# Amazon Web Services

Amazon Web Services (AWS) is Amazon's cloud computing subsidiary, offering on-demand infrastructure, platform, and AI services on a pay-as-you-go basis. It provides compute, storage, networking, and machine learning tools, including Bedrock, SageMaker, and Trainium chips, to individuals, companies, and governments worldwide.

Amazon Web Services, Inc. (AWS) is a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments on a metered, pay-as-you-go basis. Clients often use this in combination with autoscaling, a process that allows a client to use more computing in times of high application usage, and then scale down to reduce costs when there is less traffic. These cloud computing web services provide various services related to networking, compute, storage, middleware, IoT, and other processing capacity, as well as software tools via AWS server farms, freeing clients from managing, scaling, and patching hardware and operating systems.

One of the foundational services is Amazon Elastic Compute Cloud (EC2), which allows users to have at their disposal a virtual cluster of computers with extremely high availability, interactable over the Internet via REST APIs, a CLI, or the AWS console. AWS's virtual computers emulate most attributes of a real computer, including hardware central processing units (CPUs) and graphics processing units (GPUs) for processing; local/RAM memory; hard-disk (HDD)/SSD storage; a choice of operating systems; networking; and pre-loaded application software such as web servers, databases, and customer relationship management (CRM). AWS services are delivered via a network of server farms located worldwide, with fees based on usage, hardware, operating system, software, and networking features chosen by the subscriber.

## Cloud Infrastructure and Market Position

AWS operates from many global geographical regions, including nine in North America. Amazon markets AWS as a way to obtain large-scale computing capacity more quickly and cheaply than building a physical server farm. All services are billed based on usage, but each service measures usage in varying ways. As of 2023 Q1, AWS holds 31% market share for cloud infrastructure, while the next two competitors, Microsoft Azure and Google Cloud, have 25% and 11% respectively, according to Synergy Research Group. AWS was the first cloud provider to build infrastructure specifically for U.S. government security and compliance requirements (2011; launched AWS GovCloud), accredited to support classified workloads (2014; launched AWS Top Secret), and achieve accreditation across all U.S. government data classifications (2017; launched AWS Secret).

## AI and Machine Learning Services

AWS offers a comprehensive suite of [AI](https://www.wikiprompt.org/wiki/artificial-intelligence) and [machine learning](https://www.wikiprompt.org/wiki/machine-learning) services. Amazon SageMaker is a fully managed platform that enables developers and data scientists to build, train, and deploy machine learning models at scale. It covers the entire workflow, from data preparation and feature engineering to model training, tuning, and deployment. SageMaker supports popular frameworks like TensorFlow and PyTorch, and integrates with other AWS services for data storage and processing.

Amazon Bedrock is a managed service that provides access to foundation models from leading AI companies, including [Anthropic](https://www.wikiprompt.org/wiki/anthropic) and [OpenAI](https://www.wikiprompt.org/wiki/openai), through a single API. It allows users to build generative AI applications without managing the underlying infrastructure. Bedrock offers models for text generation, chat, and other tasks, with features for customization and fine-tuning using private data.

For specialized hardware, AWS developed [AWS Trainium](https://www.wikiprompt.org/wiki/aws-trainium) chips, custom silicon designed for training machine learning models. These chips are optimized for high performance and cost efficiency, offering an alternative to GPUs for certain workloads. AWS also provides Inferentia chips for inference, and both are available through EC2 instances, enabling customers to run AI workloads with lower latency and cost.

## Compute and Storage Services

Amazon Elastic Compute Cloud (EC2) is the core compute service, offering resizable compute capacity in the cloud. Users can launch virtual machines with various instance types, including those optimized for compute, memory, storage, or GPU-intensive tasks. EC2 supports multiple operating systems and allows for autoscaling to handle variable traffic. AWS also offers AWS Lambda, a serverless compute service that runs code in response to events, such as HTTP requests, without provisioning or managing servers. Lambda supports multiple programming languages and scales automatically.

Amazon Simple Storage Service (Amazon S3) is a scalable object storage service designed for data durability and availability. It is used for backup, archiving, and data lakes, and integrates with other AWS services for analytics and machine learning. S3 offers storage classes for different access patterns, from frequent to infrequent access, and supports lifecycle policies to automate data management.

## Networking and Database Offerings

AWS provides a range of networking services, including Amazon Virtual Private Cloud (VPC) for isolated network environments, Elastic Load Balancing for distributing traffic, and Amazon Route 53 for DNS management. These services enable customers to build secure and scalable network architectures. For databases, AWS offers Amazon Relational Database Service (RDS) for managed relational databases like MySQL, PostgreSQL, and Oracle, as well as Amazon DynamoDB, a NoSQL database for high-performance applications. Amazon Aurora, a MySQL and PostgreSQL-compatible database, provides high availability and performance.

## History and Founding

The genesis of AWS came in the early 2000s. After building Merchant.com, Amazon's e-commerce-as-a-service platform for third-party retailers, Amazon pursued service-oriented architecture to scale its engineering operations, led by then CTO Allan Vermeulen. Amazon was frustrated with the speed of its software engineering and implemented recommendations from Matt Round, an engineering leader, including maximizing engineering team autonomy, adopting REST, standardizing infrastructure, removing gate-keeping decision-makers, and continuous deployment. Amazon created a shared IT platform so its engineering organizations, which were spending 70% of their time on IT and infrastructure problems, could focus on customer-facing innovation.

In July 2002, Amazon.com Web Services, managed by Colin Bryar, launched its first web services, opening the Amazon.com platform to all developers. Over one hundred applications were built on top of it by 2004, taking Amazon by surprise and convincing them that developers were hungry for more. By summer 2003, Andy Jassy had taken over Bryar's portfolio at Rick Dalzell's behest, after Vermeulen declined the offer. Jassy mapped out the vision for an Internet OS made up of foundational infrastructure primitives. By fall 2003, databases, storage, and compute were identified as the first set of infrastructure pieces to launch. Jeff Barr, an early AWS employee, credits himself, Vermeulen, Jassy, Bezos, and a few others for the idea that evolved into EC2, S3, and RDS. Jassy recalls the idea resulted from brainstorming for about a week with ten of the best technology and product management minds on about ten different Internet applications and the most primitive building blocks required to build them.

## Growth and Expansion

AWS launched its first public service, Amazon S3, in March 2006, followed by EC2 later that year. The services quickly gained traction, and AWS expanded its portfolio with new offerings like Amazon CloudFront for content delivery and Amazon SimpleDB for database services. In 2010, AWS introduced Amazon RDS and Amazon DynamoDB, and by 2012, it had over 200,000 customers. AWS continued to grow, adding regions worldwide and launching services like AWS Lambda in 2014 and Amazon SageMaker in 2017. The company also invested in custom silicon, introducing AWS Graviton processors for general-purpose workloads and Trainium for AI training.

## Enterprise and Government Adoption

AWS has become a dominant player in cloud computing, serving a wide range of customers, from startups to large enterprises and government agencies. Its government cloud offerings, including GovCloud and Top Secret regions, meet strict security and compliance requirements. AWS also provides services for the Internet of Things (IoT), such as AWS IoT Core, and for robotics, with AWS RoboMaker. The company's focus on innovation and customer needs has driven its market leadership, with over 200 products and services as of 2025, including computing, storage, networking, database, analytics, application services, deployment, management, machine learning, mobile, developer tools, and IoT tools.

## Impact and Future Directions

AWS has significantly influenced the cloud computing industry, setting standards for scalability, reliability, and pay-as-you-go pricing. Its AI services, including Bedrock and SageMaker, are central to the adoption of [generative AI](https://www.wikiprompt.org/wiki/generative-ai) in enterprises. The development of custom chips like Trainium positions AWS to offer cost-effective alternatives to traditional GPU-based AI training. As of 2025, AWS continues to expand its global infrastructure and service offerings, focusing on areas like edge computing, machine learning, and sustainability. The company's commitment to innovation and customer-centric design remains a key driver of its success in the competitive cloud market.

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Source: https://www.wikiprompt.org/wiki/amazon-web-services
License: CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/)
Last updated: 2026-09-05T13:21:25.308866+00:00