Pod IO mistake
Seed wrong data into reads or writes against a target Kubernetes pod's mounted volume so you can validate how the application detects and recovers from silent data corruption.
Pod IO mistake is a Kubernetes pod-level chaos fault that overwrites a configurable number of bytes in matched filesystem read or write syscalls on a target container's mounted volume for a configurable duration. The application sees the call succeed, but the data flowing through it has been seeded with wrong bytes. When the fault ends, syscalls behave normally again immediately.
Use this fault to test how a service detects and recovers from silent data corruption: a flaky disk that flips bytes, a buggy controller that returns shuffled blocks, or a hardware error that escapes parity checks.
Due to the large blast radius of this fault, we recommend you do not execute it in the production environment.
Through the fault execution, the application pod can potentially fail to perform successful IO writes if the
writesystem call is being targeted. This can cause any data produced in this duration to be lost.Any data produced before the execution of the fault is not harmed as a result of its execution.
Use cases
Run this fault when you want to answer concrete questions like:
Checksum coverage: Does the application verify checksums on read, or does it silently propagate corrupted data downstream?
Format-level validation: When a JSON or Protobuf payload is read with zeroed bytes in the middle, does the parser reject the message or crash on it?
Replication conflict handling: For replicated stateful workloads, does a corrupted write cause the follower to diverge, and does the cluster detect the split?
Backup integrity: If a backup process reads corrupted bytes from a snapshot, does the resulting backup get flagged or stored as-is?
Recovery story: Once the fault ends, can the application repair its in-memory state, or does it stay broken until restart?
Prerequisites
Kubernetes version: 1.21 or later. Go to What's supported to confirm distribution support.
Target pod is Running: The pod you intend to target is in the
Runningstate with a mounted volume.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).Mounted volume: The target container has at least one writable mounted volume reachable at
MOUNT_PATH.Workload selector defined: The chaos experiment knows the target workload by kind, namespace, and either names or labels.
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 with Autopilot setup
EKS Fargate, ACI virtual nodes
Not supported (no access to container runtime sockets)
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 target pods and run the chaos pod on the same node
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 IO mistake to an experiment in Chaos Studio. Defaults are shown for reference.
Chaos parameters
SEED
Wrong-data pattern to substitute. Common values: zero (zero bytes), random, or a literal string.
"zero"
MAX_TIMES
Maximum number of places per syscall payload to seed the wrong data.
1
MAX_SIZE
Maximum size in bytes of each seeded chunk.
8
PERCENTAGE
Percentage of matching IO requests to corrupt, between 0 and 100. 100 corrupts every request.
100
TOTAL_CHAOS_DURATION
Duration of the fault in seconds.
60
Filters
MOUNT_PATH
Volume mount path inside the container to scope the fault. Empty applies to all mounts.
""
FILE_PATH
File path or glob beneath MOUNT_PATH to scope the fault. Empty applies to all files under MOUNT_PATH.
""
METHOD_TYPES
Comma-separated syscall types to corrupt: read, write, open. Empty applies to all three.
""
Targeting
TARGET_PODS
Comma-separated list of pod names to target. Empty selects from the workload's pods using POD_AFFECTED_PERCENTAGE.
""
TARGET_CONTAINER
Container in the pod whose filesystem to corrupt. Empty targets the first container in the pod spec.
""
NODE_LABEL
Label selector to filter target pods by the node they run on. Empty disables node-based filtering.
""
POD_AFFECTED_PERCENTAGE
Percentage of the workload's pods to target. 0 means one pod.
0
SEQUENCE
When multiple pods are targeted, inject parallel (all at once) or serial (one after another).
parallel
Runtime and helper
CONTAINER_RUNTIME
Container runtime on the target nodes. One of containerd, docker, crio.
containerd
SOCKET_PATH
Path to the container runtime socket on the target node. Set to match CONTAINER_RUNTIME.
/run/containerd/containerd.sock
RAMP_TIME
Wait 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.
WRITES SEED CORRUPTION TO DISK
When METHOD_TYPES includes write, the wrong bytes can land on disk and survive the fault. Always run against a recoverable test environment with backups; never run against production data.
Configure for your container runtime
Set CONTAINER_RUNTIME and SOCKET_PATH to match the runtime on the target node:
CONTAINER_RUNTIME
SOCKET_PATH
containerd (default)
/run/containerd/containerd.sock
docker
/var/run/docker.sock
crio
/var/run/crio/crio.sock
Fault execution in brief
Intercepts filesystem syscalls (read, write, open) inside the target container's mount namespace and substitutes up to MAX_TIMES slices of up to MAX_SIZE bytes in the payload with SEED, optionally limited to a configurable percentage so other IO is unaffected.
Expected behavior during fault execution
Matched syscalls return success with corrupted payloads. Applications that do not checksum what they read or write pass the corruption downstream.
Format-aware parsers (JSON, Protobuf, BSON) typically fail loudly with parse errors when the corruption falls in a structural region.
Checksumming layers (RocksDB, etcd, MongoDB) surface verification failures and may close affected segments or trip read-repair.
Writes can persist corrupted bytes to the backing volume. The corruption survives until overwritten or repaired by the application.
Signals to watch
Attach resilience probes to assert each layer:
Application error rate: Use an HTTP probe to detect parse or checksum errors surfacing as 5xx.
Pod readiness: Use a Kubernetes probe to fail when the target pod stops being
Readybecause of failing self-checks.Checksum / corruption metrics: Use a Prometheus probe on workload-specific counters (RocksDB
block_checksum_mismatch, MongoDBwiredTigercursor errors, etc.).
Verify the fault execution effect
While the experiment is running, confirm the data is corrupted:
Read a matched file and inspect a hexdump.
The leading bytes should contain the
SEEDpattern instead of the original content.Confirm application-level impact.
Look for parse errors, checksum mismatches, or rejected payloads.
Recovery and cleanup
End of duration: Syscalls behave normally again automatically.
Abort the experiment: Stopping the experiment from Chaos Studio triggers the same cleanup path.
Persisted corruption: Bytes written to the volume during the fault remain corrupted. Restore from backup, replay from a clean source, or rebuild affected state.
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.
Read-only volumes:
ConfigMap,Secret, and downward API volumes are read-only.Persisted corruption is not undone: Writes that succeeded during the fault leave corrupted bytes on disk. Plan recovery before running.
Page cache and
mmap: Bytes already in the page cache or mapped pages may bypass the syscall path; behavior on these reads is not guaranteed.
Troubleshooting
Related faults
Pod IO error: Fail filesystem syscalls with a configurable error code instead of corrupting data.
Pod IO latency: Add delay to filesystem syscalls.
Pod IO attribute override: Override file attributes on the mounted volume.
Pod IO stress: Generate sustained read and write load.
Common pod fault tunables: Shared environment variables for selecting target pods and workloads.
Last updated
Was this helpful?