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AWS Well-Architected design considerations - Scene Intelligence with Rosbag on AWS
Operational excellenceSecurityReliabilityPerformance efficiencyCost optimizationSustainability

AWS Well-Architected design considerations

This solution uses the best practices from the AWS Well-Architected Framework, which helps customers design and operate reliable, secure, efficient, and cost-effective workloads in the cloud.

This section describes how the design principles and best practices of the Well-Architected Framework benefit this solution.

Operational excellence

This section describes how we architected this solution using the principles and best practices of the operational excellence pillar.

  • All Lambda functions send logging output to Amazon CloudWatch.

  • Alarms from AWS services included in this solution are stored in CloudWatch to provide observability into the infrastructure.

  • You can review past runtime outcomes for Amazon MWAA, AWS Batch, and EMR Serverless.

Security

This section describes how we architected this solution using the principles and best practices of the security pillar.

  • All inter-service communications use AWS Identity and Access Management (IAM) roles.

  • All roles used by the solution follow least-privilege access. That is, they only contain the minimum permissions required so that the service can function properly.

  • All S3 buckets have default encryption at rest activated.

  • Access to data storage buckets is logged into a separate bucket.

  • Database metadata is encrypted using AWS Key Management Service (AWS KMS) keys.

Reliability

This section describes how we architected this solution using the principles and best practices of the reliability pillar.

  • The solution uses AWS serverless services wherever possible to ensure high availability and recovery from service failure.

  • All compute processing uses Lambda functions wherever possible.

  • Data is stored in S3 buckets and DynamoDB tables, so it persists in multiple Availability Zones by default.

  • The solution uses Amazon MWAA to orchestrate the workflow and provides the run history and ability to retry the failed process(es) and re-invoke the workflow.

  • All custom code uses AWS Software Development Kit (AWS SDK) and benefits from automatic retries and back-off for API calls.

Performance efficiency

This section describes how we architected this solution using the principles and best practices of the performance efficiency pillar.

  • The solution uses serverless compute and data resources throughout the architecture.

  • You can launch the solution in any Region that supports AWS services used in this solution, such as Amazon MWAA, Lambda, Amazon S3, SageMaker AI, EMR Serverless.

  • The solution is automatically tested and deployed every day. The solution is also reviewed by solution architects and subject matter experts for areas to experiment and improve.

Cost optimization

This section describes how we architected this solution using the principles and best practices of the cost optimization pillar.

  • This solution uses Lambda functions, AWS Batch, EMR Serverless, and SageMaker AI processing jobs for most compute needs.

  • You can choose to run the solution on-demand or at an interval that you choose.

Sustainability

This section describes how we architected this solution using the principles and best practices of the sustainability pillar.

  • This solution uses serverless resources for compute and data storage.

  • Most data storage is maintained in an S3 bucket or DynamoDB table that you can remove easily.