On-Demand availability of the computer system resources especially data storage, computing power, and high-performance computing is known as Cloud Computing. The Cloud platforms are the platforms that provide the user with the power of Cloud Computing. There are several Cloud platforms available these days which is also the demand of the hour, namely AWS (Amazon Web Services), GCP (Google Cloud Platforms), Microsoft AZURE, IBM BlueMix, Alibaba Cloud.
Cloud platforms aim at providing shared infrastructure. This increases resource utilization, reduces resource idle time, and thereby reduces the resource cost proportionately. Less idle time of a resource, more sharing and shared cost of the resource.
Major cloud platforms in the industry
With the primary aim of providing IAAS (Infrastructure as a Service), AWS Cloud Platform was started in the year 2006, later the expanded the services to PAAS (Platform as a Service) and SAAS (Software as a Service). They were later followed by Google which founded GCP in the year 2008 and Microsoft founding AZURE in 2010. As per date, Cloud platforms provide a wide range of services apart from the 3 mentioned above such as MBAAS (Mobile Backend as a Service), ServerLESS computing, Function as a Service, all aim to provide cost-effective, efficient, on-demand, easy expansion and scaling experience to the users.
The Cloud infrastructure is available based on the geographical region of the user and several zones under those regions. They basically are the data centers for the data storage and network connections for accessing the applications.
Availability zones and regions
- AWS has 77 Availability Zones within 24 geographic regions around the world, with announced plans for nine more Availability Zones and three more AWS Regions in Indonesia, Japan, and Spain.
- GCP is available in 61 availability zones within 22 geographic regions around the world.
- Azure is available in 60 regions with data-center all around the world. As promised by Microsoft, Azure aims to make it easy to choose the right data center in the right geographical region as per the targeted customer due to increasing concerns about data privacy.
Pros and Cons
- AWS has dominance in the cloud platforms with more than 14 years in the industry and massive scope of operations whereas Azure holds its position in providing strong integrated support for Microsoft and Windows software applications like Windows Server, Office, SQL Server, Sharepoint, Dynamics Active Directory, .Net, and others. On the other hand, GCP proves in its dominance in the scenarios where strong containerization of the application is needed. Google wrote down the standards for Kubernetes which is also offered by Azure and AWS as it is within their services.
- Kubernetes is an open-source platform by Google and is a portable, extensible cluster for containerized applications. It helps in managing containerized workloads as well as services and facilitates both declarative configuration and automation.
- Azure is considered as Enterprise-ready Cloud platform due to its ability to support large windows and Microsoft applications whereas GCP is considered for cloud-native businesses as it provides strong support for analytics, big data. GCP offers high computing services that are good for Machine learning and other domains which require high computing.
- AWS has a great customer support service and a wide set of learning resources due to its popularity and age in the industry. AWS has more mature solutions in terms of technological challenges one faces while using cloud platforms due to it presence in the industry for more than a decade now.
Pricing models by cloud platforms
- All Cloud platforms majorly provide services like storage, computation, and database. But they differ in the pricing and type of services. With new marketing strategy and ideas to reduce the customer bill, cloud platforms provide a varied range of pricing models like pay per use, pay per day, pay per hour, pay per minute and pay per request. The Approach is also known as pay as you go, this ensures less customer billing and more resource utilization and sharing.
- AWS instances can be purchased in following models from On-demand, reserved, and spot. An azure instance can be purchased on-demand and short-termed commitments. For Google cloud, it can be On-demand and sustain use
Services provided by the 3 mentioned cloud platforms and their names.
| Cloud Platforms | Storage Solutions | Database Support | Computer Engine |
| AWS | • Simple Storage Service (S3) • Elastic Block Storage (EBS) • Elastic File System (EFS) • Storage Gateway • Snowball • Snowball Edge • Snowmobile | • Aurora • RDS • DynamoDB • ElastiCache • Redshift • Neptune • Database migration service | • EC2 • Elastic Container Service • Elastic Container Service for Kubernetes • Elastic Container Registry • Lightsail • Batch • Elastic Beanstalk • Fargate • Auto Scaling • Elastic Load Balancing • VMware Cloud on AWS |
| Azure | • Blob Storage • Queue Storage • File Storage • Disk Storage • Data Lake Store | • SQL Database • Database for MySQL • Database for PostgreSQL • Data Warehouse • Server Stretch Database • Cosmos DB • Table Storage • Redis Cache • Data Factory | • Virtual Machines • Virtual Machine Scale Sets • Azure Container Service (AKS) • Container Instances • Batch • Service Fabric • Cloud Services |
| GCP | • Cloud Storage • Persistent Disk • Transfer Appliance • Transfer Service | • Cloud SQL • Cloud Bigtable • Cloud Spanner • Cloud Datastore | • Compute Engine • Kubernetes • Functions • Container Security • Graphics Processing Unit (GPU) • App Engine • Knative |
Further Technical differences
| Technical aspect | AWS | AZURE | GCP |
| Maximum no of processors | 128 | 128 | 96 |
| Managed Data warehouse | Redshift | SQL Warehouse | Big Query |
| Kubernetes | EKS | Kubernetes Service | Kubernetes Engine |
| File Storage | EFS | Azure files | ZFS and Avere |
| Serverless Functions | Lambda functions | Azure functions | Cloud Functions |
| Analytics Service | Amazon Kinesis | Azure stream analytics | Cloud dataflow |
| Search Service | Amazon Cloud Search | Azure Search | Cloud Search |
On one hand, Azure is considered as enterprise-ready with range of geographical regions to choose the datacenter from. Providing regional data privacy and tight bound connecting with windows and Microsoft applications. Then, on the other hand, AWS has great reach and mature services. On one stage, AWS provides mature and experienced support for approximately 172 services and on other GCP provides high computation focused services. AWS has a huge community and market acceptable and notable range of resources to study whereas Azure still lacks in good documentation. Therefore it can only be said that choosing a Cloud platform entirely depends on the requirement of the application one wants to deploy on the cloud.