Lambda inject latency
Inject runtime latency into an AWS Lambda function for a configurable duration so you can test how upstream callers and downstream consumers handle slower-than-expected responses, cold-start spikes, a
Lambda inject latency is an AWS chaos fault that adds LAMBDA_LATENCY seconds of delay to every invocation of a target Lambda function (FUNCTION_NAME in REGION) for TOTAL_CHAOS_DURATION seconds. The fault injects a runtime wrapper that sleeps for the configured latency on each invocation; at the end of the window it restores the original function configuration.
Use this fault to test how an event-driven or API-driven workload behaves when a Lambda function becomes slow: whether upstream callers honor timeouts, whether retries amplify the load, whether monitoring detects the latency increase, and whether downstream consumers degrade gracefully under stretched response times.
Use cases
Run this fault when you want to answer concrete questions like:
Caller timeout behaviour: When the function takes longer than expected, do upstream callers (API Gateway, ALB, EventBridge, Step Functions, application code) honor their configured timeouts?
Function timeout exposure: Does the function's own timeout protect against slow downstreams, or does it amplify cost and consumer latency?
Retry storms: Do callers retry latent invocations and amplify load on the function?
Monitoring fidelity: Do CloudWatch alarms on
Duration,ConcurrentExecutions, and downstream p99 fire within the SLA?Capacity headroom: Does extended duration push the function past its reserved concurrency and trigger throttling?
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_NAMEexists inREGIONand is in theActivestate.Latency vs function timeout: Confirm
LAMBDA_LATENCYis smaller than the function's configured timeout, otherwise every invocation hits the function timeout instead of completing.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.
Supported environments
AWS Lambda (zip and container image)
Supported
Lambda with provisioned concurrency
Supported
Lambda@Edge
Not supported
AWS regions
Supported in every commercial region; pass the region in REGION
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.
Go to common policy for all AWS faults to use a single superset IAM policy across every AWS fault.
Authentication
The fault supports three credential delivery models. Pick one based on how your chaos infrastructure is deployed.
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:
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.
Fault tunables
Configure the following fault parameters when you add Lambda inject latency to an experiment in Chaos Studio. Defaults are shown for reference.
Required parameters
FUNCTION_NAME
Name of the target Lambda function.
(required)
REGION
AWS region where the Lambda function is deployed.
(required)
LAMBDA_LATENCY
Latency to inject into every invocation, in seconds. Keep this lower than the function's configured timeout.
5
Chaos parameters
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
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.
Fault execution in brief
Reads the current function configuration, injects a runtime wrapper that sleeps for LAMBDA_LATENCY seconds on each invocation, waits for TOTAL_CHAOS_DURATION seconds, then restores the original function configuration.
Expected behavior during fault execution
Every new invocation of
FUNCTION_NAMEtakes at leastLAMBDA_LATENCYseconds longer to complete.CloudWatch metric
Durationfor the function rises by approximatelyLAMBDA_LATENCY * 1000ms.If the function is synchronously invoked (API Gateway, ALB, application code), callers see slower responses or timeouts.
If
LAMBDA_LATENCYis close to the function timeout,ErrorsandThrottlesmay rise as invocations exceed the configured timeout or push concurrency past its limit.
Signals to watch
Attach resilience probes to assert each layer:
Lambda duration: Use a Prometheus probe on the duration metric for the function.
Lambda errors/throttles: Use Prometheus probes on
aws_lambda_errors_sumandaws_lambda_throttles_sum.End-to-end latency: Use an HTTP probe on the user-visible endpoint and assert p95 / p99 stays inside the SLO.
Caller behaviour: Use an HTTP probe with the caller's timeout to confirm timeouts are honored.
Verify the fault execution effect
While the experiment is running, confirm the function is slower and then recovers:
Invoke the function and measure round-trip time.
Round-trip should rise by approximately
LAMBDA_LATENCYseconds during the chaos window and return to baseline afterwards.Check CloudWatch
Duration.Average and maximum should rise by ~
LAMBDA_LATENCY * 1000ms during the chaos window.Inspect logs.
REPORTlines should show longer billed durations during the chaos window.
Recovery and cleanup
End of duration: The chaos pod restores the original function configuration.
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> --region <region>with the original environment/runtime values (recorded in the chaos pod logs).Workload recovery: Warm containers carrying the wrapper are replaced on the next cold start; until then, sporadic latency may continue on warm invocations of the same execution environment.
Limitations
Per-invocation only: The fault adds latency on every invocation; it cannot target a percentage of invocations or specific code paths.
Cold start interaction: Updating the function configuration triggers cold starts during the chaos window; the first invocations after the start may include both
LAMBDA_LATENCYand the cold-start init time.Latency vs timeout: If
LAMBDA_LATENCYexceeds the function timeout, every invocation fails rather than completing slowly.Cross-region targeting: A single experiment targets one region (the value of
REGION).
Troubleshooting
Related faults
Lambda inject status code: Override HTTP status codes instead of adding latency.
Lambda modify response body: Override response bodies.
Lambda block TCP connection: Block outbound TCP connections from the function.
Common AWS fault tunables: Shared environment variables for AWS faults.
Last updated
Was this helpful?