data centers connected to worldwide fiber networks. The tooling and workflow offered by the compute engine enable serving from single instances to global ones. It enables users to launch Virtual Machines on-demand  VMs can be launched from the standard images or custom images created by users. The GCE users must authenticate based on 2.0 before launching the Virtual Machine. Auth 2.0 is here the Open Standard for access delegation commonly used as a way for internet users to brand websites or applications access to their information on other websites but without giving them the passwords.

The mechanism is used by companies such as Amazon, Meta, Microsoft, Twitter, and Google to permit users to share information about their accounts with third-party applications of websites. GCE can be accessed via the developer Consoles or Restful APIs or Command Line Interface.

What Reasons for Businesses Utilize Google Compute Engine?

1. Cost-effectiveness: In contrast to managing its own infrastructure, Google Compute Engine offers a pay-as-you-go model where the organization only needs to pay for the resources that are actually used.
2. Reliability: We can place a lot of trust in the Google computing engine infrastructures because they offer a 99% uptime SLA, making apps accessible to consumers around the clock.
3. Data Migration: Migrating the data from the physical servers to the cloud is very easy and efficient.

Applications of Google Compute Engine

Google Compute Engine will allow you to run your application and services on virtual machines. Below are some common applications of Google Compute Engine.

1. Web applications hosting: Google compute engine will provide the storage, and networking resources to host your web application.
2. Can run large-scale data: Google compute engine is suitable for data analysis, and scientific simulations which need to handle large-scale data. 
3. Gaming servers: Google’s compute engine has low latency so it is very suitable to host multiple gaming infrastructures. 
4. Support Docker and Kubernetes: Google compute engine will support containerization applications. Either you can run containers as a single or you can maintain the clusters which are provided by Kubernetes and docker-compose.

Features of Google Compute Engine

• Machine Type:- It describes Virtual hardware attached to an instance, it also includes RAM and CPU. It can further have two types:
• Local SSD: GCE always offers encrypted local solid-state drive block storage which is physically attached to the Virtual Machine running it. It improves performance and also reduces latency.
• Persistent Disk: Durable high-performance block storage for VM instances that can be created in Hard Disk and SSD formats, so users can take snapshots and create a new persistent disk from the snapshots.
• GPU Accelerators: GPUs are added to accelerate workloads like Machine Learning or virtual workstation applications etc.
• Image: An image contains the Operating system of the root file that uses leverage to run a virtual machine instance. So GCP provides two main types of images:

• Global Load Balancing: helps in distributing requests across pools of instances across multiple regions.
• Other features include Linux and Windows Support containers, Reservation, OS patch management live migration for Virtual machines, and many more.

Usage of Virtual Machines

Virtual machines (VMs) are frequently utilized in a variety of contexts and businesses. Here are a few frequent scenarios for using virtual machines:

1. Virtual machines are frequently employed in software development and testing. Without using physical hardware, developers can create several virtual machines (VMs) to imitate various settings and test their apps there.
2. Disaster Recovery A VM-based disaster recovery plan is an option. Businesses can build virtual machines (VMs) containing important data and applications and duplicate them to different locations. The replicated VMs can be turned on to maintain business operations in the event that the primary location suffers a calamity.
3.  VMs are frequently utilized when moving workloads and applications to the cloud. Businesses can establish virtual machines (VMs) in the cloud, move their programs and data there, then turn down their on-premise servers.
4. Web applications, databases, and other services can be hosted on VMs. Hosting companies are able to generate virtual machines (VMs) for their clients, allowing them total control over their virtual environment.

Difference between Google Compute Engine and Google App Engine

Google Compute Engine	Google App Engine
Google Compute Engine (GCE) comes under infrastructure as a service (IaaS)	Google app engine (GAE) Platform as a Service (PaaS)
Virtual machines(VMs) are available in different sizes we can select the Virtual machine based on our needs.	The underlying infrastructure will be fully taken care of by Google App Engine (GAE).
If an organization that wants control there want control over its infrastructure can use Google Compute Engine(GCE).	Google App Engine (GAE) is suitable for organizations that want to focus on application development without worrying about infrastructure.
Google Compute Engine(GCE) can manage workloads that are more complex to handle	Google App Engine (GAE) can support different programming languages like Java, Python, Node.js, and Go.

Why Do Organizations Prefer Google Compute Engine?

The following are the reasons that the Google compute engine is mostly used in organizations: 

1. Scalability: Scaling up and down based on traffic will be done automatically by Google Compute Engine. Because of automation, the cost will be reduced there is a need to maintain every time maximum servers will scale up automatically based on the incoming traffic. 
2. Security: For any organization, security is the most important thing to secure their data Google Compute Engine offers a wide variety of features like encryption of data and controlling the authorization and authentication of the users to the Google Cloud Resources.
3. Cost-effectiveness: Billing will be based on the resource used per certain time like it is pay as you go model.
4. Integrations: You can integrate with different services which are available in google cloud like kubernetes and the storages. It can manage different workloads based on the incoming traffic.

Advantages of Google Compute Engine

1. Scalability: Google compute engines helps us to scale up or down our VMs automatically based on incoming traffic to meet the changing demands.
2. Load balancing: We can increase the performance of an application by distributing traffic to several regions and availability zones with the aid of the Google compute engine load balancing. 
3. Security: You can protect data which is stored in GCP by applying encryptions, restricting access to the users, and restricting the incoming traffic to our application.
4. Integration: You can integrate with different services which are available in google cloud like kubernetes and storage. It can manage different workloads based on the incoming traffic.
5. Operating systems: It can support no.of operating systems like RedHat, Ubuntu Windows servers, and so on.

Google Compute Engine Pricing

Flexible pricing is offered by Google Compute Engine (GCE). As mentioned below:

1. Pay-as-you-go: We can pay only for the resources that we use on an hourly basis. 
2. Committed Use Discounts (CUD): Committed Use Discounts (CUD) are like the organization giving commitment to the Google Cloud by saying we will use certain resources for certain years. Then Google Cloud will provide a discount on that particular resource.
3. Sustained Use Discounts (SUD): With SUD, as your usage increases over time, you automatically enjoy reductions on your usage. SUDs are the best choice for workloads that operate constantly for a long time.

Google Compute Engine Charges On Resources

Google compute engine pricing depends on the services we are using and the time we are using like virtual machines, types of storage, network usage and etc Below are some factors on which pricing depends.

1. Type of virtual machine: The pricing will depend on the type of virtual machine you are choosing. This means touch memory, how many CPUs are, and usage time.
2. Network Usage: The charges will be based on the amount of data transferred from your virtual network to another network.
3. Committed discounts: Google compute engine will offer some discounts by you giving the commitment to a Google Cloud Platform by using certain instances for a certain amount of time.
4. Integrating with external services: Google compute engine will change for the services separately like load balancers, managed database, and managed kubernetes. Will be charged based on how much time we used the service.

Frequently Asked Questions

1. Google Compute Engine is SAAS or PAAS?

Answer: 

Google compute engine is a service offered by Google cloud platform which is considered as a infrastructure as a service.