Lambda function layer detach

Detach a specified Lambda layer from a target AWS Lambda function for a configurable duration and reattach it afterwards so you can test how the workload behaves when a shared dependency layer disappe

Lambda function layer detach is an AWS chaos fault that removes a Lambda layer (LAMBDA_FUNCTION_LAYER_ARN) from a target function (FUNCTION_NAME in REGION) for TOTAL_CHAOS_DURATION seconds, then reattaches it. While the layer is detached, code in the function that depends on the layer's libraries, binaries, or assets fails at runtime.

Use this fault to test how a Lambda workload behaves when a shared dependency layer is removed: whether new invocations fail with a clear error, whether monitoring detects the failure, and whether downstream consumers degrade gracefully.

RUN YOUR FIRST EXPERIMENT

If you have not configured the chaos infrastructure yet, go to Quickstart to install the chaos infrastructure and run an experiment end to end.

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Use cases

Run this fault when you want to answer concrete questions like:

• Dependency removal: When the layer disappears, does the function fail fast with a clear "module not found" / "binary missing" error?

• Library auditing: Identify whether the function actually uses libraries provided by the layer (functions that succeed without the layer can drop the dependency).

• Monitoring fidelity: Do CloudWatch alarms on Lambda Errors fire within the SLA?

• Downstream impact: Do consumers downstream of the Lambda function degrade gracefully when invocations start failing?

• Recovery: When the layer is reattached, do new invocations succeed without manual intervention?

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Prerequisites

• Kubernetes version: 1.21 or later for the chaos infrastructure cluster. Go to What's supported to confirm distribution support.

• Target Lambda function: FUNCTION_NAME exists in REGION and currently has LAMBDA_FUNCTION_LAYER_ARN attached.

• Layer ARN: LAMBDA_FUNCTION_LAYER_ARN is the full ARN including the version (for example arn:aws:lambda:us-east-1:123456789012:layer:my-layer:5).

• AWS credentials available: Either an AWS credentials file uploaded as a File Secret in Harness Secret Manager (see Authentication below) or an IAM role for service accounts (IRSA) bound to the chaos infrastructure service account.

• IAM permissions granted: The credentials or role include the permissions listed below.

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Supported environments

Platform	Support status
AWS Lambda (zip package)	Supported
AWS Lambda (container image)	Not supported (container images do not use layers)
AWS regions	Supported in every commercial region; pass the region in REGION

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Permissions required

The IAM principal that the chaos pod uses (the credentials mounted from the Harness Secret Manager file secret, the IRSA role on the chaos service account, or the role assumed via ASSUME_ROLE_ARN) needs the following AWS actions.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "lambda:GetFunction",
        "lambda:GetFunctionConfiguration",
        "lambda:UpdateFunctionConfiguration",
        "lambda:GetLayerVersion"
      ],
      "Resource": "*"
    }
  ]
}

Go to common policy for all AWS faults to use a single superset IAM policy across every AWS fault.

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Authentication

The fault supports three credential delivery models. Pick one based on how your chaos infrastructure is deployed.

Method	When to use it	How to configure
Harness Secret Manager file secret	Chaos infrastructure runs outside EKS, or you want explicit static credentials	Upload the AWS credentials file as a File Secret in Harness Secret Manager and reference its identifier via AWS_AUTHENTICATION_SECRET
IAM Roles for Service Accounts (IRSA)	Chaos infrastructure runs in EKS and uses an OIDC-bound service account	No tunable changes; the chaos pod inherits the role automatically. Go to AWS IAM integration to set it up
Assume role	The fault needs to act in a different account or with elevated permissions	Set ASSUME_ROLE_ARN to the role ARN; the chaos pod assumes the role on top of its base credentials

When using the Harness Secret Manager method, the contents of the File Secret should be the AWS credentials file in the standard ~/.aws/credentials format:

[default]
aws_access_key_id = REPLACE_WITH_ACCESS_KEY_ID
aws_secret_access_key = REPLACE_WITH_SECRET_ACCESS_KEY

Upload this file as a File Secret in Harness Secret Manager (Project Setup → Secrets → New File Secret), and pass the secret identifier in AWS_AUTHENTICATION_SECRET when configuring the fault.

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Fault tunables

Configure the following fault parameters when you add Lambda function layer detach to an experiment in Chaos Studio. Defaults are shown for reference.

Required parameters

Tunable	Description	Default
FUNCTION_NAME	Name of the target Lambda function.	(required)
REGION	AWS region where the Lambda function is deployed.	(required)
LAMBDA_FUNCTION_LAYER_ARN	Full ARN (including version) of the layer to detach.	(required)

Chaos parameters

Tunable	Description	Default
TOTAL_CHAOS_DURATION	Duration of the fault in seconds.	30
CHAOS_INTERVAL	Delay in seconds between successive iterations when running for more than one cycle.	30
RAMP_TIME	Wait period in seconds before and after the fault. Go to ramp time to read how it is applied.	0

Authentication

Tunable	Description	Default
ASSUME_ROLE_ARN	ARN of an IAM role to assume on top of the base credentials. Leave empty to use the base credentials directly.	""
AWS_AUTHENTICATION_SECRET	Identifier of the File Secret in Harness Secret Manager that contains the AWS credentials file. Not required when using IRSA.	""

Tunables that apply to every fault are documented in common tunables for all faults.

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Fault execution in brief

Reads the current layer list on FUNCTION_NAME, removes LAMBDA_FUNCTION_LAYER_ARN from the configuration, waits for TOTAL_CHAOS_DURATION seconds, then restores the original layer list.

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Expected behavior during fault execution

• New invocations of the function no longer have access to the layer's contents.

• Code paths that depend on the layer fail with ModuleNotFoundError, missing-binary errors, or other runtime errors.

• CloudWatch metric Errors rises if the workload exercises the affected code paths during the chaos window.

• Warm containers initialized before the detach continue to use the layer until they are recycled by Lambda.

WHEN THE FAULT ENDS

The chaos pod restores the original layer configuration. New invocations have the layer available again.

Signals to watch

Attach resilience probes to assert each layer:

• Lambda errors: Use a Prometheus probe on aws_lambda_errors_sum and assert it rises during the chaos window.

• Function logs: Inspect CloudWatch Logs for module/import errors.

• Downstream availability: Use an HTTP probe on the user-visible endpoint.

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Verify the fault execution effect

While the experiment is running, confirm the layer is detached and then reattached:

1. Inspect function configuration.

   aws lambda get-function-configuration \
     --region <region> \
     --function-name <name> \
     --query "Layers[].Arn"

   During the fault the listed layers should not include LAMBDA_FUNCTION_LAYER_ARN. After recovery the original layer should be back.

2. Invoke the function and inspect the response.

   aws lambda invoke --region <region> --function-name <name> /tmp/out.json
   cat /tmp/out.json

   Invocations that exercise layer-provided code should return an error during the chaos window.

3. Check CloudWatch Logs.

   aws logs tail --region <region> /aws/lambda/<name> --since 5m

   Look for missing-module or missing-binary errors.

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Recovery and cleanup

• End of duration: The chaos pod restores the original layer configuration on the function.

• Abort the experiment: Stopping the experiment from Chaos Studio also triggers the restore call.

• Manual recovery: If the fault exits before restore, run aws lambda update-function-configuration --function-name <name> --layers <layer-arn-list> --region <region> with the original layer list (recorded in the chaos pod logs).

• Workload recovery: Containers initialized during the chaos window are replaced on next cold start; warm containers may continue to operate normally until then.

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Limitations

• Single layer per experiment: The fault detaches one layer ARN per experiment. Run multiple experiments in sequence to detach multiple layers.

• Container images unaffected: Container-image-based Lambda functions do not use layers; this fault has no effect on them.

• Layer version specificity: LAMBDA_FUNCTION_LAYER_ARN must include the version (the ARN ends with :<version>). A bare layer ARN without a version is not valid.

• Cross-region targeting: A single experiment targets one region (the value of REGION).

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Troubleshooting

Lambda function layer detach fails with AccessDeniedException in Harness Chaos Engineering

The credentials supplied to the chaos pod do not have the required Lambda permissions. Confirm the IAM policy attached to the user, role, or IRSA service account includes lambda:GetFunction, lambda:GetFunctionConfiguration, lambda:UpdateFunctionConfiguration, and lambda:GetLayerVersion.

LAMBDA_FUNCTION_LAYER_ARN not found on the function

The layer ARN must currently be attached to FUNCTION_NAME. Run 'aws lambda get-function-configuration --function-name --region --query Layers' to list the attached layers and confirm the ARN (including version) matches exactly.

Function continues to work normally without the layer

The function may not actually use the libraries provided by the layer, in which case removing it has no effect. Use the experiment as a deliberate audit: if no invocation fails, the layer is a candidate for removal in normal deployments to reduce package size.

Layer not restored after the chaos window

If the restore call failed, the layer may stay detached. Run 'aws lambda update-function-configuration --function-name --layers --region ' with the original layer list recorded in the chaos pod logs to restore.

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Related faults

• Lambda update function memory: Test the function under tightened memory.

• Lambda update function timeout: Test the function under tightened timeout.

• Lambda update role permission: Strip IAM permissions instead of a layer.

• Common AWS fault tunables: Shared environment variables for AWS faults.