Cloud hosting was initially released as a buzzword, and it was not until we realized it was something that we needed a few years later. The online world is growing faster than ever. So many businesses have different ways of using the cloud to store mass data or else to power and host an online business or application. Cloud hosting has been popularized by large companies such as Google, Amazon, Microsoft, and Facebook, but small-medium scale businesses can also benefit from this technology. Cloud hosting is an exciting prospect at all levels of development. Amazon Web Services, Google Cloud, and Microsoft Azure offer enterprise users cost-effective cloud storage and computing platforms. But which of those three is the best choice? “Pick a cloud” is a loaded question. It depends not only on your requirements but also on how technically savvy you are and how much time you want to spend on deployment issues. Let’s try and figure it out.
AWS, Google Cloud, and Microsoft Azure are very similar in terms of the product they offer
Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure all offer infrastructure as a service (IaaS). The infrastructure provided by these cloud vendors is designed to host other services, which can be commercial or open-source. An example of an IaaS offering would be storage via object storage. This means that the infrastructure does not offer any application or service for users to access directly, e.g., Amazon S3 vs. EC2. On the other hand, a product development environment can include infrastructure examples such as local control over network configuration, OS software packages, etc., and specific services offered for development purposes, e.g., GitHub Enterprise vs. AWS CodeStar which are open source.
While AWS, GCP, and Azure all offer infrastructure as a service (IaaS) in the cloud, they also provide software for product development teams to help develop and deploy their products. For example, AWS CodeStar offers infrastructure and software services to help you build/deploy your product faster than AWS infrastructures such as Iaas and Paas, e.g., EC2 instances or S3 storage, etc. However, AWS CodeStar is currently only available via invitation at this point.
Google Cloud Platform (GCP) provides Google App Engine, developing web applications and mobile apps with pre-packaged infrastructure for Python, PHP, Java, and Go programming languages. You can also deploy your infrastructure via Google Compute Engine.
Microsoft Azure offers infrastructure as a service IaaS and platform as a service (PaaS). In addition, Microsoft Visual Studio Team Services provides a product development environment for teams to collaborate on building applications that run on the cloud.
AWS, Google Cloud Platform, and Microsoft Azure have very similar services to offer developers/teams highly relevant for their product development needs. The only essential factor of differentiation at this point is pricing. As people migrate more workloads to the cloud from traditional data centers, they will need an intuitive way to manage costs caused by moving resources from one provider to another. This can become cumbersome due to different ways infrastructure can be provisioned during migration (e.g., infrastructure as a service (IaaS) vs. platform as a service (PaaS), etc.).
AWS vs. Azure vs. Google Cloud: Service offerings, Performance, and Reliability
AWS, Google Cloud, and Microsoft Azure are three cloud computing providers that enable developers to build applications. These service offerings come with different performance, reliability, and availability. There is no “best” cloud provider as the decision should be made based on the needs of an application or business. Service offerings can be compared by examining their pricing models, features, performance characteristics, including pay-as-you-go costs and operational expenditures (OpEx). Performance can further be examined by testing components included in these service offerings, such as storage throughput speed and response time for virtual machines (VMs) running web servers through load tests.
AWS vs. Azure vs Google Cloud: Load Balancing
AWS load balancer service comes with Elastic Load Balancing (ELB). ELB load balances incoming application traffic across EC2 instances running in an Auto Scaling group or a fleet of homogenous instances. It supports IPv4 and IPv6 load balancing, load balancing rules for HTTP/HTTPS, TCP, and SSL-based load balancers. It also supports automatic recovery from instance failure or termination.
Google Cloud load balancer service is part of the load balancing product family that distributes traffic across multiple locations using anycast routing. It provides a load distribution mechanism for HTTP, HTTPS, TCP, and UDP applications. With an automatic load-balancing feature, you can manage your services efficiently by distributing incoming application traffic among healthy VM instances in different locations while maximizing the availability, performance, and scale of your services. In addition, it is integrated with Compute Engine to serve static content directly from global network edge points of presence (PoPs) without going through Compute Engine VM instances.
Microsoft Azure load balancer distributes incoming application traffic across multiple virtual machines in a load-balanced set. You can load balance network traffic to your cloud services( web apps, VMs, and cloud services) by configuring load balancing rules for HTTP/HTTPS and TCP-based load balancers. It supports Layer 4 load balancing with default settings, but you can also configure it for Layer 7 load balancing (using URL maps and backend pools).
AWS vs. Azure vs. Google Cloud: Pricing
Below is a comparison of the pricing models of Amazon Web Service, Microsoft Azure, and Google Cloud Platform based on the machine type they offer:
AWS vs. Azure vs. Google Cloud: Growth Rate and Market Shares
The latest Gartner report says that Microsoft’s Azure cloud performed better than its competitors with US$17.7 billion (50% revenue growth) in commercial-cloud revenue as per the fiscal earnings report. While AWS reported US$13.5 billion in cloud business revenue for the quarter (revenue grew 32%), Google Cloud had a modest US$4.05 billion.
AWS vs. Azure vs. Google Cloud: Pros and Cons
Amazon Web Services, or AWS, is the leading cloud services provider. It offers nearly 200 different managed services and has a worldwide infrastructure of data centers capable of scaling as needed. The most significant advantages of using AWS are its enterprise readiness and comprehensive security. However, AWS’s cost structure can be challenging to understand because it traditionally charges by the hour, and its pricing changes monthly.
Charging consumers for services and software over the Internet, Microsoft entered the cloud market by taking its on-premise services and running them via Azure. Integrating Azure with other popular applications by most organizations, Microsoft also provides significant discounts for service contracts. But Azure requires high maintenance and experts to operate at total efficiency, leading to dissatisfaction in some users.
Google Cloud is Amazon Web Services’ main competitor in offering cloud services. Google developed Kubernetes, a standardized way to manage containerized application components. As a result, Google’s hosting services often compete with Amazon Web Services in the cloud platform market. Google Cloud Platform has a few notable advantages, but it also has disadvantages. Google does not have a traditional relationship with organizational customers, but it is quickly expanding its offerings and footprint of global data centers.
Take Away
Because Amazon Web Services has long dominated the cloud provider market, other providers have struggled to gain much ground. However, Microsoft Azure and GCP are steadily gaining momentum. Even though Amazon Web Services has a leg up because it was the first player in the cloud game, Microsoft Azure and Google Cloud Platform each have strengths of their own that make sense for specific organizations. For example, Microsoft is highly integrated with many other Microsoft products, and Google offers the best pricing model for companies using Google Search and YouTube. Therefore, it’s more important to choose the best-suited cloud provider per your needs rather than worrying about choosing the “the best” cloud provider.
Thanks for reading. If you’re interested in learning more deploying Machine Learning and AI models on Amazon Web Services, Microsoft Azure, or Google Cloud Platform, please take a look at Excelsior Data Science’s courses and learn Data Science and deployment from scratch.
