Intermediate

AI Model Distribution

Distribute model artifacts globally using geo-replicated container registries, CDN-backed object storage, and efficient transfer protocols.

Distribution Strategies

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Container Registry Replication

Replicate container images with models baked in across multiple registry regions. ECR, GCR, and ACR all support cross-region replication.

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CDN-Backed Object Storage

Store model files in S3/GCS with CloudFront/Cloud CDN in front. Models are cached at 400+ edge locations worldwide.

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OCI Artifact Distribution

Package models as OCI artifacts and distribute through container registries. Leverages existing registry infrastructure and layer deduplication.

CloudFront Distribution for Models

Terraform - CloudFront for Model Artifacts
resource "aws_cloudfront_distribution" "model_cdn" {
  origin {
    domain_name = aws_s3_bucket.models.bucket_regional_domain_name
    origin_id   = "model-origin"
    s3_origin_config {
      origin_access_identity = aws_cloudfront_origin_access_identity.oai.cloudfront_access_identity_path
    }
  }

  default_cache_behavior {
    allowed_methods        = ["GET", "HEAD"]
    cached_methods         = ["GET", "HEAD"]
    target_origin_id       = "model-origin"
    viewer_protocol_policy = "redirect-to-https"
    compress               = true
    default_ttl            = 86400   # 24 hours
    max_ttl                = 604800  # 7 days
  }
}

Layer Deduplication

When distributing models as container images, layer deduplication is key. Structure your Dockerfile so the ML framework layer is at the bottom (rarely changes) and the model weights layer is at the top (changes with each version). This means only the model layer needs to be transferred on updates.

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Best practice: Pre-warm CDN caches in your primary serving regions by triggering model downloads immediately after publishing a new version. Do not wait for the first user request to populate the cache, as that first request would pay the full origin download latency.