As engineers, we often spend hours optimizing code, improving prompts, and scaling infrastructure.
But sometimes the biggest production issues come from something much simpler.
A DNS lookup.
Recently, while deploying a serverless AI application to AWS, I encountered an error that completely blocked deployment.
The application hadn't changed.
AWS was healthy.
Permissions were correct.
The deployment package was valid.
Yet every deployment failed.
The error looked like this:
Error:
getaddrinfo EAI_AGAIN serverless-framework-deployments-eu-north-1-xxxxxxxx.s3.eu-north-1.amazonaws.com
At first glance, it looked like an AWS outage.
It wasn't.
This is the story of how a simple DNS resolution issue brought an entire deployment pipeline to a halt—and how we fixed it.
The application was an AI-powered Due Diligence Platform built with:
Deployment flow:
Developer
↓
Serverless Framework
↓
S3 Deployment Bucket
↓
CloudFormation
↓
Lambda Functions
Every deployment package is first uploaded to an S3 bucket created by the Serverless Framework.
Only after the upload succeeds does CloudFormation update the stack.
During deployment, the terminal suddenly returned:
serverless deploy
✖ Error:
getaddrinfo EAI_AGAIN serverless-framework-deployments-eu-north-1-xxxxxxxx.s3.eu-north-1.amazonaws.com
The deployment stopped immediately.
No Lambda updates.
No CloudFormation changes.
Nothing.
The first thing I checked was AWS Service Health.
Everything was operational.
No incidents were reported.
The next suspect was permissions.
I verified:
aws sts get-caller-identity
Response:
{
"Account": "123456789012",
"Arn": "arn:aws:iam::123456789012:user/developer"
}
Credentials were valid.
Permissions were correct.
Still failing.
I upgraded Serverless Framework.
npm install -g serverless
Deployment still failed.
The key clue was:
EAI_AGAIN
This is not an AWS error.
It is a DNS resolution error.
Specifically:
Temporary DNS lookup failure
The operating system could not resolve the S3 endpoint hostname.
The request never reached AWS.
I manually tested DNS resolution:
nslookup google.com
Intermittent failures appeared.
Then:
nslookup s3.eu-north-1.amazonaws.com
The same issue occurred.
This confirmed that the problem existed locally.
Not in AWS.
The machine was using an unstable DNS resolver.
Under heavy network usage, DNS lookups occasionally timed out.
When Serverless Framework attempted to upload artifacts to S3:
Serverless
↓
DNS Lookup
↓
Failure
↓
Deployment Stops
No connection to AWS was ever established.
We switched to reliable public DNS servers.
Linux:
sudo nano /etc/resolv.conf
Added:
nameserver 8.8.8.8
nameserver 1.1.1.1
Then restarted networking:
sudo systemctl restart NetworkManager
After updating DNS:
nslookup s3.eu-north-1.amazonaws.com
Returned instantly.
Deployment succeeded:
serverless deploy
Output:
✔ Service deployed successfully
To avoid future issues, we added several safeguards.
serverless deploy || serverless deploy
Useful for CI/CD jobs when transient network issues occur.
Before deployment:
curl https://s3.eu-north-1.amazonaws.com
If connectivity fails:
Stop deployment
This prevents wasting build minutes on doomed deployments.
Added:
aws sts get-caller-identity
to deployment pipelines.
This immediately detects expired or invalid credentials.
The biggest lesson was simple:
Not every AWS deployment error is actually an AWS problem.
Sometimes:
And the cloud gets blamed.
When deployment issues occur, I now follow this order:
aws sts get-caller-identity
ping google.com
nslookup s3.eu-north-1.amazonaws.com
aws s3 ls
serverless deploy
This process has saved hours of troubleshooting.
As engineers, we often expect complex problems to have complex causes.
This incident reminded me that some of the most disruptive failures originate from the most basic layers of infrastructure.
A single DNS lookup failure stopped an entire deployment pipeline.
The code was correct.
AWS was healthy.
The architecture was sound.
But none of that mattered until the network could resolve a hostname.
Sometimes the fastest fix isn't changing code.
It's understanding where the request actually fails.
Before blaming AWS:
You'll save yourself hours of debugging.