This Guidance demonstrates how you can mitigate fraudulent attacks and minimize onboarding friction for legitimate customers through a streamlined facial identity-based authentication user interface.

Architecture Diagram

[Architecture diagram description]

Download the architecture diagram PDF 

Well-Architected Pillars

The AWS Well-Architected Framework helps you understand the pros and cons of the decisions you make when building systems in the cloud. The six pillars of the Framework allow you to learn architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable systems. Using the AWS Well-Architected Tool, available at no charge in the AWS Management Console, you can review your workloads against these best practices by answering a set of questions for each pillar.

The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.

  • The guidance doesn’t include any code artifacts. You can automate development pipelines using AWS Cloud Development Kit (AWS CDK) v2, AWS CloudFormation, and Terraform to enable fast iteration and consistent deployments. Observability is built in to the recommended services with process level metrics, logs, and dashboards. Extend these mechanisms to your needs, and create alarms in Amazon CloudWatch to inform your on-call team on any issues.

    Read the Operational Excellence whitepaper 
  • The serverless backend is protected with AWS Identity and Access Management (IAM)-based authentication for secure validation of the user’s guest identity. You can also deploy Amazon Cognito or another trusted identity provider (IdP) to protect client-server communication. You can define a VPC interface endpoint to securely access Amazon Rekognition and Amazon Textract by keeping all the traffic private in your VPC. The backend Amazon Step Functions state machine can be configured to only have access to the services they need by using restricted execution role and trust policies between services. You can extend the security of the backend by introducing AWS WAF, and you can secure your frontend application further with more fine-grained traffic filtering for unwanted traffic.

    Read the Security whitepaper 
  • By using serverless technologies, all the components are highly available. All components scale automatically because the limits for the Amazon Rekognition and Amazon Textract are configured to your scaling needs. To further increase reliability, consider implementing a disaster recovery plan for your solution by initiating cross-region failover using Amazon Route 53 for the whole infrastructure.

    Read the Reliability whitepaper 
  • By using serverless technologies, you only provision the exact resources you use. To maximize the performance of Amazon Rekognition, test with multiple media types. For improved performance for clients, deploy Amazon Rekognition and Amazon Textract in a multi-region architecture and consider implementing Route 53 routing policy to improve the end user experience.

    Read the Performance Efficiency whitepaper 
  • By using serverless technologies and automatically scaling Amazon Rekognition and Amazon Textract, you only pay for the resources you use. To further optimize cost, perform a content validation before sending to Amazon Rekognition and Amazon Textract. You can get visibility of the cost of the services using AWS Budgets to track your spending and get alerts when you exceed your budget.

    Read the Cost Optimization whitepaper 
  • By using managed and serverless services, you can minimize the environmental impact of the backend services. A critical component for sustainability is to maximize the usage of the AWS Rekognition and Amazon Textract services, as covered in the Performance Efficiency and Cost Optimization pillars.

    Read the Sustainability whitepaper 

Implementation Resources

The sample code is a starting point. It is industry validated, prescriptive but not definitive, and a peek under the hood to help you begin.

AWS Machine Learning

Accelerate your identity verification projects using AWS Amplify and Amazon Rekognition sample implementations

This blog post demonstrates how you can use Amazon Rekognition, along with other AWS services, to implement identity verification.


The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.

References to third-party services or organizations in this Guidance do not imply an endorsement, sponsorship, or affiliation between Amazon or AWS and the third party. Guidance from AWS is a technical starting point, and you can customize your integration with third-party services when you deploy the architecture.

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