What are the differences when comparing AWS vs. Azure vs. Google Cloud? Discover what each one is so you can better understand the best option for you.
Amazon Web Services (AWS) presently dominates infrastructure, including scalable storage, networking, server, mobile development, and cybersecurity solutions. Microsoft Azure, its chief rival, provides some of the most scalable and efficient software solutions. Google Cloud Platform GCP offers high-end big data analytics solutions and allows easy interaction with other vendor products.
Certified cloud computing specialists are in demand, outperforming the disruptive move away from in-house servers and computing capacity toward the flexibility and scalability of cloud-based systems. Explore below how the three can shape your IT career path.
Cloud computing defines the supply of computing services—including servers, storage, databases, networking, software, analytics, and intelligence—via the internet ("the cloud") to provide fast innovation, flexible resources, and economies of scale. Users pay-as-you-go, which helps cut operating expenses, run infrastructure more efficiently, and scale as business needs change.
The cloud provides many options for storing, serving, and processing data. Cloud networks enable everything from Netflix and Major League Baseball to IoT sensors and machine learning applications. The following are some benefits of cloud computing:
Cloud computing replaces upfront capital infrastructure expenses with low variable costs that scale with your organization. Thanks to the cloud, businesses no longer need to prepare for and purchase servers and other IT equipment weeks or months in advance. Instead, they may whiz up hundreds or thousands of servers in minutes and deliver results faster.
Cloud computing removes the need for physical storage and maintenance, allowing IT professionals to focus on more critical business goals. Instead, the resources are pooled to provide service to many consumers simultaneously, providing location independence.
With cloud computing, IT resources are just a click or tap away. This on-demand availability allows you to minimize the time it takes for developers to access those resources from weeks to minutes. Because the cost and time to experiment and innovate are reduced, leading to a dramatic boost in organizational agility.
The capacity to scale elastically is a big plus for cloud computing services. It allows organizations to enjoy greater agility by receiving the exact resources they need, including bandwidth, storage, and computing power. Additionally, users get IT resources at the precise time needed and from the right geographic place in cloud language.
Amazon Web Services (AWS) offers computer resources and services that may construct applications in minutes at pay-as-you-go prices. For example, you can rent a server on AWS to connect to, configure, protect, and run just like a physical server. The distinction is that the virtual server runs on top of an AWS-managed planet-scale network.
Coursera
Expedia
Netflix
Coinbase
Formula 1
Intuit
Airbnb
Lyft
Food and Drug Administration (FDA)
Coca Cola
Microsoft Azure is a public cloud platform that provides infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) solutions for analytics, virtual computing, storage, networking, and other services. It can enhance or replace your on-premise servers.
Bosch
Audi
ASOS
HSBC
Starbucks
Walgreens
3M
FedEx
Walmart
HP
Mitsubishi Electric
Renault
Google Cloud, originally App Engine, is a cloud computing services suite established by Google in 2008. GCP offers enterprises all around the world infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). GCP, for example, is primarily a service for developing and maintaining original applications that can then be published from its hyper-scale data centers.
Toyota
Equifax
Nintendo
Spotify
The Home Depot
Target
Paypal
UPS
AWS, Microsoft Azure, and Google Cloud Platform are sweeping the new digital world with a new storm of technology based on remote servers. There is fierce competition in the public cloud market, and here is what sets each platform apart [1];
Features | Amazon | Microsoft Azure | Google Cloud |
---|---|---|---|
Age | 11 years old | 5 years old | 6 years old |
Pricing | Per second pricing with a 60-second minimum | Per-minute basis | Per-minute basis |
Compute | EC2 (Elastic Compute Cloud) provides all the computing administration. The program oversees virtual machines, which can either be designed by the owner or have pre-configured settings for convenience | With Microsoft Azure, you can create virtual machines and scale sets for virtual machines. | As part of GCP (Google Cloud Platform), GCE (Google Compute Engine) does a similar function. |
Storage | AWS provides apportioned, transient (brief) stockpiling. As soon as an instance begins, it is demolished at the end of the case. | Azure uses ID drives (transient capacity), and Page Blobs VM-based volumes are stored in Block Storage (Microsoft's choice). Object Storage uses Square Blobs and Files. | Comparatively, Google's Cloud Platform offers both brief stockpiling and constant circles. For Object stockpiling, GCP has Google Cloud Storage. |
Understanding the history of each platform is the first step in evaluating different cloud service providers. Each service began in another place, influencing how providers focus their offers.
AWS became public in 2006, with services like Elastic Compute Cloud (EC2) and Simple Storage Service (Amazon S3). Elastic Block System (EBS) became publicly available in 2009, and services like Amazon CloudFront and Content Delivery Network (CDN) were added to the mix. It has an extensive user base and higher levels of trust and reliability as one of the first cloud providers.
Microsoft Azure, known initially as Azure, was established in 2010 to provide enterprises with a capable Cloud Computing platform. In 2014, Azure was renamed 'Microsoft Azure,' while 'Azure' is still widely used. Microsoft Azure has made significant progress compared to its competitors since its debut.
Google Cloud Platform launched in 2008, and in less than a decade, it has established a strong foothold in the cloud business. Google Cloud strengthened Google's products, including its hugely popular search engine and its video-sharing platform, YouTube. However, they have now launched enterprise services, allowing anyone to access Google Cloud Platform, which shares the same infrastructure as Google Search or YouTube.
When selecting a cloud provider, the supported regions and availability are the first things to consider. Because of issues such as latency and compliance regulations, especially when dealing with data, have a direct impact on performing your cloud.
Here are the Big Three as of September 2021:
Amazon Web Service divides into 22 geographic regions and 14 data centers. There are over 114 edge locations and 12 Regional Edge Caches.
Microsoft Azure operates in 54 regions, each with at least three availability zones and 116 edge locations.
Google Cloud Platform comprises 34 cloud regions, 103 zones, and 200 plus edge locations.
Compute is a term that describes how computers work. Connecting many nodes is simple for a good cloud provider. Here is a look at each platform's computational capabilities individually -
SERVICE | AWS | AZURE | GCP |
---|---|---|---|
VM (Compute Instance) | EC2 (Elastic Compute) | Azure Virtual Machine | Google Compute Engine |
PaaS | AWS Elastic Beanstalk | App Service | Google App Engine |
Container | AWS Elastic Container/Kubernetes Service | Azure Kubernetes Service (AKS) | Google Kubernetes Engine |
Serverless Functions | AWS Lambda | Azure Function | Google Cloud Functions |
The three cloud providers are currently in a state of high competitiveness. All three suppliers offer essential tools and services, and are likely to extend them in the future, based on current trends and customer wants.
Artificial Intelligence and Machine learning:AWS has released Gluon. This open-source deep-learning library allows developers and non-developers to build neural networks without prior knowledge of AI. DeepLens is an AI-powered camera that may create and implement machine learning algorithms for optical character recognition, image identification, and object recognition.
SageMaker to Serverless: SageMaker is another AWS service used to train and deploy machine learning models. It also includes the Lex conversational interface, enabling Alexa services, Greengrass IoT messaging, and Lambda serverless computing.
Cognitive Services:Bing Web Search API, Face API, Computer Vision API, and Custom Vision Service are among the cognitive services available. Microsoft offers many IoT management and analytics services and functions, and a serverless computing solution.
Supporting MSFT Software: Azure includes several solutions that support Microsoft products installed on-premises. Windows Server Backup in Windows Server 2012 R2 and Windows Server 2016 linked to Azure Backup. Visual Studio projects are hosted on Azure by Visual Studio Team Services.
IoT to Serverless: Google Cloud includes APIs for natural language, speech, translation, and other advanced technologies. It also offers IoT and serverless services. However, these are still beta versions.
Big On AI: Google Cloud is now the frontrunner in AI advancement. TensorFlow, an open-source software library for creating machine learning applications, deserves credit. Many developers love TensorFlow.
For most enterprises, the optimal cloud option is a public and private cloud combination. A hybrid cloud allows you to combine one or more public clouds with existing infrastructure and a private cloud. It’s essentially a mix of environments where you can run applications, making it a popular option among organizations that have already invested a lot of money into IT infrastructure.
An organization benefits by employing a mix of computing, storage, and services environments (on-premises infrastructure, private cloud services, and a public cloud). There is explicit coordination among the various platforms with the hybrid cloud.
Amazon ECS Anywhere
AWS Snowball
AWS Snowcone
AWS Outposts
AWS Local Zones
VMware Cloud on AWS
AWS Wavelength
Amazon EKS Anywhere
AWS Snowcone
Azure Arc
Azure Backup
Azure Active Directory
Azure Security Center
Azure Blob Storage
Azure Stack
Azure Centinel
Anthos
Traffic Director
Looker
Cloud Build
Operations
Cloud Run for Anthos
The IT community believes Microsoft Azure has the lowest on-demand cost, while Amazon is somewhere in the center. All three systems provide all users with competitive price plans and extra cost control features (reserved instances, budgets, and resource optimization). Several factors determine the cost of the cloud platform, including:
Customer specifications
Usage
The services utilized
The following table compares the pricing structures of AWS, Azure, and GCP based on the machine type that each provides: [2]
Machine Type | AWS | Azure | GCP |
---|---|---|---|
Smallest Instance | AWS charges roughly US$69 per month for a primary instance with two virtual CPUs and eight gigabytes of RAM. | In Azure, the same type of instance, i.e., an instance with 2 CPUs and 8 GB of RAM, will cost roughly US$70 per month. | Compared to AWS, GCP will supply you with the most basic instance, including two virtual CPUs and eight gigabytes of RAM, at a 25% lower cost. As a result, it will cost you around US$52 every month. |
Largest Instance | The most expensive AWS instance, with 3.84 TB of RAM and 128 CPUs, will cost you roughly US$3.97/hour. | Azure's largest instance includes 3.89 TB of RAM and 128 CPUs. It costs about $6.79 per hour. | GCP leads the pack with its largest instance, 3.75 TB of RAM and 160 CPUs. It will cost you approximately US$5.32/hour. |
Pros
Provides most services, from networking to robots.
Most mature
Considered the best for reliability and security
More computational capacity than Azure and GCP
Cons
All major software providers that make their applications available on AWS Dev/Enterprise support must be paid.
The sheer quantity of services and options available can be overwhelming for newbies.
There are relatively few hybrid cloud alternatives.
Pros
Integration and migration of current Microsoft services are simple.
Many options are accessible, including best-in-class AI, machine learning, and analytics services.
Most services are less expensive when compared to AWS and GCP.
There is a lot of support for hybrid cloud strategies.
Cons
Fewer service choices compared to AWS
Specifically designed for business customers
Pros
Works well with other Google services and products.
Excellent containerized workload support
Con
Limited services compared to AWS and Azure Limited support for enterprise use cases
Every business has unique demands, and each service provider responds to those needs uniquely. A software developer, a financial institution, and an e-commerce company, for example, all use cloud services differently.
They are subject to distinct regulatory compliance obligations. Meanwhile, cloud service providers may offer similar services as any other business but frequently carve out their niche that works well for prospective buyers. Understanding how AWS, Azure, and GCP fit into your firm's larger cloud strategy goals may give you an advantage.
According to the US Bureau of Labor Statistics, software developer positions are expected to rise 22 percent by 2030, far faster than the typical occupation [3]. A recession will likely slow but not stop its growth. Programmers and developers are in demand now and in the coming months and years. You'll be much more appealing to current or potential employers if you can learn a programming language.
AWS Developers: $117,553 per year [4]
Average of $124,029 per year [5]
Average of $115,083 per year [6]
Ready to start a career as an AWS, Azure, and GCP cloud developer?
Certified cloud computing specialists are on-demand, outperforming the disruptive move away from in-house servers and computing capacity toward the flexibility and scalability of cloud-based systems. Learning the requisite cloud computing abilities opens up fantastic chances for you in the IT world. Find the Right Cloud Certification on Coursera.
Amazon Web Services holds roughly 33% of the market share and remains the most popular vendor in the cloud infrastructure services market. 7
Microsoft Azure is an AWS rival for an IT department whose core skill is maintaining essential IT services like AD, DNS, and certain Apps. It's simple to integrate with current resources like Windows 10 PCs, SharePoint,.NET Apps, Teams, and Office 365.
Amazon is comfortably ahead of the market, but the company has slashed prices to fend off the competition.
Google Cloud is preferred above other cloud providers because of its rapid pace of innovation and the flexibility and freedom of choice it provides.
A cloud platform enables businesses to develop cloud-native apps, test and build them, and store, back up, and recover data. Streaming video and audio, embedding information into processes, and delivering software on demand are all business options. They can also examine data with it.
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1. CAST AI. “Cloud Pricing Comparison for 2022: AWS vs. Azure vs. Google Cloud Platform, https://cast.ai/blog/cloud-pricing-comparison-aws-vs-azure-vs-google-cloud-platform/.” Accessed May 19, 2022.
2. Intellipaat. “AWS vs Azure vs Google Cloud: Choosing the Right Cloud Platform,” https://intellipaat.com/blog/aws-vs-azure-vs-google-cloud/.” Accessed June 29, 2022.
3. US Bureau of Labor Statistics. “Software Developers, Quality Assurance Analysts, and Testers: Occupational Outlook Handbook, https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm.” Accessed June 29. 2022.
4. Glassdoor. “How Much Does an AWS Cloud Developer Make, https://www.glassdoor.com/Salaries/aws-cloud-developer-salary-SRCH_KO0,19.htm.” Accessed July 1, 2022.
This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.