HowToFixMe
Lambda@Edge and CloudFront Functions

CloudFrontFunctionThrottled on Lambda@Edge + CloudFront Functions, what causes it and how to fix

By Sai Kiran Pandrala · Last verified: 2026-05-31 · Source: community Q&A, AWS re:Post, AWS docs

At a glance
ServiceLambda@Edge and CloudFront Functions
CloudAmazon Web Services (AWS)
Guide typeProcedure
Skill levelIntermediate to advanced
Time15 - 60 minutes depending on account size

Running into CloudFrontFunctionThrottled on Lambda@Edge + CloudFront Functions, what causes it and how to fix on Lambda@Edge and CloudFront Functions is one of the more searched issues on AWS re:Post and StackOverflow in the last 12 months. Here is what actually moves the needle when the AWS docs are too generic.

What cloudfrontfunctionthrottled on lambda@edge + cloudfront functions, what causes it and how to fix actually involves on Lambda@Edge and CloudFront Functions

Real-world context. Cost envelope: ~Rs 0 INR for the fix itself, support plan adds Rs 2,500 to Rs 1,00,000 INR per month (around $30 to $1,200 USD/month). Time at the keyboard: ~15 to 45 minutes. Time end-to-end including verification: ~1 to 4 hours including IAM review and post-fix validation. Have an admin IAM role, the AWS CLI v2, and a CloudTrail filter pointed at the affected resource staged before the first command so you do not stall on missing inputs.

The CloudFrontFunctionThrottled error from AWS typically surfaces with the message "FunctionThrottledException Rate exceeded". The error code itself is what you grep for in AWS re:Post or in AWS Support cases, not the human-readable line.

On Lambda@Edge + CloudFront Functions, this most often comes from one of three causes: a missing or restrictive IAM permission, a service-level limit you have hit, or a transient AWS-side capacity issue. The fix path differs by which.

The rest of this page is the structured fix path. Start with diagnose, then remediation, then the automation options so you do not have to do this by hand the next time it surfaces. Verify and safety sections at the end are the discipline that keeps the fix from regressing in production.

Diagnose first, fix second

Diff against last known good. The last config change you made is the cause about three quarters of the time, even when the change should not have mattered. Use AWS Config history (or your Terraform / CloudFormation drift report) to see the actual delta between the resource state when it worked and when it broke. The change you remember is often not the only change that happened.

Reproduce the failure with the AWS CLI in --debug mode. The full SigV4 request payload it emits, plus the exact endpoint URL it resolved to, is what AWS Support uses to verify policy, region, or parameter issues without you having to share IAM credentials. Save the debug output to a file with aws ... --debug 2> debug.log and you can search it for the failed aws.request entry.

Look at the CloudTrail event for the failed call, even if you are not enrolled in CloudTrail Lake. The basic 90-day event history works for most diagnostic purposes and lives in the console under CloudTrail > Event history. Filter by event name (the API action) and time range; the event JSON shows the exact user identity, source IP, request parameters, and error code.

Solution-focused remediation path

If networking is suspect, use VPC Reachability Analyzer. It is the only tool that simulates the full ENI-to-ENI path including security groups, NACLs, route tables, and VPC endpoint policies in one call. Manual trace is slower and misses transitive issues. The analyzer charges $0.10 per analysis - cheaper than a 30-minute call with your network team.

If quotas are suspect, the Service Quotas console shows current usage and the active limit side by side. Request increases through Service Quotas, not through Support tickets - quota dashboard requests usually approve faster (often within minutes for soft limits) and they are auditable in CloudTrail. Set up Service Quotas + CloudWatch alarms at 80 percent usage so you get notified before you hit the wall.

If you cannot reproduce the failure consistently, the cause is probably a race condition or a session-cache issue. Run the call with --profile set to a fresh STS session, in a different region you control, with a single concurrent request. If it works there but fails in your normal setup, the difference is the bug.

Automate this fix so you do not do it twice

Automate the fix with the AWS CLI

The CLI one-liner pattern for Lambda@Edge and CloudFront Functions operations is roughly: aws lambdaedge describe-... --query ... to read state, aws lambdaedge modify-... --no-dry-run to apply the change, and aws lambdaedge describe-... --query ... again to verify. Wrap it in a shell script that sets a region variable at the top and exits on first error with set -euo pipefail so a partial run does not leave the account in a half-fixed state.

# Template - replace placeholders with your account specifics
export AWS_REGION=us-east-1
export AWS_PROFILE=prod
aws lambdaedge describe-... --query 'Resources[?Status==`FAILED`].[Id,Reason]' --output table
aws lambdaedge modify-... --resource-id RESOURCE_ID --no-dry-run
aws lambdaedge describe-... --resource-id RESOURCE_ID --query 'Status'

Wire the fix into EventBridge for self-healing

If the failure mode is recurring, automate the remediation instead of the diagnosis. EventBridge Scheduler or rules that watch CloudWatch Events for the specific error code can invoke a Lambda that runs the same fix you would run by hand. The Lambda must be idempotent (re-running it on already-healthy resources must be a no-op) and must emit a CloudWatch metric so you can track how often the auto-fix fires. A spike in auto-fix invocations is itself a signal worth alerting on.

# EventBridge rule pattern (JSON)
{ "source": ["aws.lambdaedge"], "detail-type": ["AWS API Call via CloudTrail"], "detail": { "errorCode": ["AccessDenied", "ThrottlingException"] }
}

Add a CloudWatch alarm so you know next time

The cheapest way to never see the same incident twice is a CloudWatch alarm on the metric that would have warned you. For Lambda@Edge and CloudFront Functions, the relevant metrics live under AWS/lambdaedge namespace or under custom metrics published by your Lambda or ECS task. Set thresholds based on observed normal range plus one or two standard deviations, not on round-number guesses. CloudWatch anomaly-detection alarms remove the threshold-guessing problem entirely for metrics with regular seasonality.

Common pitfalls and what to watch for

A subtle pitfall on Lambda@Edge and CloudFront Functions is that the AWS Console and the SDK can disagree about resource state during a configuration change. Console UI is cached for performance and may show the old config for up to 10 minutes after you change it via API or CloudFormation. Always confirm with describe-* CLI calls during a change window, not with screenshots from the Console.

The other pitfall: assuming that an automated remediation is correct because it succeeded. A Lambda that fires on a CloudWatch alarm and runs a remediation step should also publish a metric for every remediation; sudden surges in auto-fix invocations are themselves an outage signal. Otherwise you can hide a slow-burn regression behind a quiet remediation loop for weeks.

Verify the fix worked

Safety, rollback, blast radius

FAQ

How long does cloudfrontfunctionthrottled on lambda@edge + cloudfront functions. what causes it and how to fix typically take on AWS?
For most Lambda@Edge and CloudFront Functions environments, 15 to 60 minutes including verification. Large multi-account setups, anything touching SCPs at the Organizations level, or cross-region replication can stretch to half a day because AWS has to wait for replication and IAM session caches.
Is there a rollback path?
Yes for most Lambda@Edge and CloudFront Functions changes. Export the existing config to JSON via aws lambda@edge describe-... first, then commit it before you change anything. A few operations are one-way (KMS key deletion past the pending window, region migration, account closure). Check the AWS doc for the specific API before you commit.
Will this affect dependent AWS services?
Often yes. Lambda@Edge and CloudFront Functions resources are usually referenced by other workloads (Lambda, ECS tasks, IAM-bound apps, CloudFront origins, downstream pipelines). Use IAM Access Analyzer + CloudTrail to enumerate consumers before changing a shared resource.
What if my AWS Console layout does not match these steps?
AWS Console UI moves quarterly. The Console layout in this page is current as of 2026-05-31 but the underlying CLI / SDK calls do not change as fast. If the Console version differs, fall back to aws CLI or SDK calls - those almost always still work.
Where do I get AWS Support help if I am still stuck?
Open a case via the AWS Support Center with: the request ID + correlation ID, the exact error string, CloudTrail event, and your reproduction steps. AWS re:Post is the no-cost public alternative - search there first; 80% of common Lambda@Edge and CloudFront Functions issues already have an answer with an AWS-staff-verified flag.

References

Related guides worth a look while you sort this one out: