The load balancer was failing again, and the S3 access logs were a mess. Everyone blamed networking. But the real issue was permissions.
When you run an external load balancer in AWS and connect it to an S3 bucket, read-only roles are your first line of defense. They limit risk, cut down the blast radius, and keep your architecture predictable. Yet, most teams get them wrong. Over-permissive policies creep in. Debugging turns into firefighting.
An external load balancer reading from S3 only needs specific actions: s3:GetObject and maybe s3:ListBucket if you’re indexing objects. Anything else is an open door. The IAM role should attach to the load balancer through an instance profile or task role, never with access keys embedded in code. Keys leak. Roles rotate.
The fastest path to a proper setup starts with the policy:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"s3:GetObject",
"s3:ListBucket"
],
"Resource": [
"arn:aws:s3:::my-example-bucket",
"arn:aws:s3:::my-example-bucket/*"
]
}
]
}
Attach it to a role. Bind the role to the compute resource that runs your load balancer. Test with the AWS CLI before wiring it into production. One clean aws s3 ls s3://my-example-bucket with a role-based credential proves it works without exposing secrets.
External load balancers pulling static content from S3 need speed and security in equal measure. A misstep in permissions slows both. Correct role scoping means your deployment can scale without losing control. Logs stay clean. Costs stay down. Compliance teams stop asking the same questions.
If you want to see a working example where an external load balancer uses an AWS S3 read-only role with zero manual IAM guesswork, try it on hoop.dev. You can spin it up, configure it, and watch it serve content in minutes—no scripts to chase, no policies to debug.