Cloud computing has revolutionized how organizations worldwide work, advancing us to a new technology area. Virtualization has made it possible for cloud providers to make the most of their data center resources, allowing businesses to adopt cloud delivery models for their on-premises infrastructure. Unlike the traditional IT infrastructure, cloud computing helps with maximum utilization and cost savings, offering the same self-service and agility to the end users.
To date, most companies are moving towards the cloud, and multi-cloud environments due to the benefits cloud computing offers. Among the most common reasons to adopt cloud computing services are:
- Decreased CapEx;
- Increased availability;
- Reduced infrastructure maintenance;
- Scalability.
The global market size of the cloud is expected to reach $1,251.09 billion by 2028, proliferating from $36,700 million in 2019. Such rapid growth is mainly due to factors like digital transformation across various industries, big data consumption, growth in Internet penetration, and others. According to the latest Gartner forecast, worldwide end-user spending on public cloud services is expected to reach $494.7 billion in 2022 and surpass the $600 billion mark in 2023.
Businesses are adopting cloud computing services because they offer valuable insights into go-to-market approaches, partnering tactics, alliance and acquisition strategies, investments, and best operational practices.
If someone asks me what cloud computing is, I try not to get bogged down with definitions. I tell them that, simply put, cloud computing is a better way to run your business. (Marc Benioff, Salesforce).
Having started in the 1960s, cloud computing has come a long way. To date, it’s no longer a question of whether to opt for cloud computing or not - nowadays, the main question is which cloud platform to go for. The global cloud computing market is flooded with numerous cloud providers, although AWS, Azure, and Google Cloud Platform stand out in the top three, dominating the public cloud landscape and providing safe, flexible, and reliable cloud services. These top companies hold a commanding lead in the IaaS (infrastructure as a service) and PaaS (platform as a service) markets.
How do you decide which one of these cloud vendors to choose? Keep reading to look at the most significant pros and cons of these three cloud giants and fully understand their capabilities and differences to choose the cloud service provider best suited to your needs.
AWS vs. Azure vs. Google Cloud. Market Shares And Growth Rate of Cloud Giants
The pandemic has accelerated the adoption of cloud computing over the last few years, and we can see the figures growing, meaning the crisis was more a long-term booster for the cloud market than a short-term effect. According to Flexera’s report, companies are investing heavily in cloud services, and consumption of private, public, or hybrid cloud approaches continues to expand across all industries.
To date, the global cloud market is dominated by three major cloud providers sharing 64% of the market:
- Amazon Web Services or AWS;
- Microsoft Azure;
- Google Cloud Platform (GCP).
Amazon Web Services (AWS) grows 40% annually and leads the cloud infrastructure services market, according to 33% of total spending. Meta (previously Facebook) recently chose AWS as a long-term strategic cloud service provider as it begins to move away from social media to become a broader metaverse company over the next five years. AWS also announced key customer wins across healthcare, retail, and financial services.
Microsoft Azure has a 22% market share and remains the second largest cloud service provider, growing 46% annually, driven by long-term consumption commitments. In 2017, this cloud provider only had an 11% market share and doubled its position in a very short timeframe. Azure continues to grow its cloud business across multiple sectors, with key wins in the healthcare and financial services sectors. According to Microsoft CEO Satya Nadella, the number of $100 million-plus Azure deals more than doubled year over year, and the company is seeing consumption growth across all industries, customer segments, and geographies,
Google Cloud Platform (GCP) is the third cloud provider, accounting for 9% of the market. According to Alphabet's recent financial report, Google Cloud sales jumped from $4.05 billion in Q1 2021 to more than $5.82 in Q1 2022, with a 44% cloud revenue growth rate. Available to the public since 2010, the Google Cloud Platform now offers over 100 services spanning computing, networking, big data, and others. GCP is the smallest of the top 3 cloud providers compared to AWS and Azure. However, it offers a robust set of cloud services to power and supports any type of application. The industry-leading tools in deep learning, artificial intelligence, machine learning, and data analytics are also among the significant advantages of this cloud services provider.
Flexera’s 2022 State of the Cloud Report states that major public cloud provider usage is shifting among enterprises. The gap between cloud providers continues to decrease yearly, with Microsoft Azure usage surpassing that of Amazon Web Services in several instances for the first time in eleven years.
Overall, the global cloud market is growing at a rate of 34% per year, and although the level of competition remains high, it continues to coalesce around Amazon, Microsoft, and Google.
AWS vs. Azure vs. Google Cloud. Establishment And Availability Zones
AWS or Amazon Web Services is a subsidiary of amazon.com. This platform provides cloud computing services to individuals, companies, and governments on a paid subscription basis. It is the oldest and most experienced cloud service provider with a large user base, years of trust, and reliability. The platform was launched in 2006, offering services such as Elastic Compute Cloud (EC2) and Simple Storage Service (Amazon S3). By 2009, Elastic Block Store (EBS) was made publicly available, and services like Content delivery network (CDN) and Amazon CloudFront joined the list of the AWS cloud computing service offerings.
Microsoft Azure, initially called Azure, was launched four years after the AWS launch, in 2010, with the primary intent to provide a competent Cloud Computing platform for businesses. In 2014, the platform was renamed Microsoft Azure, although the name Azure is still widely used. Since its inception, Azure has shown significant progress among its competitors, evolving into a cloud platform with more than 200 products and services. Today, Microsoft Azure is considered one of the fastest-growing cloud platforms.
Google Cloud Platform (GCP) is offered by Google and is a part of the overarching Google Cloud. GCP represents a set of cloud computing services that run on the same infrastructure Google uses internally for its end-user products, such as Google Search, YouTube, and others. Google Cloud Platform is the youngest cloud services provider. It was launched in 2011 and has created a good presence in the global cloud industry in less than a decade. Currently, GCP offers over 100 services and consists of services including Google Workspace, Chrome OS, and Android.
As for the availability zones, AWS is the most mature cloud platform offering a wide range of services to power and support any type of application. It has already been established that this cloud provider was the earliest in the cloud domain, which means AWS has had more time to expand and build its network. To date, AWS is hosting in multiple locations worldwide. This cloud computing platform has 66 availability zones, with 12 more on the way. Microsoft Azure and GCP are also hosting in numerous locations worldwide, although the main difference is in the number of their availability zones. Thus, Azure is available in 140 countries and 54 regions worldwide. Compared to AWS and Azure, GCP is the smallest cloud provider. For the moment, it has been made available in 20 regions worldwide, with 3 more on the way.
AWS vs. Azure vs. Google Cloud. Who Are the Customers?
Since Amazon Web Services is the oldest player in the cloud market, it has a more extensive user base and community support than other cloud providers. Among the high-profile and well-known customers of this platform are:
- Netflix;
- BMW;
- Airbnb;
- MI;
- Coca Cola;
- Formula 1;
- Food and Drug Administration (FDA);
- Samsung;
- Unilever;
- Pinterest;
- Expedia;
- Gameloft;
- Coinbase;
- Lyft;
- Coursera;
- Intuit.
Azure is also gaining its share of prominent customers with time. As for now, this platform has nearly 80% of Fortune 500 companies as its customers. Some of its major customers are:
- Apple;
- HP;
- Starbucks;
- Mitsubishi Electric;
- Renault;
- National Health Service (UK);
- Center of Disease Control (US);
- McKesson Group;
- Fujifilm;
- Honeywell;
- Johnson Controls;
- Walgreens;
- DAIMLER AG;
- 3M;
- HSBC;
- Polycom;
- Asos.
Google Cloud Platform shares the same infrastructure as that of Google Search and YouTube and, as a result, has many high-end companies on the list of its customers. Notable GCP customers include:
- PayPal;
- Dominos;
- 20th Century Fox;
- Toyota;
- Twitter;
- Spotify;
- Unilever;
- Nintendo;
- Bloomberg;
- HSBC;
- Target;
- Etsy;
- eBay;
- The Home Depot.
All these cloud providers offer a wide range of cloud computing services that are required for any business, and the main difference is in the number of these services. Therefore, when choosing a cloud provider, the service offerings are one of the most important factors to consider. Let’s look at what these three cloud giants offer for businesses in terms of services.
AWS vs. Azure vs. Google Cloud. Features
Key Features of AWS:
- Amazon Glacier. Glacier is a low-cost, secure, and durable data archiving and backup storage service.
- Amazon Virtual Private Cloud (VPC). Amazon Virtual Private Cloud offers a secure and isolated virtual network environment that you can use to launch your AWS resources, including EC2 instances, RDS databases, and Lambda functions.
- CloudFront. It is a content delivery network (CDN) providing fast and secure delivery of your static and dynamic web content, including video, audio, and images.
- Elastic Beanstalk. Elastic Beanstalk is a fully managed service allowing deployment and scale of web apps. The service supports popular programming languages and platforms, including Java, .NET, Node.js, Python, Ruby, and more.
- Elastic Compute Cloud (EC2). Elastic Compute Cloud offers scalable computing capacity in the cloud, allowing you to quickly and easily launch virtual machines to run your applications.
- Elastic Load Balancing (ELB). ELB provides load-balancing services that automatically distribute incoming application traffic across multiple targets, including EC2 instances, containers, and IP addresses.
- Identity and Access Management (IAM). IAM offers security and identity management for your AWS resources. It allows you to control who can access your resources and what actions they can perform.
- Lambda. It is a serverless computing service that allows you to run code without managing servers. Lambda offers good scalability and is cost-effective.
- Relational Database Service (RDS). RDS provides managed database services for MySQL, PostgreSQL, Oracle, SQL Server, and others, allowing users to easily set up, manage, and scale a relational database in the cloud.
- Simple Storage Service (S3). With Simple Storage Service, you get object storage for files, documents, and other unstructured data. S3 is highly scalable and durable.
Key Features of Azure:
- Azure Active Directory (AD). AD provides security and identity management for Azure resources, allowing you to control who can access your resources and what actions they can perform.
- Azure App Service. App Service offers a fully managed platform for building, deploying, and scaling web and mobile applications. It supports popular programming languages and platforms, including .NET, Node.js, Java, Python, and more.
- Azure Cosmos DB. This globally distributed, multi-model database service provides high availability and low-latency access to your data.
- Azure DevOps. With DevOps, you get various tools and services for building, testing, and deploying applications on Azure.
- Azure Functions. Functions is a serverless computing service allowing you to run code without managing servers. The service supports multiple programming languages and platforms.
- Azure Kubernetes Service (AKS). AKS offers a fully managed service for deploying, scaling, and managing containerized applications with Kubernetes.
- Azure Machine Learning. Azure's Machine Learning is a fully-managed service that facilitates the creation, training, and deployment of machine learning models.
- Azure SQL Database. SQL Database offered by Azure is a fully managed relational database service supporting SQL Server databases. It provides high availability, automatic backups, and disaster recovery options.
- Azure Storage. Storage is highly scalable and durable and provides object storage for files, documents, and other unstructured data.
- Virtual Machines. Azure provides a range of virtual machines that can be used to run your applications, including Windows and Linux-based machines.
Key Features of GCP:
- App Engine. App Engine provides a fully managed platform for building, deploying, and scaling web and mobile applications. It supports popular programming languages and platforms, including Java, Python, Node.js, Ruby, and more.
- BigQuery. With BigQuery, you get a fully managed data warehouse service that allows analyzing large datasets using SQL queries. It also provides high availability and automatic scaling.
- Cloud Functions. This serverless computing service allows you to run code without managing servers. Cloud Functions supports multiple programming languages and platforms.
- Cloud Machine Learning Engine. GCP's Machine Learning Engine provides a completely managed service for creating, training, and deploying machine learning models.
- Cloud Pub/Sub. Cloud Pub/Sub is a messaging service that supports reliable message delivery at scale and allows users to send and receive messages between independent applications.
- Cloud SQL. This fully managed relational database service supports MySQL, PostgreSQL, and SQL Server databases, providing high availability, automatic backups, and disaster recovery options.
- Cloud Storage. With Cloud Storage, you get object storage for files, documents, and other unstructured data. It is highly scalable and durable.
- Cloud Vision API. Vision API provides a fully managed service for analyzing images and videos using machine learning models.
- Compute Engine. Compute Engine provides scalable computing capacity in the cloud, allowing you to quickly and easily launch virtual machines to run your applications.
- Kubernetes Engine. Kubernetes Engine offers users a fully managed service for deploying, scaling, and managing containerized applications with Kubernetes.
Amazon, Microsoft, and Google continue to dominate the cloud landscape. Their cloud platforms - AWS, Azure, and GCP offer clients various storage, computing, and networking options. Some features common to the three platforms include self-service, instant provisioning, security and compliance, and identity management. AWS is considered much bigger than Azure and GCP in terms of functionality, although these platforms are actively progressing to prove their market dominance. Service offerings from the top 3 cloud providers that come under the computing, storage, database, and networking domains are mapped below.
Features | AWS | Azure | GCP |
---|---|---|---|
Compute Services | Amazon EC2 AWS Beanstalk Amazon EC2 Auto-Scaling Amazon Elastic Kubernetes Services Amazon Elastic Container Registry Amazon Lightsail Elastic Load Balancing AWS Serverless Application Repository AWS Batch AWS Lambda AWS Fargate AWS Outposts VMWare Cloud for AWS | PaaS FaaS Azure Batch Service Fabric Cloud Services Azure Container Service Container Instances Batch Virtual Machines Compute Engine Virtual Machine Scale Sets | App Engine Compute Engine Kubernetes Engine Knative Instant Groups Docker Container Registry Graphics Processing Unit Cloud Functions |
Database Services | Dynamo DB Aurora ElastiCache Neptune RDS Redshift Database migration service | SQL Database Database for PostgreSQL Database for MySQL Serves Stretch Database Table Storage Data Warehouse Redis Cache Data Factory Cosmos DB | Cloud SQL Cloud Spanner Cloud Bigtable Cloud Datastore |
Storage Services | Simple Storage Service (S3) Elastic File System (EFS) Elastic Block Storage (EBS) Snowball Snowball Edge Storage Gateway Snowmobile | Blob Storage Disk Storage File Storage Queue Storage Data Lake Storage | Cloud Storage Transfer Appliance Persistent Disk Transfer Service |
Networking Services | Amazon Virtual Private Cloud (VPC) | Azure Virtual Network (VNET) | Cloud Virtual Network |
AWS vs. Azure vs. Google Cloud. Key Tools
Competition for leadership in public cloud computing remains tough between three top cloud companies - AWS, Microsoft Azure, and GCP. Following the latest trends and customer demands, all the providers have begun offering these services and are aimed at expanding them in the future.
Amazon Web Services Key Cloud Tools
Among its various AI-oriented services, AWS offers customers DeepLens - an AI-powered camera for developing and deploying ML algorithms for optical character recognition and image or object recognition. DeepLens allows developers of all skill levels to get started with deep learning in less than 10 minutes by providing sample projects with hands-on case studies that can be launched with a single click. AWS has also announced Gluon - an open-source deep learning library that developers and non-developers can utilize to build neural networks without any knowledge of AI.
The list of numerous AWS services in the areas of ML and AI also includes SageMaker, which helps data scientists and developers quickly prepare, build, train, and deploy high-quality machine learning models by combining a broad set of capabilities built specifically for ML. AWS also has a Greengrass IoT messaging service, Lambda serverless computing service, and the Lex conversational interface that powers Alexa services.
Microsoft Azure Key Cloud Tools
Microsoft Azure is a cloud provider that invests the most in machine learning and AI. The primary cognitive services of this cloud vendor include machine learning and bot service. Azure also offers such tools as Face API, Bing Web Search API, Computer Vision API, Text Analytics API, and Custom Vision Service. Besides this, for IoT, Microsoft Azure has several analytics and management services, and its serverless computing service is known as Functions.
Azure also has several tools that help in supporting on-premises Microsoft software. Azure Backup is a service that links Windows Server Backup in Windows Server 2012 R2 and Windows Server 2016, while Visual Studio Team Services hosts Visual Studio projects on Azure.
Google Cloud Platform Key Cloud Tools
Among all the advanced technologies available on Google Cloud, this cloud provider offers APIs for natural language, translation, speech, and more. Additionally to these tools, GCP offers IoT and serverless services but Beta previews.
As for AI and ML, Google Cloud Platform is currently the leader in AI development. One of the bight examples of this is TensorFlow - a free, open-source software library for building ML and AI applications, which is highly popular among developers. TensorFlow can be used across various tasks, but its primary focus is on the training and inference of deep neural networks.
Features | AWS | Azure | GCP |
---|---|---|---|
AI/ML | Comprehend Polly Lex Rekognition Deeplens Machine Learning Translate Deep Learning AMIs Transcribe SageMaker TensorFlow on AWS Apache MXNet on AWS | Machine Learning Cognitive Services Azure Bot Service | Cloud Machine Learning Engine Cloud Natural Language Dialogflow Enterprise Edition Cloud Translation API Cloud Speech API Cloud Job Discovery (Private Beta) Cloud Video Intelligence |
IoT | IoT Core Greengrass FreeRTOS IoT Analytics IoT 1-Click IoT Device Defender IoT Button IoT Device Management | IoT Edge IoT Hub Time Series Insights Stream Analytics | Cloud IoT Core (Beta) |
Serverless | Lambda Serverless Application Repository | Functions | Google Cloud Functions (Beta) |
DevOps | Code Pipeline Code Build Code Deploy Code Star | Azure Boards Pipelines Repos Artifacts Test Plans | GCP DevOps CloudBuild Artifact Registry |
AR & VR | Amazon Sumerian | Azure Mixed Reality (Spatial Anchors/Remote Rendering) | ARCore |
Business Analytics | Amazon Quicksight | Azure Power BI | Looker |
Game Development | Amazon GameLift | Azure PlayFab | |
End-User Computing | Amazon Workspaces | Azure Virtual Desktop | |
Robotics | AWS RoboMaker |
AWS vs. Azure vs. Google Cloud. Hybrid And Multi-Cloud Support
All these three cloud vendors are not yet into the hybrid and multi-cloud offerings significantly, although each offers different tools to provide their customers with maximal flexibility. AWS Hybrid and Multi-Cloud Options include:
- AWS Snowball;
- AWS Snowcone;
- AWS Local Zones;
- AWS Outposts;
- AWS Wavelength;
- VMWare Cloud on AWS;
- Amazon EKS Anywhere;
- Amazon ECS Anywhere.
In its turn, Microsoft Azure offers its customers the following tools:
- Azure Backup;
- Azure Arc;
- Azure Stack;
- Azure Active Directory;
- Azure Blob Storage;
- Azure Security Center;
- Azure Centinel.
GCP’s multi-cloud and hybrid offerings list is the most modest among the three cloud vendors, although the platform continues to develop in this area. Google Cloud Platform offers users the following tools:
- Cloud Build;
- Anthos;
- Traffic Director;
- Operations;
- Looker;
- Cloud Run for Anthos.
AWS vs. Azure vs. Google Cloud. Pricing
Line-of-business leaders everywhere are bypassing IT departments to get applications from the cloud and paying for them like they would a magazine subscription. (Daryl Plummer, Gartner).
One of the key reasons organizations worldwide are moving to the cloud is the desire to save money. Indeed, cost savings is one of the main benefits of cloud computing that attract more and more companies every year. According to Flexera’s report, 94% of enterprises use the cloud, while cost reduction is one of the top reasons businesses choose to adopt the cloud.
By using cloud infrastructure, you don’t have to spend much on purchasing and maintaining equipment that significantly reduces CAPEX costs and Total Cost of Ownership. With cloud computing services, you don’t have to invest in hardware, utilities, facilities or a large data center to grow your business. Additionally, you don’t need large IT teams to handle the cloud data center operations, as you can make the most of the experience of your cloud provider's staff. Another advantage of cloud computing is that the downtime risk is minimal, so you don’t have to spend time and money fixing this problem.
Comparing the top 3 cloud providers, let’s look at the pricing options they offer to the customers. The pricing of the cloud platform usually depends on:
- Customer requirements;
- Usage;
- Cloud services used.
AWS, Azure, and GCP offer their customers competitive pricing plans with additional cost management options, such as budgets, reserved instances, and resource optimization, available to all users.
Amazon Web Services
Minimum Instance: In the case of AWS, a basic instance includes 2 virtual CPUs and 8 Gb of RAM, which will cost you around $69/month.
Maximum Instance: The largest instance offered by this cloud vendor includes 3.89 TB of RAM and 128 virtual CPUs and will cost you around $3.07/hour.
Besides this, AWS recently started offering pay-per-minute billing. It also provides customers a one-year free trial and a discount of up to 75% for a 1-3 years commitment. There are three payment options available on AWS:
- No up-front;
- Partial up-front;
- All up-front.
AWS services also come with cancellation available. The platform offers to sell your products on the marketplace.
Microsoft Azure
Minimum Instance: The smallest instance of this platform includes 2vCPUs and 8 Gb of RAM, which will cost you around $70/month.
Maximum Instance: The largest instance offered by Azure includes 3.89 TB of RAM and 128 virtual CPUs. It costs around $6.79/hour.
Like AWS, Azure also offers customers pay-per-minute billing and up to 72% discount for a commitment ranging from one to three years. The cancellation is available but will cost you a 12% cancellation fee. Azure offers only one - all up-front payment option for customers.
Google Cloud Platform
Minimum Instance: The most basic instance offered by GCP provides customers with 2 virtual CPUs and 8 Gb of RAM at a 25% cheaper rate compared to AWS and Azure. Thus, this platform's minimum instance will cost you around $52/month.
Maximum Instance: In the case of the largest instance, GCP takes the lead, offering 3.75 TB of RAM and 160 vCPUs at around $5.32/hour.
In contrast to pay-per-minute billing offered by AWS and Azure, GCP offers users a pay-per-second billing model, allowing them to save much more. Besides this, GCP also provides various discounts to help customers save up to 50% in some cases when compared to AWS. This platform offers a Committed Use Discount (CUS) for one year up to 37% or for three years up to 55% and Sustained Use Discount (SUD) for up to 30%. Apart from a SUD, Google Cloud Platform offers a credit of $300 for 12 months. GCP services come with no cancellation available and with only no up-front payment option.
On-Demand Pricing
Instance Type | AWS | Microsoft Azure | GCP | AWS (per hour) | Microsoft Azure (per hour) | GCP (per hour) |
---|---|---|---|---|---|---|
General purpose | m6g.xlarge | B4MS | e2-standard-4 | $0.154 | $0.166 | $0.134 |
Compute optimized | c6g.xlarge | F4s v2 | c2-standard-4 | $0.136 | $0.169 | $0.208 |
Memory optimized | r6g.xlarge | E4a v4 | m1-ultramem-40 | $0.202 | $0.252 | $6.293 |
Accelerated computing | p2.xlarge | NC4as T4 v3 | a2-highcpu-1g | $0.90 | $0.526 | $3.678 |
Discounted Pricing for 1-Year Commitment (No Upfront Cost)
General purpose | m6g.xlarge | B4MS | e2-standard-4 | $0.097 | $0.0974 | $0.0137 |
---|---|---|---|---|---|---|
Compute optimized | c6g.xlarge | F4s v2 | c2-standard-4 | $0.086 | $0.10 | $0.0214 |
Memory optimized | r6g.xlarge | E4a v4 | m1-ultramem-40 | $0.127 | $0.1482 | $0.0205 |
Accelerated computing | p2.xlarge | NC4as T4 v3 | a2-highcpu-1g | $0.614 | $0.3093 | $2.313 |
Key takeaways:
- For GCP, on-demand pricing of memory-optimized instances was the highest, but the 1-year commitment price is the lowest among all three cloud providers.
- GCP is also much cheaper than AWS and Azure for computing optimized cloud-based instances, although it’s more expensive when it comes to the instance types of accelerated computing.
- The general-purpose instances for AWS and Azure are almost similar for 1-year committed plans.
Serverless Pricing Comparison
All the three cloud platforms offer users serverless services:
- AWS Lambda;
- Azure Functions;
- Google Cloud Functions.
For the computing power you use, these cloud vendors charge you in 100-millisecond increments, allowing you to focus on the code and event triggers while serverless providers will do the rest. With serverless computing, you only pay for the time your code runs without having to pay for reserving CPU Cores and RAM of the underlying EC2 instances or virtual machines. The total cost of serverless computing for all three cloud providers is calculated below.
For better understanding, let’s consider the hypothetical scenario where you allocated 512MB of memory to your function, executed it 4 million times per month, and ran for one second each time.
AWS Lambda Pricing
Monthly compute charges:
- The monthly compute price is $0.00001667 (GB-s).
- The free tier provides 400,000(GB-s).
- Total compute (seconds) = 4M * (1s) = 4,000,000 seconds.
- Total compute (GB-s) = 4,000,000 * 512MB/1024 = 2,000,000 GB-s.
- Total compute – Free tier compute = Monthly billable-compute GB-s.
- 2,000,000 GB-s - 400,000 free tier GB-s = 1,600,000 GB-s.
- Monthly compute charges = 1,600,000 * $0.00001667 = $26.67
Monthly request charges:
- The monthly request price is $0.20/1 million requests.
- The free tier provides 1M requests per month.
- Total requests – Free tier requests = Monthly billable requests.
- 4M requests – 1M free tier requests = 3M Monthly billable requests.
- Monthly request charges = 3M * $0.2/M = $0.60.
Total price per month for AWS Lambda = Compute charges + Request charges = $26.67 + $0.60 = $27.27
Azure Functions Pricing
Resource consumption (seconds) | Resource consumption (GBs) | Billable Resource | Monthly resource- consumption price: | Execution billing: | Monthly execution price: |
---|---|---|---|---|---|
Execution number = 4 million executions. | Resource consumption in GBs = 512 MB / 1,024 MB = 0.5 GB. | Resource consumption = 2M GBs. | Billable resource consumption = 1.6M GBs. | Total monthly execution = 4M executions. | Monthly billable execution = 3M executions. |
Execution duration = 1 second. | Execution time (seconds) = 4 million seconds. | Monthly free grant = 400,000 GBs. | Resource-consumption price = $0.000016/GB. | Monthly free executions = 1M executions. | Price per million execution = $0.20. |
Total resource consumption = 4M executions * 1 second = 4M seconds. | Total consumed GBs = 4M seconds * 0.5 GB = 2M GBs. | Total billable consumption = 2M GBs – 400,000 GBs = 1.6M GBs. | Total monthly resource-consumption cost = 1.6M GBs * 0.000016/GB = $25.60. | Total monthly billable executions = 4M executions – 1M executions = 3M executions. | Monthly execution cost = 3M executions * 0.20 = $0.60. |
Total price per month for Azure Functions = $25.60 + $0.60 = $26.2
Google Cloud Platform
Invocation | Per second usage | Invocation | GB-second | GHz-second |
---|---|---|---|---|
(512 MB / 1024 MB) * 1 second = 0.5 GB-s per invocation. For 512 MB, Google cloud offers an 800MHz CPU. So, GB-seconds would be: (800 / 1000) * 1 second = 0.8 GHz-second per invocation. | 4M executions * 0.5 GB-s = 2M GB-s per month. 4M execution * 0.8 GHz-s = 3,2M GHz-s per month. GCP offers a free tier of 2M invocations, 400,000 GB-seconds, and 200,000 GHz-seconds per month. | 4M – 2M = 2M execution * $0.0000004 = $0.8. | 2M – 400,000 = 1,600,000 * $0.0000025 = $4. | 3,2M – 200,000 = 3M * $0.0000100 = $30. |
Total price per month for Google Cloud Functions = $0.8 + $4 + $30 = $34.8
Key takeaways:
- AWS and Azure have almost the same monthly price, and this is a result of the high free-tier offerings they provide.
- Google Cloud Functions offer the lowest price for GBs consumed per second, along with free-tier offerings. The platform has the highest price per month due to the additional cost associated with MHz CPU performance.
Strengths And Weaknesses of the Platforms. How to Choose the Best Cloud Vendor?
Amazon Web Services
Among all the three cloud giants we’ve considered in our review, AWS remains the biggest player in the cloud computing industry, covering a market share of about 33%. This platform continues to grow and attract customers with more than 200 services available and the ease with which these tools can be used. Other advantages making this platform a prime market player include:
- Extensive, mature offerings
- Support for large organizations
- A global reach with a comprehensive network of data centers around the world.
With its flexibility, scalability, and integrated security for its users, AWS significantly enhances organizations' productivity and business growth and remains the most mature and enterprise-ready cloud services provider.
Among the main drawbacks of this platform is its pricing strategy. Many enterprises continue to find it challenging to understand the cost structure of AWS and manage the costs effectively, especially while running high-volume workloads on the platform. Other downsides of the platform include service limits and technical support fees.
Microsoft Azure
Microsoft Azure is the second largest cloud provider. This platform entered the cloud computing market by moving its on-premises services such as Windows Server, Office, SQL Server, Sharepoint, and others to the cloud. It helps Azur outrun competitors as its cloud services are integrated with other applications that most organizations popularly use. Azur offers a broad feature set and significant discounts to its customers, which, along with the flexibility and security of this platform, makes it the best choice for startups and developers.
Some areas where Azure falls short include its maintenance and complexity, as the platform requires a high level of knowledge to use it. Similar to AWS, Azure also has complicated pricing as its solutions are structured to encompass many stand-alone services.
Google Cloud Platform
Despite the smallest market share of 9%, GCP is a strong competitor when it comes to cloud services. The platform specializes in high compute offerings, such as big data, analytics, and machine learning, and offers its users significant scaling and load balancing capabilities. GCP offers flexible contracts, facilitating easy collaboration, and is the most cost-efficient option. The platform is designed for cloud-native businesses.
The downsides of GCP include a limited choice of programming languages and a complex transition to another vendor. Also, this platform has fewer services and global data centers than AWS and Azure.
Which of the platforms is the best? In terms of establishment, availability zones, number of services, and market share, the winner is AWS. However, considering the growth rate and pricing models, GCP occupies the first place. At the same time, in terms of integration with open source and on-premises systems such as MS tools that are commonly used in almost all organizations, Azure is the winner.
With all this in mind, AWS comes out on top of all the major cloud providers, but it’s hard to say how long it will remain the leading cloud provider, given that Azure and GCP are continually working their way up on the top of the cloud providers list. When choosing the best cloud provider, the key is to choose the most appropriate provider for your needs, as each of the three cloud platforms is unique and offers organizations a variety of options to choose from based on their specific requirements.