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Amazon Web Services (AWS): Unveiling the Power of the Amazon Cloud

amazon web services

Amazon Web Services or AWS is Amazon's Cloud platform. Find out all you need to know: presentation, history, operation, services, benefits, training... Cloud computing is increasingly used in business, particularly for Data Science and Machine Learning. The most widely used Cloud platform is Amazon Web Services.

What is AWS - Amazon Web Services?

Amazon Web Services (AWS) is a leading cloud provider, part of the Amazon conglomerate renowned for its global e-commerce platform. AWS offers a vast array of cloud services accessible via the internet, enabling users to leverage Amazon’s data center hardware and infrastructure, sparing them the need to procure and run on-site software.

As a pioneer in the cloud industry, AWS holds a dominant market position, with key rivals like Microsoft Azure and Google Cloud Platform. In the second quarter of 2021, AWS recorded a staggering $14.8 billion in net sales revenue, placing it in competition with companies on Forbes’ Global 500 list. AWS contributes a remarkable 13% to Amazon’s total net sales. Explore the cloud revolution with AWS.


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What is the history of Amazon Web Services?

The history of Amazon Web Services, commonly known as AWS, dates back to the year 2000. At that time, Amazon was a simple e-commerce company struggling to find its path to growth. The company had accumulated significant technical debt.

Driven by necessity, Amazon made the strategic decision to create reusable modules for its internal development groups. This allowed the groups to create new features more quickly, as there was no longer a need to reinvent the same things over and over.

Over time, this collection of internal services grew. The idea of profiting from it in the form of a new business gradually took shape.

The Amazon Web Services platform was launched in 2004 and again in 2006 with three publicly priced pay-as-you-go services. The foundations of Cloud Computing were laid.

In the years that followed, AWS had very few competitors and was able to gain ground freely. Thanks to this head start, Amazon remains the market leader in Cloud Computing today. However, Microsoft Azure, Google Cloud, and other competitors have steadily gained market share in recent years.

Who uses Amazon Web Services and why?

You may not be aware, but one in three websites relies on Amazon Web Services. The number of active users on this platform exceeds one million.

The majority of this user base consists of small and medium-sized businesses. However, many well-known companies are AWS customers, including Netflix, Twitch, Hulu, Reddit, and Slack. Large enterprises make up nearly 10% of the total.

Among Amazon Web Services clients, you’ll find tech giants, media networks, banks, food producers, and even governments.

Some large companies spend several million dollars per month on computing resources provided by Amazon EC2.

The largest AWS customer is Netflix, with a budget exceeding $20 million per month. Similarly, Twitch, Linkedin, or Facebook spend over $10 million per month on cloud services.

The use cases for Amazon Web Services or AWS are incredibly diverse. Companies use this cloud platform for web hosting, SaaS applications, media sharing, content delivery, data storage, software development, data analysis, and machine learning, among many others.

The different types of Amazon Web Services

The Amazon Web Services platform encompasses a wide array of highly diversified services. These services can be grouped into major categories.

The various Amazon Web Services enable businesses to build sophisticated applications while enhancing flexibility, scalability, and reliability. Organizations can leverage a multitude of compute power, database storage, content delivery, and many other features.

Storage and databases

For data storage, Amazon Simple Storage Service (S3) is dedicated to object storage. This service allows you to store and retrieve any amount of data or information from any website. The key advantages of S3 are durability and availability. Another strong point is scalability, as you can increase storage resources as needed.

A storage class system allows you to sort data based on how frequently you need to access it, which can lead to cost savings.

S3 is ideal for data storage, backup, software delivery, archiving, web hosting, and applications, as well as for Data Science. The maximum file size allowed is 5 terabytes, making it suitable for processing Big Data.

Storage is provided through a web service interface, and data can be transferred very easily, as S3 is known for its user-friendliness.

Amazon Glacier is dedicated to long-term cold storage, and Amazon Elastic Block Store provides block storage. For managed file storage, Amazon Elastic File System is the preferred choice.

For databases, Amazon Relational Database supports Oracle, SQL Server, PostgreSQL, MySQL, and MariaDB. Amazon Aurora is a high-performance proprietary database directly developed by Amazon.

Similarly, Amazon DynamoDB offers managed NoSQL databases. With Amazon Redshift, Data Analysts can benefit from a Data Warehouse to perform Business Intelligence tasks more efficiently.

Big Data and AI

Many experts use AWS for Big Data and Artificial Intelligence. This is because, in addition to access to powerful servers, this Cloud platform offers numerous dedicated services.

For instance, Elastic MapReduce is a Hadoop framework for processing large volumes of data, and Kinesis provides various tools for streaming data processing and analysis. AWS Glue service allows for data extraction, processing, and loading.

With Amazon Athena, analysts can query data on datasets stored on S3. On the other hand, QuickSight is dedicated to data visualization.

The Amazon AI suite comprises various artificial intelligence tools: Amazon Lex for voice recognition and text chatbots, Amazon Polly for text-to-speech transcription, and Amazon Rekognition for facial recognition and computer vision.

Furthermore, Amazon Machine Images (AMIs) enable developers to create and train AI models with GPUs or optimized compute instances. There are also Deep Learning development frameworks for MXNet and TensorFlow.

Virtual machines

Amazon Web Services Cloud also allows for the creation of virtual machines to develop and deploy applications more quickly. The Amazon Elastic Compute Cloud service, or EC2, allows you to launch as many virtual servers as needed, configure security and networking, and manage storage.

This service eliminates the need to invest in hardware. Additionally, you can increase or decrease the number of virtual servers to handle changes in requirements or traffic spikes. This eliminates the need for capacity planning.

Virtual environments in EC2 are called instances. There are various instance types offering different configurations of CPU, memory, and storage capacity.

EC2 also includes pre-configured templates called Amazon Machine Images (AMIs). These packages contain all the necessary components for the virtual server.

It is also possible to create virtual networks, logically isolated from the rest of the AWS cloud. You can connect them to your network. These are called Virtual Private Clouds (VPCs).

Software development

The AWS Cloud platform encompasses various software development tools. The AWS Command Line Interface integrates Amazon’s proprietary code interface, while AWS Tools for PowerShell enable the management of cloud services from a Windows environment.

The AWS Serverless Application Model can simulate an AWS environment for testing Lambda functions. There are different AWS SDKs for a variety of platforms and programming languages, including Java, PHP, Python, Node.js, Ruby, C++, Android, or iOS.

The Amazon API Gateway allows a team to create, manage, and monitor custom APIs that allow applications to access data or features from backend services. There’s also the Amazon Elastic Transcoder service for media transcoding.

For microservices-based applications, AWS Step Functions visualize workflows. The AWS X-RAY service is used for performance evaluation.

Various services are dedicated to integration and continuous delivery: CodePipeline, CodeBuild, CodeDeploy, and CodeStar. On the other hand, CodeCommit allows you to store code in Git repositories.

Several services are focused on mobile development: AWS Mobile Hub brings together various tools, including the AWS Mobile SDK offering libraries and code samples. You can manage user access to mobile apps with Amazon Cognito and send push notifications with Amazon Pinpoint.

Many video game studios, including Ubisoft, use AWS for development. The platform includes development tools and backend services for deploying or expanding a project. Analytical tools allow developers to better understand their game users, and data can also be hosted on Amazon Web Services servers.

Amazon Sumerian, on the other hand, brings together development tools for virtual and augmented reality applications. Users can create apps without even having to master programming or 3D creation.

Other Amazon Web Services categories

Amazon Elastic Compute Cloud (EC2) provides virtual servers for computing capacity. Businesses can choose the size and capacity of the server that meets their needs, based on their types of workloads and applications. It is a widely used service by organizations in all sectors.

Amazon is also interested in emerging technologies like the Internet of Things (IoT) and offers dedicated cloud services. The AWS IoT service is a backend platform for managing IoT devices and ingesting data into other AWS storage and database services. The AWS IoT Button is a hardware device, and AWS Greengrass brings Amazon server computing capabilities to IoT devices.

Cybersecurity is now a major concern for businesses, and Amazon offers several dedicated services. For example, Amazon Macie protects sensitive data in the cloud using machine learning. Various tools enable encryption and protection against DDoS attacks.

Among other highly popular AWS services are Amazon Chime for video meetings and text discussions, WorkDocs for file storage and sharing, and WorkMail for email and calendar features.

The dozens of AWS services cover all areas of computing. Other categories of services include cloud migration, hybrid cloud, networking, management and monitoring, governance, as well as messaging and notifications.

It is a very comprehensive cloud platform, allowing organizations in all sectors to entirely eliminate on-premises infrastructure and on-site software. That’s why more and more organizations are choosing to migrate to the cloud.

Amazon Web Services infrastructure and technology

AWS infrastructure is separated into “regions.” In total, there are 25 regions spread across six continents. Each region consists of multiple availability zones.

These zones are physical data centers where computers are located. Data centers are geographically separated to limit the risk of a natural disaster causing an outage in an entire region.

The Content Delivery Network (CDN) of AWS consists of 200 edge locations around the world. There are also regions that are not publicly accessible, including two AWS GovCloud regions reserved for the U.S. government and two regions managed by Chinese authorities in accordance with local laws.

AWS’s high-speed optical fiber network connects all availability zones in these different regions. To make this network faster and more reliable, the company has created its own hardware equipment.

The advantages and disadvantages of Amazon Web Services

Compared to its competitors, Amazon Web Services has several advantages. Firstly, its cloud services offering is the most comprehensive and diverse.

In total, this catalog comprises nearly 200 services in 2021 and continues to expand. Improvements and new features are rolled out every week, with customer requests and queries being directly addressed.

Another strength of AWS is the diversity of its services, which cater to almost every use case. You’ll find basic cloud services for storage and computing as well as highly specific domains such as multimedia streaming, robotics, or even quantum computing.

In addition to storage and typical remote data center uses, businesses extensively use AWS for Big Data analysis and Machine Learning to extract value from their data. Many organizations have migrated all their IT operations to AWS and are benefiting from increased agility, efficiency, and reliability.

Downloading your data to AWS Cloud is free, but you will incur charges when extracting data from it. These charges are not very high but are worth mentioning. This is one of the drawbacks of AWS.

Beyond the quality of the platform, one can also lament Amazon’s dominance in the cloud market. Just like in e-commerce, the Seattle giant nearly monopolizes the field and hinders smaller players from entering.

How do I learn to use Amazon Web Services?

To learn how to use AWS, you can choose DataScientest’s training programs. Our various programs allow you to get started with cloud services and prepare for your AWS certifications. These certifications will help you demonstrate your expertise in future interviews.

Our Blended Learning approach combines online learning on a coached platform with collective Masterclasses. You can take these courses as BootCamps or Continuing Education.

At the end of the program, learners receive a certificate from Dauphine-PSL and Les Mines. Among our alumni, 93% found employment immediately.

Don’t waste any more time and discover DataScientest’s training programs!

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