Pod application function exception
Throw a configurable exception from a specific function of an instrumented application running in a Kubernetes pod so you can test how callers and dependents handle the failure.
Pod application function exception is a Kubernetes pod-level chaos fault that causes a specific function in an instrumented application to throw a configurable exception for a configurable duration. Only the named function is affected; other application code paths run normally. When the fault ends, the function returns to its normal behavior immediately.
Use this fault to validate how callers and dependents behave when a specific business function starts throwing: an unchecked exception from a library wrapper, a domain-specific exception from a validation routine, or any failure path that propagates as a thrown exception rather than a returned error.
Use cases
Run this fault when you want to answer concrete questions like:
Unchecked exception propagation: When a deep function throws, does the request boundary catch the exception, log it, and return a clean response, or does the stack trace leak to the client?
Exception-aware fallback paths: Does a wrapper that catches a specific exception type route to a fallback implementation, or does it rethrow and break the caller?
Retry filter correctness: Do retry policies treat the injected exception as retryable or non-retryable as intended, and does the policy match the framework's behavior?
Circuit breaker behavior: Does a circuit breaker that counts exceptions open after the configured failure threshold and short-circuit subsequent calls?
Observability coverage: Does the exception surface in traces, logs, and alerts with the right error type and message?
Prerequisites
Kubernetes version: 1.21 or later. Go to What's supported to confirm distribution support.
Target pod is Running: The application pod is in the
Runningstate.Application is instrumented: The application registers a name and exposes the target function to the chaos infrastructure. Without instrumentation, the chaos pod cannot reach the function.
Function is identifiable: The function to fail is reachable by the name set in
TARGET_APPLICATION_FUNCTION.Workload selector defined: The chaos experiment knows the target application by name.
Supported environments
Amazon EKS
Supported
Azure AKS
Supported
Google GKE
Supported
Red Hat OpenShift
Supported
Rancher
Supported
VMware Tanzu
Supported
Self-managed Kubernetes (CNCF-certified)
Supported
GKE Autopilot
Supported (no privileged access required)
EKS Fargate, ACI virtual nodes
Supported (no container runtime socket required)
Permissions required
The fault runs under the chaos infrastructure's service account.
Resource (apiGroup)
Verbs
Why it is needed
pods ("")
get, list, create, delete, deletecollection, patch, update
Discover the target pod and run the chaos pod
pods/log ("")
get, list, watch
Stream chaos pod logs for status and debugging
deployments, statefulsets, replicasets, daemonsets (apps)
get, list
Resolve the target workload to the pods it owns
events ("")
get, list, create, patch, update
Record fault progress as Kubernetes events
jobs (batch)
get, list, create, delete, deletecollection
Run the chaos job that drives the fault
The default Harness chaos infrastructure service account already includes these permissions.
Fault tunables
Configure the following fault parameters when you add Pod application function exception to an experiment in Chaos Studio. Defaults are shown for reference.
Required parameters
TARGET_APPLICATION_NAME
Name of the target application as registered with the chaos infrastructure.
(required)
TARGET_APPLICATION_FUNCTION
Name of the function inside the target application to throw the exception from.
(required)
Chaos parameters
MESSAGE
Exception message attached to the injected throw. Empty uses a default message.
""
TOTAL_CHAOS_DURATION
Duration of the fault in seconds.
60
RAMP_TIME
Wait period in seconds before and after the fault. Go to ramp time to read how it is applied.
0
Tunables that apply to every fault are documented in common tunables for all faults.
Fault execution in brief
Signals the instrumented application to make the function named in TARGET_APPLICATION_FUNCTION throw an exception containing MESSAGE for TOTAL_CHAOS_DURATION seconds.
Expected behavior during fault execution
Calls to the named function throw the configured exception. Other functions in the same application run normally.
Direct callers see the exception propagate up the stack unless they catch it. Frameworks may surface it as a 5xx response, a queued message rollback, or a propagated failure depending on the runtime.
Downstream services may see reduced or absent traffic if the throwing function fronted upstream calls.
Error dashboards and traces should show the injected exception type and message alongside any cascading failures.
Signals to watch
Attach resilience probes to assert each layer:
Application error rate: Use an HTTP probe against endpoints that exercise the function to detect 4xx/5xx spikes.
Function-level metrics: Use a Prometheus probe on the function's exception counter or success rate to confirm the injection.
Application logs: Use a command probe to grep container logs for the configured
MESSAGE.
Verify the fault execution effect
While the experiment is running, confirm the function is throwing:
Exercise the function from a client.
The response should reflect the failure, either as an HTTP error or an error payload that mentions the injected exception.
Confirm the exception surfaces in logs.
The configured
MESSAGEshould appear in stack traces or error logs for each thrown invocation.
Recovery and cleanup
End of duration: The function returns to its normal behavior automatically.
Abort the experiment: Stopping the experiment from Chaos Studio triggers the same cleanup path.
Stuck state: If the application caches the failure (for example by tripping a circuit breaker that does not reset on its own), restart the pod to clear the cached state.
Limitations
Instrumentation required: The fault only affects applications that have registered themselves and their functions with the chaos infrastructure. Uninstrumented applications cannot be targeted.
Function-name granularity: Only one function at a time is targeted. Use multiple experiments in sequence for multi-function scenarios.
Exception type is fixed by the instrumentation: The runtime exception type thrown is determined by the application's instrumentation layer; only
MESSAGEis configurable. Use Pod JVM method exception for JVM-specific exception-type control.
Troubleshooting
Related faults
Pod application function error: Inject an error from a function instead of throwing an exception.
Pod application function latency: Inject latency into a function instead of failing it.
Pod JVM method exception: JVM-specific method-level exception injection with full exception-type control.
Common pod fault tunables: Shared environment variables for selecting target pods and workloads.
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