Amazon Web Services (AWS)
Enterprise cloud infrastructure, data and AI platform provider.
Available information varies by company and source.
Profile record updated:
Company facts
- Official name
- Amazon Web Services, Inc.
- Entity type
- BUSINESS_UNIT
- Founded
- 2002
- Headquarters
- United States
- Company size
- >5,000
- Market role
- B2B SaaS Provider
- Official website
- aws.amazon.com
What Amazon Web Services (AWS) does
AWS operates a hyperscale cloud platform model. It invests heavily in global infrastructure, software abstraction layers and managed services, then monetises that capacity across a broad product catalogue. Customers consume compute, storage, databases, AI services and related tooling on demand, while AWS increases account value through cross-sell into higher-level managed services, support, marketplace transactions and consulting. The model creates value by replacing customer-owned infrastructure with elastic shared infrastructure, integrated platform services and operational expertise.
Category differentiation
Amazon Web Services is Amazon’s enterprise cloud infrastructure and platform business, not Amazon’s consumer retail marketplace. It is broader than a single hosting product, covering infrastructure, data, AI, software marketplace and cloud services.
Strategic context
AI-supported assessment from the existing company research; distinguish interpretation from sourced facts.
Amazon Web Services, Inc. is Amazon’s cloud infrastructure business. It sells on-demand compute, storage, database, AI, analytics, software marketplace access, support and professional services to enterprises, developers, public sector organisations and software vendors. Its core value proposition is outsourced infrastructure and platform capability delivered as managed cloud services rather than on-premise hardware and self-operated stacks. AWS generates revenue primarily from usage-based consumption of cloud services, supplemented by longer-term committed-spend arrangements, enterprise support plans, marketplace-related commercial flows, and consulting-led implementation work. Its customers are businesses and institutions building, migrating, operating and scaling digital workloads, data platforms, applications and AI systems on AWS infrastructure.
Company news briefing
Briefing updated:
AWS has deepened its hardware and database partnerships to scale enterprise AI capabilities, headlined by a deal to integrate two million NVIDIA GPUs through 2028 alongside the general availability of Oracle AI Database@AWS across 22 regions. Furthermore, AWS has expanded Amazon Bedrock offerings with OpenAI’s Daybreak cybersecurity models and welcomed Vespa.ai into the AWS AI Competency programme. These developments reinforce the cloud provider's commitment to high-performance AI infrastructure and specialized enterprise workloads.
Business model & monetisation
AWS monetises through consumption-based pricing for compute, storage, databases, AI and networking, with bills tied to resource usage such as capacity, runtime, storage volume and data transfer. It also uses committed-use pricing via reserved capacity and savings plans, discounted spot capacity for spare infrastructure, tiered pricing for storage and other services, subscription and contractual support tiers, professional service fees for migration and transformation work, and marketplace-related commercial participation tied to third-party software procurement and deployment.
- Core infrastructure services
- Pay-per-Use
- Committed-use and enterprise cloud contracts
- Software Subscription
- Professional services
- Service Fee
- Support plans
- Service Fee
- Marketplace commerce
- Percentage Take-Rate
Products & capabilities
No products with linked sources are available in this view.
Products & market categories
Recent recorded signals
Dates refer to the source publication. Older entries are historical context, not evidence of a new event.
AWS Launches 'Built Together' Community Program for Data Centers
Infrastructure · Recorded impact score: 2/5
Amazon Web Services (AWS) has announced new initiatives to counter criticism over its data center expansion in the U.S., including a $1 billion investment over five years for community programs focusing on education, workforce training, energy efficiency, water conservation, and local infrastructure. Additionally, AWS introduced the 'Amazon Data Center Commitment' with pledges on energy, water, transparency, and employment, and has ceased using non-disclosure agreements (NDAs) with government agencies for new projects. CEO Matt Garman addressed data center 'myths', citing that generators run only about 10 hours per year and that water consumption is 0.5% of industrial use, while highlighting over $1 billion in community contributions in the past three years. These actions come amid over 100 proposed moratoriums on data centers across the U.S.
- AWS invested over $1 billion in communities with data centers over five years.
- AWS stopped using nondisclosure agreements with government agencies for new data centers.
Vespa.ai Achieves AWS AI Competency
AI Infrastructure · Recorded impact score: 3/5
Vespa.ai announced it has achieved the Amazon Web Services (AWS) AI Competency in the AI Software category. This designation recognizes Vespa as an AWS Partner that helps customers build, deploy, and operate large-scale AI applications on AWS. The Vespa AI Search Platform combines hybrid retrieval, advanced ranking, machine learning inference, and real-time serving in a single platform, reducing infrastructure complexity while providing low latency and scalability for production AI. Vespa is trusted by organizations including Perplexity, Spotify, and Yahoo, powering billions of queries and recommendations across industries such as information platforms, digital commerce, media and advertising, and life sciences. The recognition validates Vespa's expertise in building production AI search applications on AWS.
- Vespa.ai achieved the AWS AI Competency in the AI Software category.
- The designation recognizes Vespa as an AWS Partner for building and operating large-scale AI applications on AWS.
Startup FinOps: Cloud Cost Optimization Playbook
Infrastructure · Recorded impact score: 2/5
This playbook outlines practical FinOps steps startups can use to reduce cloud spend without major re-architecture. Key recommendations include making spend visible via enforced cost-allocation tags, scheduling non-production environments to sleep, adding caching and CDNs, cleaning up orphaned resources, rightsizing underutilized compute and databases, and buying commitment discounts (Savings Plans / Reserved Instances) for steady-state baseline usage. The guide recommends measuring cost against business units (e.g., cost per user), validating production changes with metrics, and making a lightweight monthly FinOps review a habit. The author cites typical waste at 25–35% of cloud bills and claims many Series A companies can realize 25–40% savings within 90 days by following these practices.
- Industry data cited: idle resources, over-provisioning, and missed commitment discounts account for roughly 25–35% of the average cloud bill.
- Hosting can consume 6–12% of revenue for early-stage companies, making cloud waste a runway risk.
RDS High Availability and Credential Rotation Without Downtime
Infrastructure · Recorded impact score: 2/5
A technical how-to describing an AWS architecture that meets strict recovery and rotation requirements for a PostgreSQL RDS-backed financial application: 1-second RPO, 60-second RTO, and automated credential rotation every 30 days with no application downtime. The recommended design combines Multi-AZ RDS for synchronous standby failover, RDS Proxy to preserve application connections through failover, and AWS Secrets Manager with the AWS-managed rotation Lambda to perform staged credential rotation. The article includes Terraform examples for VPC, IAM, RDS, RDS Proxy, Secrets Manager, and deployment validation steps, plus cost considerations for Multi-AZ, RDS Proxy, and Secrets Manager.
- Use RDS Multi-AZ with a synchronous standby to achieve near-zero RPO (typically under 1 second) and automated failover that usually completes within 60 seconds.
- RDS Proxy maintains application connections and a warm pool of DB connections so application connections remain alive during Multi-AZ failover.
Survey: 50% of Game Developers Fear Job Loss from AI
Game Development Tools & Engines · Recorded impact score: 2/5
Perforce's State of Real-Time Workflows report, produced in partnership with Amazon Web Services (AWS) and surveying more than 600 game-technology practitioners worldwide, finds 50% of developers cite job insecurity as their top AI concern. The report also records rising productivity from AI alongside ethical and creativity worries: 48% flagged ethical concerns and 36% reported reduced creativity. Version control adoption rose to 94% (from 86% in 2025). Game engines are increasingly used outside gaming—55% for film/TV and 32% for VFX—and regional differences show APAC leading AI-driven acceleration (74%) while LATAM reports the highest job-loss fears (83%).
- 50% of game developers cited job insecurity as their top AI concern.
- Perforce's State of Real-Time Workflows report was produced in partnership with Amazon Web Services (AWS) and surveyed more than 600 game technology practitioners worldwide.
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Questions about Amazon Web Services (AWS)
What is Amazon Web Services (AWS)?
AWS is Amazon’s cloud computing business, providing infrastructure, data, AI and managed platform services to organisations.
Who uses Amazon Web Services (AWS)?
Enterprises, developers, public sector bodies, software vendors, IT teams and data teams use AWS to build and run digital workloads.
How does Amazon Web Services (AWS) make money?
AWS makes money mainly from usage-based cloud consumption, plus committed-use plans, support fees, professional services and marketplace-related revenue.
Sources & coverage
This profile uses public, official and technically observable information. Missing information does not prove that a product or relationship does not exist. The list below does not imply that every profile statement has been verified.
18 publicly documented primary sources and citations linked across the market graph.
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