Last modified: 10thApril, 2018
The public cloud computing market is estimated to touch around $411 billion in 2020, up from $260 billion in 2017 – Gartner1
Quick Links
- What is Public Cloud?
- Who should go for public cloud?
- The state of public cloud in 2018
- Top Public cloud providers
- AWS vs Microsoft Azure vs Google Cloud Platform vs IBM: The features’ comparison
- AWS vs Microsoft Azure vs Google Cloud Platform vs IBM: The public cloud prices’ comparison
The demand for public cloud solutions is rising, and this translates to growing opportunities for public cloud providers. The top public cloud companies are enhancing their services and dropping the prices to better compete in the public cloud market.
What is Public Cloud? back to top
A public cloud, like Azure or AWS or Google, is a multi-tenant service based upon standard model of cloud computing, where a service provider or a third-party provider provides resources, like storage and applications to the general public over a network, like internet.
Users have no control or visibility over the placement of the infrastructure. Services are either free, low cost or are on pay-per-usage model, so no wastage of resources is there. The set-up is easy and almost inexpensive as cost of applications, bandwidth and hardware are covered by the service provider.
It is not possible to select cache, hardware or storage performance (SAS/SATA) in the public cloud. Public cloud provider decides the hardware and network for the user. Also, PCI, SOX or HIPAA compliance cannot be provided in the public cloud as it is a multi-tenant environment, in which the user’s server shares the network devices, storage and hardware with multiple others in the cloud.
It is different from the private and hybrid cloud as private cloud is used by organizations for their own use, and hybrid cloud is a combination of public and private clouds.
The public cloud comprises a broad range of products and services related to cloud, including infrastructure as a service (IaaS), software as a service (SaaS), and platform as a service (PaaS). As per Gartner, the worldwide public cloud services market is projected to grow 17.3 percent in 2019 to total $206.2 billion, up from $175.8 billion in 2018.
Who should go for public cloud? back to top
Public Cloud is the obvious choice for:
- Developers and testers of application codes who fire up and tear down development servers regularly.
- Those who require scalability i.e. capability of adding compute resources at peak times.
- Those doing projects in collaboration with different teams.
- Those running webservers where data security is not a major concern.
- Those who have SaaS (Software as a Service) applications from vendors implementing proper security strategies.
- Those who are using PaaS (Platform as a Service) for doing ad-hoc software development projects.
The state of public cloud in 2019back to top
As per IDC, cloud services will show double digit growth across the globe. It predicts that the US that showed 64% growth in revenue in 2015, will witness a drop of 4% and will account for 60% growth by 2019. Asia Pacific excluding Japan and Latin America will account for public cloud’s highest growth rates in next 5 years.
As per IDC, Greater Cloud Spending will surpass $500B by the year 2020, including SaaS, PaaS, IaaS, and all managed and professional cloud services – public and private, and supporting hardware and software used in cloud implementation as well.
Top Public cloud providers back to top
The public cloud market is majorly dominated by Amazon, Microsoft, IBM and Google. Experts predict that these face competitions only from one another and are not likely to be replaced by any other cloud service provider in the near future atleast. The reason behind it is that competing in public cloud needs very heavy investment, as well as masses of tech talent to support the underlying infrastructure.
Amazon Web Services (AWS) has been leading the public cloud market since it started services in 2006. In July 2017, Synergy Research report of the public cloud providers market share, found that AWS market share now stands at 34%, compared to 11% for Microsoft and 5% for Google. IBM held its market share steady at 8%, thanks primarily to a strong showing in hosted private cloud services.
“While Microsoft Azure and Google Cloud Platform are doubling in size, IBM continues to dominate in hosted private cloud and AWS is still over three times the size of its nearest competitor. Some of the numbers are actually pretty spectacular. The year-on-year market growth rate is nudging down as we expected in such a large market, but it remains at comfortably over 40% and AWS alone generated revenue growth of $1.2 billion over the last four quarters.” – John Dinsdale, a Chief Analyst and Research Director at Synergy Research Group.
However, under the leadership of CEO Satya Nadella, Microsoft is quickly gaining ground, thereby, shortening the gap between AWS and Azure. IBM has also reportedly recovered from the transformational phase and has been experiencing a growth in its revenue due to its cloud, security services and advanced solutions like IBM Watson.
On the other hand, the search engine giant Google too is able to maintain its position in the top public cloud providers list, with its Google Cloud Platform, by introducing discounts and adding features. Google also announced new Network Service Tiers – Premium and Standard to optimize performance and cost of using public cloud.
Amazon, Microsoft and Google provide similar storage solutions but there are a number of differences in features and pricing of their public cloud services, which set them apart from the other. They either drop the prices of cloud instances, offer discounts, drop billing increments, or even provide per second billing options to stay one step ahead of each other.
Gartner named AWS and Microsoft as the leaders in Gartner’s Infrastructure as a Service (IaaS) Magic Quadrant 2017, while keeping IBM and Google among visionaries, following the leaders closely.
AWS vs Microsoft Azure vs Google Cloud Platform vs IBM: The features’ comparison back to top
The comparison of AWS, Azure, and Google Cloud Platform can be done on the basis of features, pricing, and solutions.
| Features and Solutions | AWS | GCP | IBM Cloud | Azure |
| Maximum Processors in VM | 128 | 96 | 56 | 128 |
| Maximum memory in VM (GiB) | 3904 | 1433 | 242 | 3800 |
| Maximum memory in VM (GiB) | 3904 | 1433 | 242 | 3800 |
| Operating Systems supported | Windows, SLES, CentOS, CoreOS, OpenSUSE, RHEL, CloudLinux, Debian, FreeBSD, Ubuntu, Oracle Linux | Windows, SLES, CentOS, CoreOS, OpenSUSE, RHEL, Debian, FreeBSD, Ubuntu, | Windows, CentOS, CoreOS, RHEL, CloudLinux, Debian, FreeBSD, Ubuntu, | Windows, SLES, CentOS, CoreOS, OpenSUSE, RHEL, Debian, FreeBSD, Ubuntu, Oracle Linux |
| SLA Availability | Amazon S3: Monthly uptime of at least 99.9% for any billing cycle.
Amazon EC2: 99.95% annual uptime in service year. |
99.95% Monthly Uptime | 100% Uptime for Private & Public Network, Customer Portal and redundant infrastructure | 99.9% Uptime |
| Marketplace | AWS Marketplace | G Suite Marketplace | IBM Marketplace | Azure Marketplace |
| COMPUTE | ||||
| Scalability | AWS Auto Scaling | Autoscaling | Auto Scaling | Azure Autoscaling, Virtual Machine Scale Sets, Azure App Service Scale Capability (PaaS) |
| Virtual Servers | Elastic Compute Cloud (EC2) Instances,Amazon LightSail | Custom Machine Types, Compute Engine | IBM Virtual Servers | Azure Virtual Machines, Azure Virtual Machines & Images |
| Backend process logic | – | – | – | Web Jobs |
| Container Instances | EC2 Container Service (ECS), EC2 Container Registry | Kubernetes Engine | IBM Cloud Container Service | Azure Container Service (AKS), Azure Container Registry |
| Container Orchestrators/ Microservices | Elastic Container Service for Kubernetes (EKS) | Google Container Engine | IBM Cloud Container Service | Azure Container Service (AKS), Service Fabric, Azure Container Service (ACS) |
| Batch Computing | AWS Batch | Preemptible VMs | – | Azure Batch |
| Serverless | Lambda, Lambda @ Edge | Google Cloud Functions (Beta) | IBM Cloud Functions | Azure Functions, Azure Event Grid |
| STORAGE | ||||
| Object storage | Simple Storage Services (S3) | Google Cloud Storage | IBM Cloud Object Storage | Azure Storage |
| Shared file storage | Elastic File System | Google Cloud Storage FUSE | File Storage | Azure Files |
| Virtual Server disk infrastructure | Elastic Block Store (EBS) | Google Persistent Disk | Block Storage | Azure Storage Disk |
| Archiving – cool storage | S3 Infrequent Access (IA) | Cloud Storage | Object Storage | Azure Storage – Standard Cool |
| Archiving – cold storage | S3 Glacier | Google Cloud Storage Nearline & Coldline | Backup Storage | Azure Storage – Standard Archive |
| Hybrid Storage | Storage Gateway | – | – | StorSimple |
| Backup | – | – | – | Azure Backup |
| Data transfer | AWS Import/Export Disk, AWS Import/Export Snowball, AWS Snowball Edge, AWS Snowmobile | Cloud Data Transfer | Data Transfer Service | Import/ Export, Azure Data Box |
| Disaster Recovery | AWS Disaster Recovery | – | – | Site Recovery |
| DATABASE | ||||
| Relational Database | RDS for MariaDB, RDS for SQL Server, RDS for MySQL, RDS for Oracle DB, RDS for Postgre SQL | SQL Server, Google Cloud SQL, Cloud SQL support for Postgre SQL (Beta) | Compose for MySQL, Compose for Postgre SQL | SQL Database, Azure Database for MySQL, Azure Database for PostgreSQL (Preview) |
| NoSQL – key/value storage, document storage | Dynamo DB and SimpleDB | Cloud Spanner | Db2 on Cloud | Table Storage Azure Cosmos DB |
| Non-relational database | Amazon Neptune (Preview), Amazon EMR, Amazon Dynamo DB, Amazon SimpleDB | Google Cloud Dataproc, Google Cloud Dataflow, Google Cloud Bigtable, Google Cloud Datastore | Compose for JunusGraph, IBM Open Platform, Cloudant | Azure HDInsight, Azure Batch, Cosmos DB |
| Database Migration | Database Migration Service | – | Lift | Azure Database Migration Service |
| Caching | ElastiCache | None – App Engine only | Compose for Redis | Azure Redis Cache |
| CONTENT DELIVERY AND NETWORKING | ||||
| Cloud virtual networking | Virtual Private Cloud (VPC) | Google Virtual Private Cloud (VPC) | VLANs | Virtual Network |
| Content delivery network | CloudFront | Google Cloud CDN | Content Delivery Network | Azure Content Delivery Network |
| Domain name system management | Route 53 | Google Cloud DNS | DNS | Azure DNS, Traffic Manager |
| Cross – premise connectivity | AWS VPN Gateway | Cloud VPN | VPN | Azure VPN Gateway |
| Dedicated network | Direct Connect | Google Cloud Interconnect | Direct Link | ExpressRoute |
| Load balancing | Classic Load Balancer, Network Load Balancer, Application Load Balancer | Google Cloud Load Balancing | Load Balancer | Load Balancer, Application Gateway |
| INTERNET OF THINGS | ||||
| IoT | AWS IoT | Google Cloud IoT, Cloud IoT Core (Beta) | Internet of Things (IoT) | Azure IoT Hub |
| IoT Services | Kinesis, EMR, SNS, Machine Learning, Data Pipeline, QuickSight | Google Cloud Pub/Sub | IBM Push Notifications | Machine Learning, IoT Hub, Power BI, Stream Analytics, Notification Hubs |
| Streaming data | Kinesis Streams, Kinesis Firehose | Cloud Dataflow | Streaming Analytics | Event Hubs |
| Edge compute for IoT | AWS Greengrass | – | – | Azure IoT Edge |
| ANALYTICS AND BIG DATA | ||||
| Elastic data warehouse | Redshift | Google Cloud BigQuery | Db2 Warehouse on Cloud | SQL Data Warehouse |
| Data orchestration | Data Pipeline, AWS Glue | Google Cloud Dataflow | – | Data Factory, Data Catalog |
| Big data processing | Elastic MapReduce (EMR) | Google Cloud Dataproc, Dataflow | IBM Open Platform | HDInsight |
| Data discovery | Amazon Athena | Big Query | – | Data Catalog, Azure Data Lake Analytics |
| Search | Elasticsearch, CloudSearch | None – only App Engine | Compose for Elasticsearch | Azure Search |
| Analytics | Kinesis Analytics | Google Cloud Dataflow | Streaming analytics | Stream Analytics, Data Lake Analytics, Data Lake Store |
| Visualization | QuickSight | Google Data Studio (Beta) | – | PowerBI, PowerBI Embedded |
| Machine Learning | Machine Learning, SageMaker | Google Cloud AI, Google Cloud Datalab, Google Cloud Machine Learning Engine | Watson | Azure Machine Learning Studio, Azure Machine Learning Workbench |
| INTELLIGENCE | ||||
| Visual Recognition | Amazon Rekognition | Vision API | Visual Recognition | Computer Vision API, Face API, Emotions API, Video API |
| Virtual Personal Assistant | Alexa Skills Kits | Google Assistant | Virtual Personal Assistant | Cortana Intelligence Suite – Cortana Integration, Microsoft Bot Framework + Azure Bot Service |
| Text to Speech | Amazon Polly, Amazon Translate, Amazon Transcribe | Translation API, Speech API | – | Bing Speech API |
| Speech recognition | Amazon Lex, Comprehend | Natural Language API | Natural Language Classifier, Language Translator, Alchemy API | |
| IDENTITY, ACCESS AND SECURITY | ||||
| Firewall | Web Application Firewall | – | Firewalls | Application Gateway Web Application Firewall (in preview) |
| Authorization & Authentication | Identity and Access Management (IAM), Multi-Factor Authentication, AWS Organizations | Google Cloud Identity and Access Management | Feature in webportal | Azure Active Directory, Multi-Factor Authentication, Azure Subscription and Service Management + Azure RBAC |
| Encryption | Amazon S3 Key Management Service for server-side encryption, Key Management Service, CloudHSM | Google Cloud Key Management Service | Hardware Security Module, Key Protect | Azure Storage Service Encryption, Key Vault |
| Security | Inspector, Certificate Manager | – | SSL Certificates, Nessus Security Scanner | Security Center, App Service Certificates |
| Compliance | AWS Artifact | – | – | Microsoft Service Trust Portal |
| Directory Services | AWS Directory Service + Windows Server Active Directory on AWS, Cognito, AWS Directory Service | – | – | Azure Directory Domain Services + Windows Server Active Directory on Azure IaaS, Azure Active Directory B2C |
| Information protection | – | – | – | Azure Information Protection |
| MONITORING AND MANAGEMENT | ||||
| DevOps (Deployment Orchestration) | OpsWorks (Chef-based), CloudFormation | – | – | Azure Automation, Azure Resource Manager, VM extensions, Azure Automation |
| Monitoring & Management (DevOps) | CloudWatch, CloudTrail, AWS X-Ray, AWS Usage and Billing Report, AWS Management Console | Google StackDriver, Monitoring, Logging, Error Reporting, Trace, Debugger | – | Azure portal, Azure Monitor, Azure Application Insights, Azure Billing API, Log Analytics |
| Cloud advisor | Trusted Advisor | Google Cloud Platform Security | – | Azure Advisor |
| Administration | AWS Application Discovery Service, Amazon EC2 Systems Manager, AWS Personal Health Dashboard, Third Party | – | – | Azure Log Analytics in Operations Management Suite; Microsoft Operations Management Suite – Automation and Control functionalities, Azure Resource Health, Azure Storage Explorer |
| DEVELOPER TOOLS | ||||
| Simple Email Service (SES) | – | SendGrid | – | |
| Workflow | Simple Workflow Service (SWF) | Cloud Dataproc Workflow Templates | Business Rules | Logic Apps, Azure Automation |
| Scheduling | – | – | Workload Scheduler | Azure Scheduler |
| Media transcoding | Elastic Transcoder, Elemental MediaConvert, Elemental MediaLive | – | – | Media Services |
| Messaging | Simple Queue Service (SQS) | Google Cloud Pub/Sub | Compose for RabbitMQ | Azure Queue Storage, Service Bus Queues, Topics, Relays |
| API Management | API Gateway, Elastic Beanstalk, CodeDeploy, CodeCommit, CodePipeline, AWS Developer Tools | Google Cloud Endpoints | API Connect | API Management, Web Apps, API Apps, Cloud Services, Visual Studio Team Services, Azure Developer Tools, Power Apps |
| App testing | AWS Device Farm | Cloud Test Lab | – | Azure DevTest Labs (backend), Xamarin Test Cloud (frontend) |
| DevOps | AWS CodeBuild, AWS Cloud9, AWS Code Star, AWS CodeCommit, AWS CodePipeline, AWS CodeDeploy, AWS X-Ray | Cloud Source Repositories | Active Deploy, Continuous Delivery, Delivery Pipeline, Globalization Pipeline, Track & Plan | Visual Studio Team Services |
| App customer payment service | Amazon Flexible Payment Service and Amazon Dev Pay | – | – | – |
| Game development (Cloud based tools) | GameLift, Lumberyard | – | – | Visual Studio |
| Predefined templates | AWS Quick Start | Instance Templates | Lifecycle project templates | Azure Quickstart templates |
| Backend process logic | AWS Step Functions | App Engine | IBM Cloud Functions | Logic Apps |
| Programmatic access | Command Line Interface | Cloud Shell | – | Azure Command Line Interface (CLI), Azure PowerShell |
| ENTERPRISE INTEGRATION | ||||
| Content management in cloud | – | Google Sites, Google Docs | IBM FileNet | SharePoint Online |
| Enterprise app integration | – | Google App Engine | IBM WebSphere | Logic Apps |
| Commercial PaaS – IaaS- DBaaS framework | – | – | IBM Cloud Private | Azure Stack |
| Enterprise application services | – | Google Enterprise Search | IBM offers Microsoft Consulting services for Dynamics 365, SharePoint and Office 365. | Dynamics 365 |
AWS vs Microsoft Azure vs Google Cloud Platform vs IBM: The public cloud prices’ comparison back to top
With the maturing of cloud computing, the prices of instances from cloud providers are also witnessing good reductions.
AWS cloud pricing reductions back to top
In addition to reducing prices on a regular basis, AWS also gives options to customers for optimizing their use of AWS. Reserved instances allow Amazon EC2 users for obtaining discounts when compared to on-demand pricing, in addition to capacity reservation when utilized in an Availability Zone.
The price cuts are so frequent that AWS has a blog category dedicated to price reduction!
As per the latest announcement by AWS, effective December 1, 2017 the prices have been reduced for On-Demand and Reserved Instances in Asia Pacific (Mumbai) region as follows:
M4 – Up to 15%.
T2 – Up to 15%.
R4 – Up to 15%.
C4 – Up to 10%.
In May 2017, AWS announced its 61st price reduction. A no upfront payment option with a 1-year term for Standard RIs that was offered previously was changed to a No Upfront payment option with a 3-year term for C4, M4, R4, I3, P2, X1, and T2 Standard Reserved Instances.
Below were the average reductions for No Upfront Reserved Instances and Convertible Reserved Instances for Linux in different representative regions, respectively:
| US East (Northern Virginia) | US West (Oregon) | EU (Ireland) | Asia Pacific (Tokyo) | Asia Pacific (Singapore) | |
| C4 | -11% | -11% | -10% | -10% | -9% |
| M4 | -16% | -16% | -16% | -16% | -17% |
| R4 | -10% | -10% | -10% | -10% | -10% |
| US East (Northern Virginia) | US West (Oregon) | EU (Ireland) | Asia Pacific (Tokyo) | Asia Pacific (Singapore) | |
| C4 | -13% | -13% | -5% | -5% | -11% |
| M4 | -19% | -19% | -17% | -15% | -21% |
| R4 | -15% | -15% | -15% | -15% | -15% |
The prices for M4 Linux instances were lowered by up to 7%.
Moreover, AWS now offers per-second billing for EC2 and other services, instead of per-hour billing to make the cloud billing more flexible.
Azure cloud pricing reductions back to top
In addition to reducing prices on a regular basis, AWS also gives options to customers for optimizing their use of AWS. Reserved instances allow Amazon EC2 users for obtaining discounts when compared to on-demand pricing, in addition to capacity reservation when utilized in an Availability Zone.
The price cuts are so frequent that AWS has a blog category dedicated to price reduction!
In order to offer competitive pricing, Microsoft also has been lowering prices on a frequent basis. Microsoft has a price match promise according to which, it has a commitment to match Amazon Web Services prices for commodity services such as compute, storage and bandwidth.
In November 2017, Microsoft made Azure Reserved VM Instances (RIs) generally available on one or three-year term basis, claiming that customers can get up to 72% cost savings over pay-as-you-go pricing.
In May 2017, prices of Dv2 Promo VMs were lowered by up to 7% for Linux VMs and by up
to 5% for Windows VMs. The price reduction in a few representative regions was as follows:
| Region | Linux | Windows |
| West US | -7.0% | -5.0% |
| East US | -7.0% | -5.0% |
| Canada Central | -6.5% | -4.0% |
| West Europe | -6.5% | -5.0% |
| North Europe | -6.5% | -4.0% |
| UK South | -7.0% | -4.0% |
| Southeast Asia | -6.0% | -4.5% |
| Japan East | -7.0% | -4.5% |
| Australia East | -7.0% | -5.0% |
| Central India | -6.5% | -4.0% |
| Korea Central | -7.0% | -4.0% |
| Brazil South | -7.0% | -5.0% |
The above price reductions came barely three months after the reductions in February, 2017, when prices of both virtual machines and storage were reduced. Compute optimized instances – F Series were reduced by 24% and General purpose instances – A1 Basic by up to 61%.
The table below shows VM price reductions in UK South.
| Azure VMs | Price reductions (Linux VM) | Price reductions (Windows VM) |
| F1 to F16 | -23%-23% | -18% |
| A1 Basic | -42% | -51% |
Azure also offers billing per-second on container instances, for saving money and providing more transparency in billing.
Google cloud pricing reductions back to top
Google Cloud Platform is the cheapest option with it being 60% less expensive for compute as compared to other cloud services for various workloads, with no amount to be paid upfront. It has dropped its prices 3 times in last three years.
It provides per-second billing discounts, sustained usage discounts (SUD) and Committed Use Discount (CUD) to the customers. Custom machine types help customers save up to 50% by matching the needed machine, eliminating over-provisioning and excess payment.
Google has publicly committed to passing along to customers any future price reductions Google achieves through technology-driven advancements in density, scale, power, and cooling. What Google provides is on-demand, real-time pricing. – ESG Labs Whitepaper
In November 2017, Google reduced the price of NVIDIA Tesla GPUs linked to on-demand Google Compute Engine VMs by up to 36%. Lower priced GPUs, along with Custom VM shapes and Sustained Usage Discounts, provide an additional 30% off of instance pricing, allowing customers to run parallel compute tasks on high performance GPUs. Preemptible Local SSDs were also reduced in price by 40 percent as compared to on-demand Local SSDs.
In August 2017, Google announced price cuts on Local solid state disks (SSDs) attached to on-demand Google Compute Engine virtual machines. Lower prices for Local SSDs that are used with Preemptible VM instances were also introduced and were made up to 71% cheaper than before.
Google Compute Engine had provided per second billing from the beginning, but updated its billing model in 2013 to bill instances on per-minute usage. Instances running 10 minutes or less are charged for 10 minutes usage. Following first 10 minutes, per-minute basis usage charges are applicable.
IBM cloud pricing reductions back to top
With the increase in competition, trust in cloud and cloud -native deployment, the market is getting more mature with time, leading to price cuts spiraling to other services linked to VMs, like storage, Database etc.
While last few years saw the leading giants introducing price cuts on storage as it became the next front for competition to grab the bigger cloud market share, experts from 451 Research predict price cuts in relational databases to be the next competitive arena for them.
IBM pioneered this concept, and in March 2017, cut the price of its object storage, with Google, Microsoft and AWS quickly following suit. IBM’s Cloud Object Storage Flex (Flex), works on a “pay as you use” model of storage tiers and potentially lowers the price by 53 percent as compared to AWS S3 IA and 75 percent as compared to Azure GRS Cool Tier.
This leads to an overall reduction in the price of the cloud instance.
Given below are the pricing of AWS, Azure, IBM and Google instances as on January 2017.
| AWS | |||||
| Name | vCPU | Memory | Storage | Amt/month | |
| t2.micro | 1 | 1.0 | 50 GB | INR 805.02 | |
| t2.small | 1 | 2.0 | 100 GB | INR 1,653.50 | |
| t2.medium | 2 | 4.0 | 150 GB | INR 3,161.09 | |
| t2.large | 2 | 8.0 | 200 GB | INR 5,811.46 | |
| t2.xlarge | 4 | 16.0 | 250 GB | INR 10,747.39 | |
| t2.2xlarge | 8 | 32.0 | 300 GB | INR 20,254.46 | |
| m4.large | 2 | 8.0 | 100 GB | INR 5,349.12 | |
| m4.xlarge | 4 | 16.0 | 150 GB | INR 10,552.32 | |
| m4.2xlarge | 8 | 32.0 | 200 GB | INR 20,593.92 | |
| m4.4xlarge | 16 | 64.0 | 250 GB | INR 40,312.32 | |
| c4.large | 2 | 3.7 | 50 GB | INR 4,753.92 | |
| c4.xlarge | 4 | 7.5 | 100 GB | INR 9,726.72 | |
| c4.2xlarge | 8 | 15.0 | 150 GB | INR 19,307.52 | |
| c4.4xlarge | 16 | 30.0 | 200 GB | INR 38,104.32 | |
| Azure | |||||
| Name | CORE | RAM | STORAGE | Amt/month | |
| A1 | 1 | 1.75 GiB | 40 GiB | INR 1,451.48 | |
| A2 | 2 | 3.50 GiB | 60 GiB | INR 4,644.72 | |
| A3 | 4 | 7.00 GiB | 120 GiB | INR 11,224.73 | |
| A4 | 8 | 14.00 GiB | 240 GiB | INR 22,449.46 | |
| A1 v2 | 1 | 2.00 GiB | 10 GiB | INR 2,273.98 | |
| A2 v2 | 2 | 4.00 GiB | 20 GiB | INR 4,741.49 | |
| A4 v2 | 4 | 8.00 GiB | 40 GiB | INR 9,966.79 | |
| A8 v2 | 8 | 16.00 GiB | 80 GiB | INR 20,949.61 | |
| A2m v2 | 2 | 16.00 GiB | 20 GiB | INR 7,644.43 | |
| A4m v2 | 4 | 32.00 GiB | 40 GiB | INR 16,111.36 | |
| A8m v2 | 8 | 64.00 GiB | 80 GiB | INR 33,819.34 | |
| IBM | |||||
| NAME | VCPU | RAM | FIRST DISK | Amt/month | |
| C1.1x1x25 | 1 | 1 GB | 25 GB (SAN) | INR 1,937.28 | |
| C1.1x1x100 | 1 | 1 GB | 100 GB (SAN) | INR 2,727.68 | |
| C1.2x2x25 | 2 | 2 GB | 25 GB (SAN) | INR 3,832.96 | |
| C1.2x2x100 | 2 | 2 GB | 100 GB (SAN) | INR 4,623.36 | |
| C1.4x4x25 | 4 | 4 GB | 25 GB (SAN) | INR 7,680.00 | |
| C1.4x4x100 | 4 | 4 GB | 100 GB (SAN) | INR 8,470.40 | |
| C1.8x8x25 | 8 | 8 GB | 25 GB (SAN) | INR 15,104.00 | |
| C1.8x8x100 | 8 | 8 GB | 100 GB (SAN) | INR 15,894.40 | |
| C1.16x16x25 | 16 | 16 GB | 25 GB (SAN) | INR 29,184.00 | |
| C1.16x16x100 | 16 | 16 GB | 100 GB (SAN) | INR 29,974.40 | |
| C1.32x32x25 | 32 | 32 GB | 25 GB (SAN) | INR 55,040.00 | |
| C1.32x32x100 | 32 | 32 GB | 100 GB (SAN) | INR 55,830.40 | |
| Machine type | Virtual CPUs | Memory | Hard disc | Price (INR) | |
| n1-standard-1 | 1 | 3.75GB | 30 GB | INR 1,865.60 | |
| n1-standard-2 | 2 | 7.5GB | 30 GB | INR 3,731.20 | |
| n1-standard-4 | 4 | 15GB | 30 GB | INR 7,462.40 | |
| n1-standard-8 | 8 | 30GB | 30 GB | INR 14,925.44 | |
| n1-standard-16 | 16 | 60GB | 30 GB | INR 29,850.24 | |
| n1-standard-32 | 32 | 120GB | 30 GB | INR 59,700.48 | |
| n1-standard-64 | 64 | 240GB | 30 GB | INR 119,400.96 | |
| n1-highmem-2 | 2 | 13GB | 30 GB | INR 4,646.40 | |
| n1-highmem-4 | 4 | 26GB | 30 GB | INR 9,292.80 | |
| n1-highmem-8 | 8 | 52GB | 30 GB | INR 18,585.60 | |
| n1-highcpu-2 | 2 | 1.80GB | 30 GB | INR 2,782.72 | |
| n1-highcpu-4 | 4 | 3.60GB | 30 GB | INR 5,565.44 | |
| n1-highcpu-8 | 8 | 7.20GB | 30 GB | INR 11,131.52 | |
Got anything that you would like to add, add in the comments section.
Source:https://www.gartner.com/newsroom/id/3815165
Author Bio
Jyotsana Gupta
Jyotsana Gupta - the content and communication head, is an engineer by education and a writer at heart. In technical writing for 6 years, she makes complex topics interesting to general audience. She loves going on long drives in her spare time.