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Inference Results S3 Upload Feature

Overview

The Inference Uploader component automatically uploads inference results (images and metadata) from edge devices to S3 for centralized storage, analysis, and monitoring.

Architecture

Components

  1. Greengrass Component: aws.edgeml.dda.InferenceUploader

    • Platform-independent (works on all architectures)
    • Monitors /aws_dda/inference-results/ directory
    • Uploads images (.jpg, .png) and metadata (.jsonl) to S3
    • Manages local file retention and cleanup

  2. S3 Bucket: dda-inference-results-{account-id}

    • Created in each UseCase Account
    • Lifecycle policies: 30 days → IA, 90 days → delete
    • Encrypted with S3-managed keys
    • Block all public access

  3. IAM Permissions:

    • Devices: Upload permissions via DDAPortalComponentAccessPolicy
    • Portal: Read permissions via DDAPortalAccessRole

Data Flow

Edge Device
  └─> /aws_dda/inference-results/{model-id}/
       ├─> {event-id}.jpg (1.1MB)
       └─> {event-id}.jsonl (1.2KB)
            └─> InferenceUploader Component
                 └─> S3: s3://dda-inference-results-{account}/
                          {usecase-id}/{device-id}/{model-id}/YYYY/MM/DD/
                           ├─> {event-id}.jpg
                           └─> {event-id}.jsonl

Setup Instructions

Step 1: Build and Publish Component (Portal Account)

cd DefectDetectionApplication
./build-inference-uploader.sh

This will:

  • Upload artifacts to s3://dda-component-{region}-{portal-account}/
  • Create component version in Greengrass
  • Tag component as dda-portal:managed=true

Step 2: Deploy Infrastructure (UseCase Account)

cd edge-cv-portal/infrastructure
npm run build
rm -rf cdk.out
cdk deploy EdgeCVPortalStack-UseCaseAccountStack --context usecase_account_id=198226511894

This creates:

  • S3 bucket: dda-inference-results-198226511894
  • IAM permissions for devices to upload
  • IAM permissions for portal to read

Step 3: Provision Shared Components

The InferenceUploader component is automatically provisioned to usecase accounts along with LocalServer:

  1. For New Usecases: Automatically provisioned during onboarding
  2. For Existing Usecases: Use "Update All Usecases" button in portal

Or via API:

POST /api/v1/shared-components/provision
{
  "usecase_id": "your-usecase-id"
}

Step 4: Deploy to Devices

Create a deployment in the portal with:

Required Components:

  • aws.edgeml.dda.LocalServer.{arch} (already required)
  • aws.edgeml.dda.InferenceUploader v1.0.0 (NEW)
  • Model component (e.g., model-cookie-defect-detection-arm64-cpu)

Component Configuration for aws.edgeml.dda.InferenceUploader:

{
  "s3Bucket": "dda-inference-results-198226511894",
  "s3Prefix": "{usecase-id}/{device-id}",
  "uploadIntervalSeconds": 300,
  "batchSize": 100,
  "localRetentionDays": 7,
  "uploadImages": true,
  "uploadMetadata": true,
  "inferenceResultsPath": "/aws_dda/inference-results",
  "awsRegion": "us-east-1"
}

Configuration Options

Parameter Default Description
uploadIntervalSeconds 300 Upload batch interval (5 minutes)
batchSize 100 Max files per batch
localRetentionDays 7 Keep local files for N days after upload
uploadImages true Upload .jpg/.png files
uploadMetadata true Upload .jsonl/.json files
inferenceResultsPath /aws_dda/inference-results Local directory to monitor
s3Bucket (required) Target S3 bucket
s3Prefix (optional) S3 key prefix for organization
awsRegion us-east-1 AWS region

S3 Structure

s3://dda-inference-results-{account}/
  └─> {usecase-id}/
       └─> {device-id}/
            └─> {model-id}/
                 └─> YYYY/MM/DD/
                      ├─> {event-id}.jpg
                      └─> {event-id}.jsonl

Example:

s3://dda-inference-results-198226511894/
  └─> cookie-factory/
       └─> dda_edge_server_2/
            └─> cc3ke9hm/
                 └─> 2026/01/19/
                      ├─> cc3ke9hm-a20e6456a4ed44649c3dc48da1a5a8a7.jpg
                      └─> cc3ke9hm-a20e6456a4ed44649c3dc48da1a5a8a7.jsonl

Metadata Format

Each .jsonl file contains:

{
  "deviceGroundTruthData": [{
    "source-ref": "/aws_dda/inference-results/...",
    "anomaly-label-detected": 1,
    "anomaly-label-detected-metadata": {
      "class-name": "Anomaly",
      "creation-date": "2026-01-19T18:25:51",
      "confidence": 0.9375,
      "type": "groundtruth/image-classification"
    }
  }],
  "eventMetadata": {
    "eventId": "cc3ke9hm-a20e6456...",
    "modelName": "model-cookie-defect-detection-arm64-cpu",
    "modelVersion": "1",
    "inferenceTime": "2026-01-19T18:25:51"
  }
}

Monitoring

Component Logs

View logs in CloudWatch:

/aws/greengrass/UserComponent/{region}/{device-name}/aws.edgeml.dda.InferenceUploader

Upload Status

The component maintains state in:

/aws_dda/.inference_uploader_state.json

This tracks uploaded files to avoid duplicates.

Metrics

Monitor:

  • Upload success/failure rates
  • Batch sizes
  • Local disk usage
  • S3 bucket size

Troubleshooting

No files uploading

  1. Check component is running:

    sudo /aws_dda/greengrass/v2/bin/greengrass-cli component list

  2. Check logs:

    sudo tail -f /aws_dda/greengrass/v2/logs/aws.edgeml.dda.InferenceUploader.log

  3. Verify IAM permissions:

    • GreengrassV2TokenExchangeRole has DDAPortalComponentAccessPolicy attached
    • Policy includes S3 upload permissions

Permission denied errors

Ensure the device's IAM role has:

{
  "Effect": "Allow",
  "Action": [
    "s3:PutObject",
    "s3:PutObjectTagging",
    "s3:GetBucketLocation"
  ],
  "Resource": [
    "arn:aws:s3:::dda-inference-results-{account}",
    "arn:aws:s3:::dda-inference-results-{account}/*"
  ]
}

Files not being cleaned up

Check localRetentionDays configuration. Set to 0 to disable cleanup.

Future Enhancements

  1. Portal UI: Browse and view uploaded inference results
  2. Analytics Dashboard: Visualize inference metrics over time
  3. Alerts: Notify on anomaly detection patterns
  4. Batch Processing: Trigger SageMaker jobs on uploaded data
  5. Compression: Optional gzip compression before upload
  6. Filtering: Upload only anomalies or specific confidence ranges

Related Files

  • Component: DefectDetectionApplication/inference-uploader/
  • Build Script: DefectDetectionApplication/build-inference-uploader.sh
  • Infrastructure: edge-cv-portal/infrastructure/lib/usecase-account-stack.ts
  • Backend: edge-cv-portal/backend/functions/shared_components.py