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Guidance for Building an Advertising Data Lake for Publishers on AWS

Overview

This Guidance helps publishers monetize their assets effectively and create a foundation for broader internal and external data collaboration. The architecture diagram shows how to build a data product that logs data sources, consolidates them in a data lake, and follows a data lifecycle management process. This data product supports yield optimization, ad-hoc queries, and reporting. 

How it works

These technical details feature an architecture diagram to illustrate how to effectively use this solution. The architecture diagram shows the key components and their interactions, providing an overview of the architecture's structure and functionality step-by-step.

Download the architecture diagram

Well-Architected Pillars

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.

To support observability, every service in this Guidance publishes metrics to Amazon CloudWatch , through which you can configure dashboards and alarms. We also recommend that you establish “lessons learned” sessions, retrospectives, and a feedback process in your organization to analyze and resolve potential issues.  

Read the Operational Excellence whitepaper 

IAM policies use least-privilege access so that every policy is restrictive to the specific resource and operation. The data at rest in the Amazon S3 bucket is encrypted using AWS Key Management Service (AWS KMS) keys. The data in transit is encrypted and transferred over HTTPS. 

All of the Amazon S3 buckets are blocked from public access. AWS managed services access the short-term analytical data storage hosted in Amazon EKS through a VPC endpoint. This prevents traffic from traversing the open internet and being subject to that environment.

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You can back up Kinesis Data Streams to Amazon S3 and store static content in Amazon S3 . Amazon Redshift periodically takes snapshots of the cluster. By default, Amazon Redshift takes a snapshot about every eight hours or following every 5 GB per node of data changes (whichever comes first). For the short-term analytical storage, Amazon EKS on AWS Fargate offers the easiest path to a resilient data plane. Fargate runs each pod in an isolated compute environment. Each pod running on Fargate gets its own worker node. Fargate automatically scales the data plane as Kubernetes scales pods. You can scale both the data plane and your workload by using the horizontal pod autoscaler.

Read the Reliability whitepaper 

Using serverless technologies, you only provision the exact resources you use. The serverless architecture diagram reduces the amount of underlying infrastructure you need to manage, allowing you to focus on solving your business needs. Each microservice can be scaled according to its own transactions per second (TPS) requirements.

Read the Performance Efficiency whitepaper 

You should scope real-time data ingestion to use Kinesis Data Streams provisioned capacity mode. Provisioned capacity mode is best suited for predictable application traffic, application with traffic that is consistent or ramps gradually, or applications where you can forecast capacity requirements to control costs.  

When AWS Glue performs data transformations, you pay only for infrastructure during the time that processing occurs. Additionally, you can use a tenant isolation model and resource tagging to automate cost usage alerts and measure costs specific to each tenant, application module, and service.

Read the Cost Optimization whitepaper 

This Guidance uses purpose-built data stores for specific workloads which minimizes the amount of provisioned resources. For example, Amazon S3 , a low latency analytical data storage service, provides historical data lake storage and only stores the latest information that is needed for operational queries.  

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Disclaimer

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.