Google Cloud vs. AWS:
Businesses are still moving toward cloud computing. You’re one of many looking for the additional advantages of cloud technology, whether through adopting a single cloud service or moving your complete Infrastructure into a new cloud ecosystem.
There are many benefits to moving to the cloud, from increases in scalability, security, and flexibility to decreases in cost and environmental effect. Naturally, the shift is more difficult than it used to be.
The cloud ecosystem, which was first introduced, has since grown to include a wide range of suppliers, technology, goods, and services. Your selections might soon reach the thousands as you try to piece together the many combinations across these verticals. It rapidly becomes clear that there can be too many options.
A few businesses stand out from the competition to dominate their markets, just like in any industry. When we think of cloud computing providers, three companies come to mind: Google Cloud Platform, Amazon Web Services, and Microsoft Azure.
Today, we’ll contrast Google Cloud Platform and Amazon Web Services, two industry titans in the cloud. Each provider’s goods and services will be thoroughly examined. Trying to make the process of contrasting these two cloud service providers clearer and easier so that you can make a well-informed choice.
Even though Kinsta only uses the Google Cloud Platform, we’ll give you an unbiased assessment. Both platforms have many advantages, but which is best for you will ultimately depend on the particular needs of your business.
Why Choose Amazon Web Services Over Google Cloud
You will surely find three suppliers if you plan to use cloud services: Google Cloud, Amazon Web Services, and Microsoft Azure. Today, our comparison will center on Google Cloud vs. AWS two of them.
These tech industry heavyweights in the cloud are well-known. Both businesses have dominated their respective markets for more than ten years. They are rigorous in their pursuit of innovation and perfection and are known as industry leaders. Each boasts an abundance of technical skill that is nearly impossible to match.
They have yet to unexpectedly create industry-leading cloud computing platforms, given their different technology backgrounds. In their Infrastructure as a Service (IaaS) Magic Quadrant for September 2020, Gartner has once again cited Google and AWS as the market leaders.
For Amazon, the top-right position of the Leader’s quadrant in Gartner’s Magic Quadrant for Cloud Infrastructure as a Service has been held by AWS for ten consecutive years (IaaS). Achieving the top ranking for the ability to execute and the greatest distance for vision completeness.
Google Cloud and AWS Remain Industry Leaders
Since IaaS solutions started to gain popularity in 2008, Google Cloud and AWS have dominated the cloud computing market.
Google and Amazon were listed in research from Gartner in August 2020 as part of a group of five public cloud infrastructure providers that account for 80% of the IaaS industry. A pattern that is only expected to persist as both businesses intensify their efforts to strengthen their position in the market.
Despite the global pandemic slowing down major economies, Gartner predicts a 6.3% increase in global public cloud sales in 2020. We should expect comparable results in the cloud arena, driven by a boom in remote work, especially in light of the report’s assertion that the Desktop as a Service (DaaS) market has grown by 94%. In light of this, Google and Amazon are certain to keep growing. Google cloud services have a cloud provider for their cloud platforms and google cloud storage. There are different Google cloud network locations and a virtual private cloud. AWS cloud has thriving cloud communities with public cloud service providers providing access to both Aws and clouds.
Although they both began in the IaaS market, Google Cloud and AWS now provide hundreds of IaaS, SaaS, and PaaS options. Both businesses continue to innovate and diversify their portfolio of cloud service products.
Revenue from Google Cloud Platform in 2020
With overall sales rising 18% yearly, Alphabet’s Q4 and Fiscal Year 2019 earnings demonstrated the company’s sustained ability to produce robust growth. Although Google Cloud’s sales are not publicly available, the business announced a spectacular increase of more than 100%, placing it on an annual run rate of $10 billion as of year’s end.
The Google Cloud parent company, Alphabet, saw its first-ever quarterly revenue decline since going public in 2004 in 2020 as a result of the Coronavirus outbreak. With such a bleak outlook, Google Cloud has defied expectations and appears to be experiencing rapid development.
Thanks to Google Meet, which helped their video conferencing solution become popular among distant workers, Google Cloud saw considerable growth in Q1. The Google Cloud Platform’s YoY revenue growth has persisted, according to the earnings release statements for the first, second, and third quarters. Google Cloud revenue is anticipated to increase to a run rate of over $13 billion annually as we approach the end of 2020, with a predicted 30% growth in 2019.
Amazon Web Services 2020 revenue
According to Amazon’s Q4 Earnings Release, the sales revenue for AWS in 2019 was close to $10 billion. Putting the company on a revenue run pace of more than $40 billion annually.
The start of the coronavirus pandemic in 2020 has caused a sharp slowdown in AWS growth. YoY growth was dropping and settling at a sub-30 percent growth rate in each of the three quarters’ earnings release statements. There has been a noticeable slowdown compared to increases of 40–50% over the previous three years.
This is far from a bleak situation; AWS is now on a $43 billion annual revenue run pace, and the number is anticipated to rise after Q4 is through. The only possible exemption is if you own stock in Amazon, particularly after Jeff Bezos ordered Amazon shareholders to “have a seat” as their COVID-19 reaction eats away at operating profits.
Comparison of the Features of Google Cloud vs. Amazon Web Services
Comparing the Google Cloud with AWS platforms is a challenging task. Their vast and constantly increasing cloud services now provide a huge selection of items, numbering in the hundreds. Further complicating matters, vendors frequently name comparable goods differently from one another. Therefore, it demands a certain level of expertise and comprehension to prevent losing the details.
Thankfully, both the Google Cloud Platform and the Amazon Web Services Platform classify their items under the same category titles, which simplifies the work. We have accelerated the process to save you time by comparing the most popular services from business-critical areas.
The components of a typical cloud deployment, including computation, networking, security, and storage, will be discussed in this section. Kinsta has first-hand knowledge of using these services to provide industry-leading hosting solutions.
We also talk about the important issues surrounding these services. Support for assistance, the platform’s security, pricing, and billing procedures.
We’ll concentrate on virtual machines when contrasting the computational capabilities of Google Cloud vs. Amazon Web Services (VMs).
These computer systems can execute practically any job you can imagine and offer the same capability as a real computer. Since they form the basis of your cloud environment, you must select a VM setup appropriate for your company’s requirements.
Although their unique product offerings are given various names, both cloud providers have followed a similar strategy for VMs.
The Google Cloud Platform’s service offering is called Compute Engine, whereas Amazon Web Services is called Amazon Elastic Compute Cloud (Amazon EC2). Each service provider also employs various terminologies and ideas.
Features of virtual machines
Both services offer several closely related functionality for deploying virtual machine instances on Compute Engine Amazon EC2, including the following:
- the capacity to build instances using saved disk images
- the ability to start and stop instances of demand
- Free administration of your instances from restrictions
- Your instances’ ability to be tagged
- Various operating systems are available and can be installed on your instance.
- Access to virtual machines
- There are several significant variations between Compute Engine and Amazon EC2’s approaches to accessing your virtual machine.
You must include your SSH key if you want terminal access to an Amazon EC2 instance.
Terminal access is more adaptable with Compute Engine. Enabling the creation of an SSH key whenever you require one, even if the instance is currently running. Additionally, thanks to Compute Engine’s browser-based SSH terminal, accessible through the Google Cloud Console, you won’t need to save these keys on your personal computer.
Types of Virtual Machine Instances
Compute Engine and Amazon EC2 make it simple to launch your virtual machine by providing a variety of preconfigured instances. These instances use particular virtual CPU, RAM, and network specifications.
Both Google and Amazon provide hundreds of different virtual machines that can be configured differently. Each provides flexibility, enabling you to alter configurations and scale your VM resources to suit your company’s particular demands.
You can do this by boosting the number of CPUs and the amount of RAM to extremely high standards.
The following is the highest the providers will go:
Google Compute Engine virtual machines can use up to 416 vCPUs and 11,776 GB of RAM.
Scaling up to 448 vCPUs and 24,576 GB of RAM, Amazon EC2 virtual machines
Both platforms utilize a roughly identical classification throughout the spectrum of VM types. Even so, in some areas, one provider might provide a particular machine type that the other does not.
Depending on your business needs, you can select from various machine types across categories, such as shared core, general-purpose, memory-optimized, compute-optimized, storage-optimized, GPU, and high-performance.
The following table, which includes the most recent machine types for both services, was put together to give you the greatest virtual machine comparison between Amazon EC2 and Compute Engine.
Images of virtual machines
You can use machine images to speed up the deployment of virtual machines.
These are normally set up with an operating system and the necessary database and web server software. Both Amazon EC2 and Compute Engine use machine images to launch new instances. They enable you to use photos provided by a third-party vendor or unique ideas developed for private use in addition to the basic setups.
The systems are comparable enough that you can create images on Amazon EC2 and Compute Engine using the same methodology.
They employ slightly diverse strategies for image storage. While Amazon EC2 saves its pictures in Amazon Simple Storage Service (S3) or Amazon Elastic Block Store, Google Cloud stores its photos with Compute Engine (EBS).
Access to a community repository of ready-made images and the option to make your images publicly available are the two key advantages Amazon EC2 has over Compute Engine (should this be a requirement).
Contrarily, Compute Engine has the advantage of having machine images that are accessible worldwide. In contrast, Amazon Machine photos are geo-locked or only accessible in a particular area.
Automatic Virtual Machine Instance Scaling
The flexibility to scale your workload resources to match demand is one of the most potent advantages of the cloud. To sustain performance during busy periods, resources are increased. Conversely, resources are decreased during slow periods to reduce waste and keep costs under control. Autoscaling is the term used to describe this procedure.
You can add and remove resources following user-defined policies using Compute Engine and Amazon EC2’s support for and implementation of autoscaling.
Each instance is in a set of auto-scaled illustrations created by Amazon EC2 according to a defined launch configuration. One of the three selected scaling plans determines whether to add or remove instances.
You can manually tell the computer to scale up or down.
You set aside certain times to automatically scale resources in your schedule.
Dynamic: You design scaling rules for your instances based on measurements from Amazon CloudWatch or queues from the Amazon Simple Queue Service (SQS).
Compute Engine scales a managed instance group’s instances. Resources are scaled according to an autoscaling policy for each instance group after it is established from an instance template. The auto scaler on Compute Engine, in contrast to Amazon EC2, only enables dynamic scaling.
instances of a temporary virtual machine
Temporary instances are a viable alternative to consider if you want to use cloud computing but have a tight budget. Executing on virtual computers using resources that were spared from other processes.
Since temporary instances are only occasionally available, it is ideal to use them for tasks that:
It can be interrupted without losing work, doesn’t need to be finished in a specific amount of time, and normally doesn’t require more processing resources, like rendering video.
Temporary instances are a feature offered by both Amazon EC2 and Compute Engine. Although their temporary VMs have various pricing strategies and naming standards, they have the following characteristics in common:
They are limited to a subset of machine types and images compared to on-demand instances and are completely controllable while operating and operating at comparable performance levels.
Spot Instances are short-term virtual machines (VM) on Amazon EC2. There are two formats available for them:
Undefined Spot Instances:
You buy a spot instance for an arbitrary amount of time, paying the rate when the sample operates. This instance may be purchased for up to 90% less than the typical rate for on-demand services. You may verify and contrast current Spot costs with On-Demand rates through the Spot Instance Advisor.
Spot Instances for the predetermined period—you prepay for a block. For up to 6 hours, available in hourly increments. When you prepare ahead, you can only get 30–50% discounts.
Preemptible Virtual Machines are the moniker given to Compute Engine’s interim VMs. They run for up to 24 hours (if not reclaimed) before being automatically terminated, which is a longer duration of availability than their Amazon EC2 counterparts. Compared to on-demand prices for comparable VM instances, their fixed pricing structure is offered at a discount of up to 80%.
Features of Networks
Both Google Cloud and Amazon Web Services have built powerful worldwide cloud infrastructures. Their vast networks are made up of hundreds of globally connected data centers.
Each provider has created a cutting-edge cloud network optimized for minimal latency, various redundancy possibilities, and high fault tolerance. Each provides networking services that can provide VMs, other cloud services, and on-premises servers with high-speed connectivity.
Both Google Cloud and Amazon Web Services offer a variety of features for cloud computing, such as autoscaling and temporary instances. Autoscaling helps you maintain an optimal number of resources to meet your application’s demands. At the same time, brief models are ideal for cost-effective tasks that don’t require long processing time. More Blog And Follow YouTube Channel