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Pod JVM Kafka exception

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Pod JVM Kafka exception is a Kubernetes pod-level chaos fault that causes Kafka client calls from a JVM running in a target container to throw a configurable exception on a chosen topic and client mode for a configurable duration. Only matched calls fail; other Kafka traffic and other code paths run normally. When the fault ends, Kafka calls behave normally again immediately.

Use this fault to test how a Java service handles Kafka failures: a broker rejecting produces, a consumer that fails to deserialize, or a partition leader that drops responses.

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.

Use cases​

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

  • Producer error handling: When a send() throws on a critical topic, does the application retry, buffer, or drop the message?
  • Consumer poison messages: Simulate deserialization or processing errors on the consumer side and verify dead-letter or skip semantics.
  • Idempotency under retries: Does the application's retry logic correctly de-duplicate messages?
  • Topic-scoped impact: Confirm that failing one topic does not unintentionally fail other topics on the same client.
  • Observability coverage: Do producer-error metrics, dead-letter queues, and dashboards surface the failure clearly?

Prerequisites​

  • Kubernetes version: 1.21 or later. Go to What's supported to confirm distribution support.
  • Target pod is Running: The Java application pod is in the Running state.
  • Java agent attach available: The Java process allows agent attach. Utilities such as ps, pgrep, and bash are present in the container, and the JVM is not built with a restricted runtime that strips attach modules.
  • Kafka client in classpath: The target JVM uses the Apache Kafka Java client and produces to or consumes from the configured KAFKA_TOPIC in the configured KAFKA_MODE.
  • Privileged pods allowed: The cluster lets you schedule privileged pods in the chaos namespace. GKE Autopilot supports this fault but requires the one-time setup in Chaos on GKE Autopilot; other locked-down distributions may need similar exemptions.
  • Container runtime access: The chaos pod can reach the container runtime socket on the target node (/run/containerd/containerd.sock, /var/run/docker.sock, or /var/run/crio/crio.sock).
  • Workload selector defined: The chaos experiment knows the target workload by kind, namespace, and either names or labels.
JVM chaos uses the Byteman agent

This fault attaches a Byteman agent to the target JVM over BYTEMAN_PORT. The port must be reachable from the chaos pod and must not be in use by the application.

Supported environments​

PlatformSupport status
Amazon EKSSupported
Azure AKSSupported
Google GKESupported
Red Hat OpenShiftSupported
RancherSupported
VMware TanzuSupported
Self-managed Kubernetes (CNCF-certified)Supported
GKE AutopilotSupported with Autopilot setup
EKS Fargate, ACI virtual nodesNot supported (no access to container runtime sockets)

Permissions required​

The fault runs under the chaos infrastructure's service account.

Resource (apiGroup)VerbsWhy it is needed
pods ("")get, list, create, delete, deletecollection, patch, updateDiscover target pods and run the chaos pod on the same node
pods/log ("")get, list, watchStream chaos pod logs for status and debugging
deployments, statefulsets, replicasets, daemonsets (apps)get, listResolve the target workload to the pods it owns
events ("")get, list, create, patch, updateRecord fault progress as Kubernetes events
jobs (batch)get, list, create, delete, deletecollectionRun 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 JVM Kafka exception to an experiment in Chaos Studio. Defaults are shown for reference.

Kafka filters

TunableDescriptionDefault
KAFKA_MODEClient mode to target. One of producer (publish-side) or consumer (subscribe-side)."producer"
KAFKA_TOPICTarget Kafka topic name. Empty matches all topics for the configured mode.""
TRANSACTION_PERCENTAGEPercentage of matched Kafka operations to fail, between 0 and 100. 0 fails none; 100 fails every match.0

Exception

TunableDescriptionDefault
EXCEPTION_CLASSException class to throw. Defaults to a common runtime exception."IllegalArgumentException"
EXCEPTION_MESSAGEMessage attached to the thrown exception."CHAOS BOOM!"

Chaos parameters

TunableDescriptionDefault
TOTAL_CHAOS_DURATIONDuration of the fault in seconds.60

JVM

TunableDescriptionDefault
BYTEMAN_PORTPort on which the Byteman agent listens inside the container. Must not conflict with any port already in use.9091
JAVA_HOMEAbsolute path to the Java installation inside the container. Empty auto-detects from PATH.""

Targeting

TunableDescriptionDefault
TARGET_PODSComma-separated list of pod names to target. Empty selects from the workload's pods using POD_AFFECTED_PERCENTAGE.""
TARGET_CONTAINERContainer in the pod running the JVM. Empty targets the first container in the pod spec.""
NODE_LABELLabel selector to filter target pods by the node they run on. Empty disables node-based filtering.""
POD_AFFECTED_PERCENTAGEPercentage of the workload's pods to target. 0 means one pod.0
SEQUENCEWhen multiple pods are targeted, inject parallel (all at once) or serial (one after another).parallel

Runtime and helper

TunableDescriptionDefault
CONTAINER_RUNTIMEContainer runtime on the target nodes. One of containerd, docker, crio.containerd
SOCKET_PATHPath to the container runtime socket on the target node. Set to match CONTAINER_RUNTIME./run/containerd/containerd.sock
RAMP_TIMEWait period in seconds before and after the fault. Go to ramp time to read how it is applied.0

Common pod selection tunables (TARGET_WORKLOAD_KIND, TARGET_WORKLOAD_NAMESPACE, TARGET_WORKLOAD_NAMES, TARGET_WORKLOAD_LABELS) are documented in common pod fault tunables. Tunables that apply to every fault are documented in common tunables for all faults.

Use a realistic exception type

Choose an exception the caller can plausibly receive (for example org.apache.kafka.common.errors.TimeoutException or org.apache.kafka.common.errors.SerializationException). Picking an unrelated exception type often surfaces uncaught-exception bugs that would not happen in real failures.

Configure for your container runtime​

Set CONTAINER_RUNTIME and SOCKET_PATH to match the runtime on the target node:

CONTAINER_RUNTIMESOCKET_PATH
containerd (default)/run/containerd/containerd.sock
docker/var/run/docker.sock
crio/var/run/crio/crio.sock

Fault execution in brief​

Attaches a Java agent to the target JVM and intercepts Kafka client operations matching KAFKA_MODE and KAFKA_TOPIC to throw an instance of EXCEPTION_CLASS with EXCEPTION_MESSAGE on the configured percentage of calls, for TOTAL_CHAOS_DURATION seconds.

Expected behavior during fault execution​

  • Matched Kafka client operations throw the configured exception. Other topics and the unmatched mode (producer or consumer) run normally.
  • Application logs show stack traces from the configured exception class.
  • The Kafka brokers are not stressed; no real produce or fetch happens for the failed calls.
  • Tracing systems show the Kafka span ending in error.
When the fault ends

Kafka calls behave normally again immediately. Cached state in callers (open circuits, exhausted retry budgets, dead-letter queues that filled during the fault) may take additional time to drain.

Signals to watch​

Attach resilience probes to assert each layer:

  • Producer error rate: Use a Prometheus probe on kafka_producer_record_error_total or your APM's Kafka error metric.
  • Consumer lag and error rate: Use a Prometheus probe on kafka_consumer_records_consumed_total and error counters to detect lag growth or failed processing.
  • Application logs: Use a command probe to grep for the configured EXCEPTION_MESSAGE.

Verify the fault execution effect​

While the experiment is running, confirm operations are failing:

  1. Exercise the matched code path from a client.

    kubectl run -n <namespace> tester --image=nicolaka/netshoot --rm -it -- \
      curl -s http://<service>:<port>/<endpoint-that-uses-the-topic>

  2. Confirm the exception in logs.

    kubectl logs -n <namespace> <target-pod> --tail=200 | grep "<EXCEPTION_MESSAGE>"

Recovery and cleanup​

  • End of duration: Kafka calls behave normally again automatically.
  • Abort the experiment: Stopping the experiment from Chaos Studio triggers the same cleanup path.
  • Backlog drainage: Consumers may have built up lag during the fault. Allow time for normal processing to catch up, or scale consumers temporarily if needed.

Limitations​

  • Serverless Kubernetes (EKS Fargate, ACI virtual nodes): These platforms do not expose container runtime sockets and reject the privileged access the fault needs. GKE Autopilot is supported once the one-time setup in Chaos on GKE Autopilot is in place.
  • Windows containers: This fault is supported on Linux pods only.
  • Non-JVM and non-Kafka workloads: This fault targets the Apache Kafka Java client inside a JVM.
  • Streams API: Applications using Kafka Streams may surface errors through the StreamsUncaughtExceptionHandler rather than directly to the caller.

Troubleshooting​

Pod JVM Kafka exception experiment stays Pending or never starts in Harness Chaos Engineering

Inspect the chaos pods in the experiment namespace with kubectl describe pod -n <chaos-namespace>. The most common causes are taints on the target node that the chaos pods do not tolerate, insufficient resources, or a PodSecurity admission policy blocking privileged pods. Add the required tolerations or run in a namespace with privileged Pod Security level.

No exception observed during pod-jvm-kafka-exception

The most common causes are: KAFKA_MODE does not match what the application uses (producer vs consumer); KAFKA_TOPIC does not match the topic the application produces/consumes; TRANSACTION_PERCENTAGE is 0 (default); or the application uses the Kafka Streams API which surfaces errors differently. Re-run with TRANSACTION_PERCENTAGE=100 and empty KAFKA_TOPIC to broaden the match.

Connection to container runtime fails for pod-jvm-kafka-exception in Harness Chaos Engineering

The default SOCKET_PATH is /run/containerd/containerd.sock. For Docker, set CONTAINER_RUNTIME=docker and SOCKET_PATH=/var/run/docker.sock. For CRI-O, set CONTAINER_RUNTIME=crio and SOCKET_PATH=/var/run/crio/crio.sock.