ECS container memory hog
Consume a configurable amount of memory (absolute or percentage) using a configurable number of workers inside a percentage of running ECS tasks (EC2 launch type) for a configurable duration so you ca
ECS container memory hog is an AWS chaos fault that allocates MEMORY_CONSUMPTION MB (or MEMORY_PERCENTAGE percent of the container's memory limit) using NUMBER_OF_WORKERS worker threads inside a percentage of running ECS tasks (EC2 launch type) for a configurable duration. The fault discovers the EC2 container instances hosting the target tasks and runs memory-stress commands inside the relevant containers via AWS Systems Manager Run Command on each host, scoped by ECS container metadata.
Use this fault to test how an ECS workload behaves under sustained memory pressure that is contained to a subset of tasks: whether the container OOM-kills cleanly, whether application-level memory limits engage, whether replacement tasks recover quickly, and whether memory-based autoscaling responds correctly.
Use cases
Run this fault when you want to answer concrete questions like:
OOM kill behaviour: When memory exceeds the container limit, does ECS OOM-kill the container cleanly, and does the service controller launch a replacement?
Cache eviction: For caches that hold a large working set in memory, do they evict gracefully under pressure, or do they crash?
Memory leak detection: Does monitoring detect rapidly rising memory usage within the alarm SLA?
GC pressure (managed runtimes): Does the JVM/CLR/Go runtime stabilize, or does it enter a GC death spiral?
Recovery time: When the stress ends, how quickly does memory return to baseline?
Prerequisites
Kubernetes version: 1.21 or later for the chaos infrastructure cluster. Go to What's supported to confirm distribution support.
Target ECS service or cluster:
CLUSTER_NAMEexists inREGIONand uses the EC2 launch type. IfSERVICE_NAMEis set, the fault selects from that service's running tasks.Container instances are SSM-managed: Every EC2 container instance is registered with AWS Systems Manager.
ECS container metadata enabled: Container metadata must be enabled so the fault can locate the target container on each host. Go to Container metadata file to enable it.
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
Amazon ECS on EC2 launch type
Supported
Amazon ECS on Fargate launch type
Not supported (use ECS Fargate memory hog instead)
Linux container instances
Supported
Windows container instances
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.
Go to AWS named profile for chaos to switch between profiles inside a single credentials file.
Fault tunables
Configure the following fault parameters when you add ECS container memory hog to an experiment in Chaos Studio. Defaults are shown for reference.
Required parameters
CLUSTER_NAME
Name of the target ECS cluster.
(required)
REGION
AWS region that hosts the ECS cluster (for example us-east-1).
(required)
Targeting parameters
SERVICE_NAME
Name of the target ECS service. When set, the fault selects TASK_REPLICA_AFFECTED_PERC of the service's running tasks.
""
TASK_REPLICA_AFFECTED_PERC
Percentage of running tasks to stress when SERVICE_NAME is set.
100
Chaos parameters
MEMORY_CONSUMPTION
Amount of memory in MB to allocate per worker inside the container. Set to 0 and use MEMORY_PERCENTAGE for a percentage-based allocation.
100
MEMORY_PERCENTAGE
Percentage of the container's memory limit to allocate. Used only when MEMORY_CONSUMPTION=0.
0
NUMBER_OF_WORKERS
Number of worker threads that each allocate MEMORY_CONSUMPTION MB.
1
TOTAL_CHAOS_DURATION
Duration of the fault in seconds.
60
INSTALL_DEPENDENCIES
Install the stress tooling on each container instance if missing.
true
DEFAULT_HEALTH_CHECK
When true, the fault runs additional checks against ECS to verify task health.
false
SEQUENCE
Order in which multiple tasks are stressed: parallel issues the stress on all selected tasks at once; serial does so one at a time.
parallel
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. AWS-specific shared tunables are documented in common AWS fault tunables.
Fault execution in brief
Resolves the running tasks for SERVICE_NAME (or all tasks in CLUSTER_NAME), picks TASK_REPLICA_AFFECTED_PERC of them, and dispatches a memory-allocation command via AWS Systems Manager Run Command to the EC2 host of each selected task. The command is scoped to the target container via ECS container metadata, holds the memory for TOTAL_CHAOS_DURATION seconds, and releases it at the end.
Expected behavior during fault execution
The targeted containers' memory usage rises to (
MEMORY_CONSUMPTION×NUMBER_OF_WORKERS) MB or toMEMORY_PERCENTAGEof the container limit.If the allocation exceeds the container's memory limit, ECS OOM-kills the container; the service controller launches a replacement.
Application latency may rise; the memory-based autoscaling alarm may fire.
Other containers on the same EC2 host may experience pressure depending on cgroup limits.
CloudWatch metrics (MemoryUtilization) reflect the elevated usage.
Signals to watch
Attach resilience probes to assert each layer:
Memory utilization: Use a Prometheus probe on
aws_ecs_memory_utilizationfor the affected service.Application latency: Use an HTTP probe and assert percentile latency SLOs.
OOM kills: Use a command probe that runs
aws ecs describe-tasks --query "tasks[].containers[].[exitCode,reason]"and asserts on expected (or unexpected) OOM behaviour.Autoscaling alarms: Confirm memory-based scaling policy alarms fire when expected.
Verify the fault execution effect
While the experiment is running, confirm memory pressure is applied:
Check memory utilization metrics.
In the AWS console (CloudWatch → ECS → ClusterName → ServiceName),
MemoryUtilizationshould rise sharply during the chaos window and fall after recovery.Check for OOM kills.
Look for
OutOfMemoryErrorin the reason field for containers that were OOM-killed.Inspect SSM command status.
During the fault, you should see in-progress commands on the affected container instances.
Recovery and cleanup
End of duration: The chaos pod terminates the stress process on each host. Memory returns to baseline.
Abort the experiment: Stopping the experiment from Chaos Studio cancels the SSM command.
Manual recovery: If the fault exits before cleanup runs, stop the stress process by sending an SSM command to kill the relevant process on the affected hosts.
Workload recovery: Tasks killed by OOM during the stress are rescheduled by the ECS service controller.
Limitations
EC2 launch type only: This fault uses SSM Run Command against the underlying EC2 host. For Fargate use ECS Fargate memory hog.
Container metadata must be enabled.
SSM-managed hosts only.
Linux-only.
Cross-region targeting: A single experiment targets one region (the value of
REGION).
Troubleshooting
Related faults
ECS container CPU hog: Stress CPU inside containers instead of memory.
ECS container IO stress: Stress filesystem IO inside containers.
ECS Fargate memory hog: Memory stress for Fargate tasks (different mechanism).
Common AWS fault tunables: Shared environment variables for AWS faults.
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