Amazon Web Services (AWS) Reviews, Ratings & Features 2026 | Gartner Peer Insights

Generative AI (GenAI) Infrastructure providers are infrastructure vendors (such as cloud platforms and hardware manufacturers) that offer underlying technology, tools and hardware that other companies and developers use to build and deploy specific generative AI applications in production. Generative AI refers to technologies that can generate new derived versions of content, strategies, designs and methods by learning from large repositories of original source content. These providers offer scalable, reliable and cost-effective solutions for generative AI projects, which can be complex and expensive to train and deploy. Generative AI infrastructure providers focus on research and developing the foundational AI techniques, while application developers focus on building products using those foundational technologies. Please note that this market is based on Beta research and is continuously evolving. We will be making changes as and when there are new updates.

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Generative AI Infrastructure Providers (Transitioning to Cloud AI Infrastructure)

Amazon Web Services

Amazon Web Services (AWS)

Engineer

I have had a fantastic experience using AWS because the extensive infrastructure marketplace allows me to quickly use pre-configured tools from third-party vendors. The platform integrates beautifully with my day-to-day code management systems, while the granular admin control makes setting precise team permissions straightforward. Additionally, setting up a secure network configuration is highly intuitive, and the built-in monitoring features give me continuous, real-time visibility into the exact performance of all my applications.

<50M USD

50M - 250M USD

250M - 500M USD

500M - 1B USD

1B - 3B USD

Gov't/PS/ED <5,000 Employees

3B - 10B USD

30B + USD

10B - 30B USD

Gov't/PS/ED 5,000 - 50,000 Employees

Data Scientist

AWS provides a robust and scalable Gen AI infrastructure through services like Bedrock and KB. Managed access to foundation models removes the overhead of model hosting and reduces the amount of boiler plate code. KB enables the easy RAG implementation with minimal setup. 

Lead Cloud Infrastructure Specialist

Reliability & Uptime: My experience has been generally strong in production-like and lower environments when we followed vendor-approved patterns (Service Catalog provisioning, VPC/private network connectivity, IAM least privilege, and managed service defaults).  Bedrock, QuickSight, and Sagemaker AI components were stable once the network configurations and role boundaries were correct.

Support Quality: AWS and internal platform support were effective for blocker-level issues, especially around service enablement and permissions.  The best outcomes came when tickets included the exact account/region, role ARN, and reproduction steps.

Integration Success: Integration was successful but not "plug-and-play".  The biggest wins came from standardizing deployment through Service Catalog for Amazon Q Business, Bedrock AgentCore runtime/gateway targets, and SageMaker domain setup.  This reduced drift and made troubleshooting repeatable.

Business Impact: We moved from ad hoc experimentation to repeatable implementation patterns for RAF, analytics copilot, and ingestion automation.  Time-to-first-solution improved after guardrails and templates were in place.

Scenario 1: In QuickSight + Snowflake integration, we use VPC connectivity and service accounts (not user SSO) for asynchronous dataset refresh.  We confirmed that RBAC and masking policies were enforced at query time in Direct Query mode, and we handled SPICE data-visibility constraints by creating role-specific datasets.

Scenario 2: In Bedrock AgentCore deployment, we implemented admin controls such as: Runtime + Gateway + Memory with Service Catalog and IAM controls.  Initial friction came from auth/config nuances and network pathing, but once standardized, the deployment became reproducible for additional teams.

Google

Microsoft

Cloudflare

Oracle

Lambda

Alibaba Cloud

NVIDIA

Dell Technologies

CoreWeave

Other...

Crusoe

Domino Data Lab

OVHcloud

Nebius

Huawei

Tencent Cloud

Scaleway

Vultr

Nscale

Amazon Web Services (AWS), established in 2006, is focused on providing essential infrastructure services to businesses globally in the form of cloud computing. The key advantage offered through cloud computing, particularly via AWS, is its capacity to shift fixed infrastructure expenses into flexible costs. Businesses have been able to forgo extensive planning and procurement of servers and other Information Technology (IT) resources, owing to AWS. AWS seeks to provide businesses with prompt and cost-effective access to resources using Amazon's expertise and economies of scale, as and when their business requires. Currently, AWS offers a robust, scalable, economic infrastructure platform on the cloud powering an extensive array of businesses worldwide. It operates across numerous industries with data center locations in various parts of the globe including U.S., Europe, Singapore, and Japan.

Launched in 2006, Amazon Web Services (AWS) began exposing key infrastructure services to businesses in the form of web services -- now widely known as cloud computing. The ultimate benefit of cloud computing, and AWS, is the ability to leverage a new business model and turn capital infrastructure expenses into variable costs. Businesses no longer need to plan and procure servers and other IT resources weeks or months in advance. Using AWS, businesses can take advantage of Amazon's expertise and economies of scale to access resources when their business needs them, delivering results faster and at a lower cost. Today, Amazon Web Services provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world. With data center locations in the U.S., Europe, Singapore, and Japan, customers across all industries are taking advantage of our low cost, elastic, open and flexible, secure platform.

Reviews

Ratings Overview

Overall experience with

Favorable Review

Consistent integration achieved despite operational hurdles and regional feature limits

Critical Review

AWS Bedrock and KB Simplify RAG Implementation and Model Hosting Overhead

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