This is a contextual advertising solution with enhanced machine learning (ML) capabilities, designed to reach target audiences without using third party cookies. Contextual advertising enables advertisers to reach an audience based on the content consumed by users. It uses an event-driven serverless architecture based on a highly scalable and cost-optimized design. The architecture enables demand side platforms (DSPs), advertisement publishers and supply side platforms (SSPs) to build a contextual intelligence solution utilizing AWS artificial intelligence (AI) and machine learning services to extract relevant metadata and map it to their own taxonomy or industry-standard taxonomy, which informs the programmatic bids for advertisement publishers, brand safety for advertisers and advertisement creative classification for supply side platforms.
All the services used in the design provide cloud watch metrics that can be used to monitor individual components of the design. Amazon API Gateway and AWS Lambda allow for publishing of new versions through an automated pipeline.
Amazon API Gateway provides a protection layer when invoking category service through an outbound API. All the proposed services support integration with AWS Identity and Access Management (IAM), which can be used to control access to resources and data.
AWS Lambda, Amazon DynamoDB, Amazon S3, Amazon Comprehend and Amazon Rekognition provide high availability within a region. Customers can deploy Amazon SageMaker endpoints in a highly available manner.
The solution requires batch processing for content discovery and content analysis. The performance requirements for batch processing range from minutes to hours; AWS Lambda, Amazon Comprehend and Amazon Rekognition are designed to meet them. Category service requires latency of less than 10 milliseconds (ms). Provisioned Concurrency in AWS Lambda and the HTTP API in Amazon API Gateway can support a latency requirement of less than 10 ms.
This solution uses AWS Lambda to design all compute components of content discovery and content analysis, keeping billing to pay per millisecond. The data store is designed using Amazon DynamoDB and Amazon S3, providing a low total cost of ownership for storing and retrieving data. For content analysis, the solution uses Amazon Comprehend and Amazon Rekognition. These allow customers to pay only when data is processed by the service. The category service uses Amazon API Gateway, reducing API development time and helps customers make sure they only pay when an API is invoked.
The solution uses the scaling behaviors of AWS Lambda and Amazon API Gateway to reduce over-provisioning resources. It uses AWS Managed Services to maximize resource utilization and to reduce the amount of energy needed to run a given workload.
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