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Pod JVM method latency

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Pod JVM method latency is a Kubernetes pod-level chaos fault that adds a configurable delay to every invocation of a specific Java method in a JVM running in a target container for a configurable duration. Only the named method is slowed; all other code paths run at normal speed. When the fault ends, the method returns to its normal latency immediately.

Use this fault to test how callers and dependents behave when a specific method becomes slow: a database wrapper hitting a slow query, a third-party SDK on a degraded link, or a business-logic method blocked on a slow lock.

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:

  • Timeout-budget validation: When the method takes 2 seconds instead of 20 ms, do callers honor their timeouts or hang?
  • Thread-pool saturation: Does slow method invocation block worker threads enough to stall the application?
  • Tail-latency budget: Does the added method latency push end-to-end p99 over your SLO?
  • Caller fallback paths: If the method represents a non-critical call, does the application skip it and continue, or block on the slow path?
  • Bulk-operation impact: For methods called in batch loops, does the cumulative delay produce timeouts or out-of-memory pressure as queues grow?

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.
  • 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 method latency to an experiment in Chaos Studio. Defaults are shown for reference.

Required parameters

TunableDescriptionDefault
CLASSFully qualified class name containing the target method (for example com.example.payments.PaymentService).(required)
METHODName of the method to add latency to.(required)

Chaos parameters

TunableDescriptionDefault
LATENCYDelay to add to each invocation of the target method, in milliseconds.2000
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.

Start near the caller's timeout

Set LATENCY slightly below the caller's configured timeout to validate that timeout handling is correct, then increase it above the timeout to confirm the caller cancels the call cleanly.

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 instruments CLASS.METHOD so that each invocation blocks for LATENCY milliseconds before returning, for TOTAL_CHAOS_DURATION seconds.

Expected behavior during fault execution​

  • Every call to the named method takes longer by approximately LATENCY ms. Other methods run normally.
  • Caller-side metrics (request latency, queue depth, in-flight requests) rise to reflect the added delay.
  • Clients with timeouts shorter than LATENCY cancel the call and may retry.
  • Thread-pool-bound applications saturate quickly if many concurrent callers wait on the slow method.
  • Tracing systems show the method span growing by LATENCY; downstream spans are unchanged.
When the fault ends

The method returns to its normal latency immediately. Calls already in flight finish at the delayed time and then the system returns to baseline.

Signals to watch​

Attach resilience probes to assert each layer:

  • Method-level latency: Use a Prometheus probe on the method's p99 duration to confirm the rise matches LATENCY.
  • Caller timeouts: Use an HTTP probe against endpoints that exercise the method to detect rising timeouts.
  • Pod readiness: Use a Kubernetes probe to fail when the target pod oscillates NotReady.

Verify the fault execution effect​

While the experiment is running, confirm the method is slower:

  1. Time a request that calls the method.

    kubectl run -n <namespace> tester --image=nicolaka/netshoot --rm -it -- \
      curl -w "time=%{time_total}\n" -o /dev/null -s http://<service>:<port>/<endpoint-that-calls-the-method>

    time_total should rise by approximately LATENCY ms.

  2. Confirm method span in tracing.

    In your APM, the configured method span should be roughly LATENCY ms longer than its baseline.

Recovery and cleanup​

  • End of duration: The method returns to its normal latency automatically.
  • Abort the experiment: Stopping the experiment from Chaos Studio triggers the same cleanup path.
  • Stuck threads: If the application is wedged because of saturated thread pools, restart the pod.

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 processes: This fault targets a Java process.
  • Inlined methods: Methods inlined by the JIT compiler may not be interceptable; run with -XX:-Inline for verification if needed.
  • Method overloads: Only the method name is matched. All overloads with the same name are affected.

Troubleshooting​

Pod JVM method latency 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 latency observed during pod-jvm-method-latency

The most common causes are: CLASS or METHOD does not match (verify the fully qualified class name and case-sensitive method name); the method is JIT-inlined; the wrong container is targeted (set TARGET_CONTAINER explicitly); or JAVA_HOME is not detectable. Re-run with a larger LATENCY value and time a known client call to confirm.

Connection to container runtime fails for pod-jvm-method-latency 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.