What is cloud computing?
The definition of cloud computing is the system of computer resources, infrastructure, computing power, and data storage that are available on-demand without user involvement. The technical aspects of the service are fully managed by the provider. The data is made accessible to multiple users via an online service. To access the information, a user needs to log in to a personal account.
The trust of the number of businesses in cloud service is rapidly increasing. We are looking at the future where the majority of companies will be using cloud providers regularly.
Why cloud computing?
Paying for used services: One of the defining qualities of cloud storage is that you only pay for occupied space, computing power, used traffic, and other resources when you were using them.
Scalability: When the business is at initial development stages, business owners can acquire limited storage space, and upgrade the subscription once the company has expanded.
Global accessibility: Cloud services can be used anytime and anywhere. As soon as the user has access to the account, it’s possible to reach the storage, edit settings, manage data, etc.
Simplicity: Cloud providers take responsibility for setting up and maintaining the infrastructure. Business owners only need to subscribe to the service and transfer payment.
Secure infrastructure: Cloud providers offer safe infrastructure, hundreds of customization instruments, versatile security, and access settings.
The major players in this market consist of Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP). Clearly, these three top cloud companies hold a commanding lead in the infrastructure as a service (IaaS) and platform as a service (PaaS) markets.
Writing about the percentage they share on the market, for AWS it is around 52%, Microsoft Azure has about 21%, while the Google Cloud Platform consists of 16%.
Each of the leading vendors has particular strengths and weaknesses that make them a good choice for certain projects – there is no “one size fits all” cloud solution.
AWS is a go-to Cloud infrastructure for enterprises. Its resources are responsible for processing multiple real-time requests, handling fluctuating user loads, and scaling to different geographical markets. The platform is predominantly geared towards big teams and ambitious platforms.
Microsoft Azure specializes in supporting software as a service, retail businesses, and IoT. The infrastructure has multiple tools for creating, managing, and setting up sensors. It also offers powerful tools for real-time data analytics, machine learning, and insight processing.
Google Cloud stands out with its program for startups Companies registered in accelerators, or venture funds can get a special offer for using Google Cloud infrastructure. This way, Google paves the way to becoming a leading startup Cloud. On top of that, the platform offers one of the best AI tools on the market.
While selecting a cloud platform for your business, some criteria must be measured up as reliability, scalability, standardization, and flexibility.
How do they fare against each other?
AWS Service Overview
An innovator of online commerce, it stands to reason that Amazon would develop a robust cloud computing platform for the enterprise. The vast global framework and disbursement of Amazon Web Service is what the entire platform is built upon. The service is divided between regions, availability zones (AZ’s), and what are called edge locations. Altogether, AWS has 22 regions located around the world, 14 AZ’s, and 114 edge locations.
The regions cover a geographic area such as a state or country, and the AZ’s are data centers within regions. The availability zones are located as far as possible from each other within their region to ensure that there are no lapses in service if one AZ goes down due to a natural or other types of widespread disaster. Edge zones are caches that act in a similar manner to content delivery networks (CDN’s) by caching web content nearer to the location of the user for faster delivery and response times
This type of infrastructure allows data delivery to deploy faster and on a global scale without affecting the availability of service or performance. AWS supports all operating systems and generally ranks as the top IaaS platform for availability, reliable performance, and the number of applications.
What kind of services will you find through AWS? So far, there are 18,000 distinct services and counting.
Developer, engagement, and management tools
Machine learning and predictive analytics
Databases and storage solutions
Business productivity tools
Azure Service Overview
Known as a solid, integrated platform for companies that already rely on Windows-based standardization, Microsoft Azure has overcome some obstacles to compete head-to-head with AWS. One surprising feature is its Linux-friendliness as it relates to the virtual guest operating systems and compatibility with Linux container platforms.
The strength of Azure was always as a provider of infrastructure-as-a-service (IaaS), Azure also comes with built-in and ready-to-run server apps that support a range of languages, including .NET, Java, PHP, Node.js, and Python. The platform is available in 54 regions around the world, with services that are designed to increase productivity while deploying the most current technology. It’s also one of the easiest enterprise clouds when it comes to configuring and operation.
With Azure, you’ll enjoy services like:
Big data and predictive analytics
Game and app development
Scalable data warehousing
Google Cloud Service Overview
As far as IaaS providers go, Google Cloud Platform is the relative newcomer. It supports several generations of Linux in addition to Windows Server versions up to 2016. As of 2018, it had expanded to 21 regions that are divided into a minimum of three zones each. This gives it a shorter reach than the other two providers, but Google is attempting to make up for the lack of range in other ways.
For one thing, GCP is an innovator in undersea server deployment, with a unique cabling system that begins in Guam and connects with servers in Australia, the South Pacific, Asia, Japan, and the US mainland. Data centers are being added so quickly, there is no current reliable count.
All of the functionality is operable through a new console that was designed with ease of use in mind, and it’s simple to set up and configure.
Data management and storage
SMB business analytics and AI
Productivity and workload management tools
Features and services
At their core AWS, Microsoft Azure, and Google Cloud Platform offer largely similar basic capabilities around flexible compute, storage and networking. They all share the common elements of a public cloud: self-service and instant provisioning, autoscaling, plus security, compliance, and identity management features.
All three vendors have launched services and tools targeted at cutting edge technology areas like the Internet of Things (IoT) and serverless computing (Lambda for AWS, Functions with Azure, and Google), while customers can tap either cloud to variously build a mobile app or even create a high-performance computing environment depending on their needs.
Machine learning has also been a booming area in the great cloud computing arms race as of late.
AWS launched SageMaker in 2017 as a way to simplify the adoption of machine learning by bringing together a hosted environment for Jupyter notebooks with built-in model management, automated spin-up of training environments using EC2 instances, and HTTPS endpoints for hosting capabilities with Amazon S3. The vendor also has a broad set of off-the-shelf machine learning services for use cases like image recognition (AWS Rekognition), text to speech deep learning models (Polly), and the engine that powers Alexa (Lex).
Microsoft's Azure Machine Learning allows developers to write, test and deploy algorithms, as well as access a marketplace for off-the-shelf APIs.
Google offers a one-stop-shop AI platform, which helps machine learning engineers build and deploy models based on its popular open-source TensorFlow deep learning library.
The recent buzz around containers is catered for as well, with all three providers offering managed services around popular container services like Kubernetes.
Compute, storage, databases, and networking
For compute, AWS's main offering is its EC2 instances, which can be tailored with a large number of options. It also provides related services such as Elastic Beanstalk for app deployment, the EC2 Container Service, ECS for Kubernetes (EKS), AWS Lambda, and Autoscaling.
Meanwhile, Azure's compute offering is centered around its Virtual Machines (VMs), with other tools such as Cloud Services and Resource Manager to help deploy applications on the cloud, and its Azure Autoscaling service.
Google's scalable Compute Engine delivers VMs in Google's data centers. They are quick to boot, come with persistent disk storage, promise consistent performance, and are highly customizable depending on the needs of the customer.
All three providers support relational databases – that's Azure SQL Database, Amazon Relational Database Service, Redshift, and Google Cloud SQL – as well as NoSQL databases with Azure DocumentDB, Amazon DynamoDB, and Google Bigtable.
So what's the conclusion?
A high-profile user base may not be the main reason for choosing your cloud provider, but it can help more cautious organizations understand how the public cloud is benefiting others in their sector. This is clearly a strong point of AWS But if most of your business operations run on Microsoft products, Azure might work better for you. Businesses that need less reach and more innovation might prefer the Google Cloud Platform.