Chaos faults for AWS
Introduction
AWS faults disrupt the resources running on different AWS services from the EKS cluster. To perform such AWS chaos experiments, you will need to authenticate CE with the AWS platform. This can be done in two ways.
- Using secrets: You can use secrets to authenticate CE with AWS regardless of whether the Kubernetes cluster is used for the deployment. This is Kubernetes' native way of authenticating CE with AWS.
- IAM integration: You can authenticate CE using AWS using IAM when you have deployed chaos on the EKS cluster. You can associate an IAM role with a Kubernetes service account. This service account can be used to provide AWS permissions to the experiment pod which uses the particular service account.
Here are AWS faults that you can execute and validate.
ALB AZ down
ALB AZ down takes down the AZ (Availability Zones) on a target application load balancer for a specific duration.
CLB AZ down
CLB AZ down takes down the AZ (Availability Zones) on a target CLB for a specific duration.
DynamoDB replication pause
DynamoDB replication pause fault pauses the data replication in DynamoDB tables over multiple locations for the chaos duration.
EBS loss by ID
EBS loss by ID disrupts the state of EBS volume by detaching it from the node (or EC2) instance using volume ID for a certain duration.
EBS loss by tag
EBS loss by tag disrupts the state of EBS volume by detaching it from the node (or EC2) instance using volume ID for a certain duration.
EC2 CPU hog
EC2 CPU hog disrupts the state of infrastructure resources. It induces stress on the AWS ECS container using Amazon SSM Run command, which is carried out using SSM docs which is in-built into the fault.
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ALB AZ down
ALB AZ down takes down the AZ (Availability Zones) on a target application load balancer for a specific duration. This fault restricts access to certain availability zones for a specific duration.
Use cases
- Tests the application sanity, availability, and recovery workflows of the application pod attached to the load balancer.
- ALB AZ down fault breaks the connectivity of an ALB with the given zones and impacts their delivery.
- Detaching the AZ from the application load balancer disrupts the application's performance.
CLB AZ down
CLB AZ down takes down the AZ (Availability Zones) on a target CLB for a specific duration. This fault restricts access to certain availability zones for a specific duration.
Use cases
- Tests the application sanity, availability, and recovery workflows of the application pod attached to the load balancer.
- CLB AZ down fault breaks the connectivity of a CLB with the given zones and impacts their delivery.
- Detaching the AZ from the classic load balancer disrupts the dependent application's performance.
DynamoDB replication pause
DynamoDB replication pause fault pauses the data replication in DynamoDB tables over multiple locations for the chaos duration.
- When chaos experiment is being executed, any changes to the DynamoDB table will not be replicated in different regions, thereby making the data in the DynamoDB inconsistent.
- You can execute this fault on a DynamoDB table that is global, that is, there should be more than one replica of the table.
Use cases
DynamoDB replication pause determines the resilience of the application when data (in a database) that needs to be constantly updated is disrupted.
EBS loss by ID
EBS loss by ID disrupts the state of EBS volume by detaching it from the node (or EC2) instance using volume ID for a certain duration.
- In case of EBS persistent volumes, the volumes can self-attach and the re-attachment step can be skipped.
Use cases
- It tests the deployment sanity (replica availability and uninterrupted service) and recovery workflows of the application pod.
EBS loss by tag
EBS loss by tag disrupts the state of EBS volume by detaching it from the node (or EC2) instance using volume ID for a certain duration.
- In case of EBS persistent volumes, the volumes can self-attach and the re-attachment step can be skipped.
Use cases
- It tests the deployment sanity (replica availability and uninterrupted service) and recovery workflows of the application pod.
EC2 CPU hog
EC2 CPU hog disrupts the state of infrastructure resources. It induces stress on the AWS ECS container using Amazon SSM Run command, which is carried out using SSM docs which is in-built into the fault.
- It causes CPU chaos on the containers of the ECS task using the given
CLUSTER_NAMEenvironment variable for a specific duration.
Use cases
- Induces CPU stress on the target AWS EC2 instance(s).
- Simulates a lack of CPU for processes running on the application, which degrades their performance.
- Simulates slow application traffic or exhaustion of the resources, leading to degradation in the performance of processes on the instance.
EC2 DNS chaos
EC2 DNS chaos causes DNS errors on the specified EC2 instance for a specific duration. It determines the performance of the application (or process) running on the EC2 instance(s).
Use cases
- Determines the performance of the application (or process) running on the EC2 instance(s).
- Simulates the unavailability (or distorted) network connectivity from the VM to the target hosts.
- Determines the impact of DNS chaos on the infrastructure and standalone tasks.
- Simulates unavailability of the DNS server (loss of access to any external domain from a given microservice, access to cloud provider dependencies, and access to specific third party services).
EC2 HTTP latency
EC2 HTTP latency disrupts the state of infrastructure resources. This fault induces HTTP chaos on an AWS EC2 instance using the Amazon SSM Run command, carried out using SSM Docs that is in-built in the fault.
- It injects HTTP response latency to the service whose port is specified using
TARGET_SERVICE_PORTenvironment variable by starting the proxy server and redirecting the traffic through the proxy server. - It introduces HTTP latency chaos on the EC2 instance using an SSM doc for a certain chaos duration.
Use cases
- Delays the network connectivity from the VM to the target hosts.
- Simulates latency to specific API services for (or from) a given microservice.
- Simulates a slow response on specific third party (or dependent) components (or services).
EC2 HTTP modify body
EC2 HTTP modify body injects HTTP chaos which affects the request/response by modifying the status code or the body or the headers by starting proxy server and redirecting the traffic through the proxy server.
Use cases
- It can test the application's resilience to erroneous or incorrect HTTP response body.
EC2 HTTP modify header
EC2 HTTP modify header injects HTTP chaos which affects the request (or response) by modifying the status code (or the body or the headers) by starting the proxy server and redirecting the traffic through the proxy server. It modifies the headers of requests and responses of the service.
Use cases
- This can be used to test service resilience towards incorrect or incomplete headers.
EC2 HTTP reset peer
EC2 HTTP reset peer injects HTTP reset on the service whose port is specified using the TARGET_SERVICE_PORT environment variable.
- It stops the outgoing HTTP requests by resetting the TCP connection for the requests.
Use cases
- Verifies connection timeout by simulating premature connection loss (firewall issues or other issues) between microservices.
- Simulates connection resets due to resource limitations on the server side like out of memory server (or process killed or overload on the server due to a high amount of traffic).
- Determines the application's resilience to a lossy (or flaky) HTTP connection.
EC2 HTTP status code
EC2 HTTP status code injects HTTP chaos that affects the request (or response) by modifying the status code (or the body or the headers) by starting a proxy server and redirecting the traffic through the proxy server.
Use cases
- Tests the application's resilience to erroneous code HTTP responses from the application server.
- Simulates unavailability of specific API services (503, 404).
- Simulates unavailability of specific APIs for (or from) a given microservice (TBD or Path Filter) (404).
- Simulates unauthorized requests for 3rd party services (401 or 403), and API malfunction (internal server error) (50x).
EC2 IO stress
EC2 IO stress disrupts the state of infrastructure resources.
- The fault induces stress on AWS EC2 instance using Amazon SSM Run command that is carried out using the SSM docs that comes in-built in the fault.
- It causes IO stress on the EC2 instance for a certain duration.
Use cases
- Simulates slower disk operations by the application.
- Simulates noisy neighbour problems by hogging the disk bandwidth.
- Verifies the disk performance on increasing IO threads and varying IO block sizes.
- Checks how the application functions under high disk latency conditions, when IO traffic is high and includes large I/O blocks, and when other services monopolize the IO disks.
EC2 memory hog
EC2 memory hog disrupts the state of infrastructure resources.
- The fault induces stress on AWS EC2 instance using Amazon SSM Run command that is carried out using the SSM docs that comes in-built in the fault.
- It causes memory exhaustion on the EC2 instance for a specific duration.
Use cases
- Causes memory stress on the target AWS EC2 instance(s).
- Simulates the situation of memory leaks in the deployment of microservices.
- Simulates application slowness due to memory starvation, and noisy neighbour problems due to hogging.
EC2 network latency
EC2 network latency causes flaky access to the application (or services) by injecting network packet latency to EC2 instance(s). This fault:
- Degrades the network without marking the EC2 instance as unhealthy (or unworthy) of traffic, which is resolved using a middleware that switches traffic based on SLOs (performance parameters).
- May stall the EC2 instance or get corrupted waiting endlessly for a packet.
- Limits the impact (blast radius) to the traffic that you wish to test, by specifying the IP addresses.
Use cases
- Determines the performance of the application (or process) running on the EC2 instances.
- Simulates a consistently slow network connection between microservices (for example, cross-region connectivity between active-active peers of a given service or across services or poor cni-performance in the inter-pod-communication network).
- Simulates jittery connection with transient latency spikes between microservices.
- Simulates a slow response on specific third party (or dependent) components (or services), and degraded data-plane of service-mesh infrastructure.
EC2 network loss
EC2 network loss causes flaky access to the application (or services) by injecting network packet loss to EC2 instance(s). This fault:
- Degrades the network without marking the EC2 instance as unhealthy (or unworthy) of traffic, which is resolved using a middleware that switches traffic based on SLOs (performance parameters).
- May stall the EC2 instance or get corrupted waiting endlessly for a packet.
- Limits the impact (blast radius) to the traffic that you wish to test, by specifying the IP addresses.
Use cases
- Determines the performance of the application (or process) running on the EC2 instances.
- Simulates a consistently slow network connection between microservices (for example, cross-region connectivity between active-active peers of a given service or across services or poor cni-performance in the inter-pod-communication network).
- Simulates jittery connection with transient latency spikes between microservices.
- Simulates a slow response on specific third party (or dependent) components (or services), and degraded data-plane of service-mesh infrastructure.
EC2 process kill
EC2 process kill fault kills the target processes running on an EC2 instance. This fault disrupts the application critical processes such as databases or message queues running on the EC2 instance by killing their underlying processes or threads.
Use cases
EC2 process kill determines the resilience of applications when processes on EC2 instances are unexpectedly killed (or disrupted).
EC2 stop by ID
EC2 stop by ID stops an EC2 instance using the provided instance ID or list of instance IDs.
- It brings back the instance after a specific duration.
- It checks the performance of the application (or process) running on the EC2 instance.
- When the
MANAGED_NODEGROUPenvironment variable is enabled, the fault will not try to start the instance after chaos. Instead, it checks for the addition of a new node instance to the cluster.
Use cases
- Determines the performance of the application (or process) running on the EC2 instance.
- Determines the resilience of an application to unexpected halts in the EC2 instance by validating its failover capabilities.
EC2 stop by tag
EC2 stop by tag stops an EC2 instance using the provided tag.
- It brings back the instance after a specific duration.
- It checks the performance of the application (or process) running on the EC2 instance.
- When the
MANAGED_NODEGROUPenvironment variable is enabled, the fault will not try to start the instance after chaos. Instead, it checks for the addition of a new node instance to the cluster.
Use cases
- Determines the performance of the application (or process) running on the EC2 instance.
- Determines the resilience of an application to unexpected halts in the EC2 instance by validating its failover capabilities.
ECS agent stop
ECS agent stop disrupts the state of infrastructure resources. This fault:
- Induces an agent stop chaos on AWS ECS using Amazon SSM Run command, that is carried out by using SSM documentation which is in-built in the fault for the give chaos scenario.
- Causes agent container stop on ECS for a specific duration, with a given
CLUSTER_NAMEenvironment variable using SSM documentation. Killing the agent container disrupts the performance of the task containers.
Use cases
- ECS agent stop halts the agent that manages the task container on the ECS cluster, thereby impacting its delivery.
ECS container CPU hog
ECS container CPU hog disrupts the state of infrastructure resources. It induces stress on the AWS ECS container using Amazon SSM Run command, which is carried out using SSM documentation that is in-built into the fault. This fault:
- Causes CPU chaos on the containers of the ECS task using the given
CLUSTER_NAMEenvironment variable for a specific duration. - To select the Task Under Chaos (TUC), use the service name associated with the task. If you provide the service name along with the cluster name, all the tasks associated with the given service will be selected as chaos targets.
- This experiment induces chaos within a container and depends on an EC2 instance. Typically, these are prefixed with "ECS container" and involve direct interaction with the EC2 instances hosting the ECS containers.
Use cases
- Evicts the application (task container) thereby impacting its delivery. These issues are known as noisy neighbour problems.
- Simulates a lack of CPU for processes running on the application, which degrades their performance.
- Verifies metrics-based horizontal pod autoscaling as well as vertical autoscale, that is, demand-based CPU addition.
- Scales the nodes based on growth beyond budgeted pods.
- Verifies the autopilot functionality of (cloud) managed clusters.
- Verifies multi-tenant load issue, wherein when the load increases on one container, it does not cause downtime in other containers.
- Tests the ECS task sanity (service availability) and recovery of the task containers subject to CPU stress.
ECS container HTTP latency
ECS container HTTP latency induces HTTP chaos on containers running in an Amazon ECS (Elastic Container Service) task. This fault introduces latency in the HTTP responses of containers of a specific service using a proxy server, simulating delays in network connectivity or slow responses from the dependent services.
Use cases
- Modifies the HTTP responses of containers in a specified ECS service by starting a proxy server and redirecting traffic through the proxy server.
- Simulates scenarios where containers experience delays in network connectivity or slow responses from dependent services, which may impact the behavior of your application.
- Validates the behavior of your application and infrastructure during simulated HTTP latency, such as:
- Testing how your application handles delays in network connectivity from containers to dependent services.
- Verifying the resilience of your system when containers experience slow responses from dependent services.
- Evaluating the impact of HTTP latency on the performance and availability of your application.
ECS container HTTP modify body
ECS container HTTP modify body injects HTTP chaos which affects the request or response by modifying the status code, body, or headers. This is achieved by starting a proxy server and redirecting the traffic through the proxy server.
Use cases
- Tests the application's resilience to erroneous (or incorrect) HTTP response body.
- Tests the resilience of the ECS application container to erroneous or incorrect HTTP response body.
ECS container HTTP modify header
ECS container HTTP modify header injects HTTP chaos which modifies the headers of the request or response of the service.
- This is achieved by starting a proxy server and redirecting the traffic through the proxy server.
- This experiment induces chaos within a container and depends on an EC2 instance. Typically, these are prefixed with "ECS container" and involve direct interaction with the EC2 instances hosting the ECS containers.
Use cases
ECS container HTTP modify header tests the resilience of the ECS application container to erroneous or incorrect HTTP header of the request or response body.
ECS container HTTP reset peer
ECS container HTTP reset peer injects HTTP reset on the service whose port is specified using the TARGET_SERVICE_PORT environment variable.
- It stops the outgoing HTTP requests by resetting the TCP connection for the requests.
Use cases
- It determines the application's resilience to a lossy (or flaky) HTTP connection.
- Simulates premature connection loss (firewall issues or other issues) between microservices (verify connection timeout).
- Simulates connection resets due to resource limitations on the server side like out of memory server (or process killed or overload on the server due to a high amount of traffic).
ECS container HTTP status code
ECS container HTTP status code injects HTTP chaos that affects the request (or response) by modifying the status code (or the body or the headers) by starting a proxy server and redirecting the traffic through the proxy server on the target ECS containers.
Use cases
- Tests the ECS task container resilience to erroneous code HTTP responses from the application server.
- Simulates unavailability of specific API services (503, 404), unavailability of specific APIs for(or from) a given microservice (TBD or Path Filter) (404).
- Simulates unauthorized requests for 3rd party services (401 or 403), and API malfunction (internal server error) (50x) on ECS task container.
ECS container IO stress
ECS container IO stress disrupts the state of infrastructure resources. It induces stress on the AWS ECS container using Amazon SSM Run command, which is carried out using SSM docs which is in-built into the fault.
- It causes I/O stress on the containers of the ECS task using the given
CLUSTER_NAMEenvironment variable for a specific duration. - To select the Task Under Chaos (TUC), use the service name associated with the task. If you provide the service name along with the cluster name, all the tasks associated with the given service will be selected as chaos targets.
- It tests the ECS task sanity (service availability) and recovery of the task containers subject to I/O stress.
- This experiment induces chaos within a container and depends on an EC2 instance. Typically, these are prefixed with "ECS container" and involve direct interaction with the EC2 instances hosting the ECS containers.
Use cases
- Determines how a container recovers from a memory exhaustion.
- File system read and write evicts the application (task container) and impacts its delivery. These issues are also known as noisy-neighbour problems.
- Injecting a rogue process into a target container starves the main microservice process (typically pid 1) of the resources allocated to it (where the limits are defined). This slows down the application traffic or exhausts the resources leading to eviction of all task containers.
ECS container memory hog
ECS container memory hog disrupts the state of infrastructure resources. It induces stress on the AWS ECS container using Amazon SSM Run command, which is carried out using SSM docs which is in-built into the fault.
- It causes memory stress on the containers of the ECS task using the given
CLUSTER_NAMEenvironment variable for a specific duration. - To select the Task Under Chaos (TUC), use the service name associated with the task. If you provide the service name along with the cluster name, all the tasks associated with the given service will be selected as chaos targets.
- It tests the ECS task sanity (service availability) and recovery of the task containers subject to memory stress.
Details
Use cases
Memory usage inside containers is subject to constraints. If the limits are specified, exceeding them can result in termination of the container (due to OOMKill of the primary process, often pid 1). The container is restarted, depending on the policy specified. When there are no limits on the memory consumption of containers, containers on the instance can be killed based on their oom_score, which extends to all the task containers running on the instance. This results in a bigger blast radius. This fault launches a stress process within the target container, that causes the primary process in the container to have constraints based on resources or eat up the available system memory on the instance when limits on resources are not specified.ECS container network latency
ECS container network latency disrupts the state of infrastructure resources. It brings delay on the AWS ECS container using Amazon SSM Run command, which is carried out using SSM docs which is in-built into the fault.
- It causes network stress on the containers of the ECS task using the given
CLUSTER_NAMEenvironment variable for a specific duration. - To select the Task Under Chaos (TUC), use the service name associated with the task. If you provide the service name along with the cluster name, all the tasks associated with the given service will be selected as chaos targets.
- It tests the ECS task sanity (service availability) and recovery of the task containers subject to network stress.
Details
Use cases
This fault degrades the network of the task container without the container being marked as unhealthy/ (or unworthy) of traffic. It simulates issues within the ECS task network or communication across services in different availability zones (or regions). This can be resolved using middleware that switches traffic based on certain SLOs (or performance parameters). This can also be resolved by highlighting the degradation using notifications (or alerts). It also determines the impact of the fault on the microservice. The task may stall or get corrupted while waiting endlessly for a packet. The fault limits the impact (blast radius) to only the traffic you wish to test by specifying the service to find TUC (Task Under Chaos). This fault helps improve the resilience of the services over time.ECS container network loss
ECS container network loss disrupts the state of infrastructure resources.
- The fault induces chaos on the AWS ECS container using Amazon SSM Run command, which is carried out using SSM docs that comes in-built in the fault.
- It causes network disruption on containers of the ECS task in the cluster name.
- To select the Task Under Chaos (TUC), use the service name associated with the task. If you provide the service name along with cluster name, all the tasks associated with the given service will be selected as chaos targets.
- It tests the ECS task sanity (service availability) and recovery of the task containers subjected to network chaos.
Details
Use cases
This fault degrades the network of the task container without the container being marked as unhealthy/ (or unworthy) of traffic. It simulates issues within the ECS task network or communication across services in different availability zones (or regions). This can be resolved using middleware that switches traffic based on certain SLOs (or performance parameters). This can also be resolved by highlighting the degradation using notifications (or alerts). It also determines the impact of the fault on the microservice. The task may stall or get corrupted while waiting endlessly for a packet. The fault limits the impact (blast radius) to only the traffic you wish to test by specifying the service to find TUC (Task Under Chaos). It simulates degraded network with varied percentages of dropped packets between microservices, loss of access to specific third party (or dependent) services (or components), blackhole against traffic to a given AZ (failure simulation of availability zones), and network partitions (split-brain) between peer replicas for a stateful application. This fault helps improve the resilience of the services over time.ECS container volume detach
ECS container volume detach provides a mechanism to detach and remove volumes associated with ECS task containers in an Amazon ECS (Elastic Container Service) task. This experiment primarily involves ECS Fargate and doesn't depend on EC2 instances. They focus on altering the state or resources of ECS containers without direct container interaction.
Use cases
- Allows you to test and validate the behavior of your ECS tasks when volumes are detached. You can verify the resilience and performance of your application during volume detachment scenarios, ensuring that the containers continue to function as expected.
- By detaching volumes, you can safely remove the volume associations from the containers without deleting the volumes themselves.
- By detaching unnecessary volumes, you can optimize the resource utilization within your ECS tasks. This helps to free up storage space and minimize any potential performance impact associated with unused volumes.
ECS Fargate CPU Hog
ECS Fargate CPU Hog generates high CPU load on a specific task running in an ECS service.
Use cases
- Simulates a scenario where a task consumes excessive CPU resources, impacting the performance of other main container in the task.
- Tests the slowness and resource allocation capabilities of the ECS Fargate task.
- Testing the ability of the ECS Fargate task to handle CPU-intensive workloads and dynamically allocate resources.
- Evaluating the impact of resource contention on other container running in the task.
ECS Fargate memory hog
ECS Fargate memory hog generates high CPU load on a specific task running in an ECS service.
Use cases
- Simulates a scenario where a task consumes excessive CPU resources, impacting the performance of other main container in the task.
- Tests the slowness and resource allocation capabilities of the ECS Fargate task.
- Testing the ability of the ECS Fargate task to handle CPU-intensive workloads and dynamically allocate resources.
- Evaluating the impact of resource contention on other container running in the task.
ECS instance stop
ECS instance stop induces stress on an AWS ECS cluster. It derives the instance under chaos from the ECS cluster.
- It causes EC2 instance to stop and get deleted from the ECS cluster for a specific duration.
Details
Use cases
EC2 instance stop breaks the agent that manages the task container on ECS cluster, thereby impacting its delivery. Killing the EC2 instance disrupts the performance of the task container.ECS invalid container image
ECS invalid container image allows you to update the Docker image used by a container in an Amazon ECS (Elastic Container Service) task.
Use cases
- Tests the behavior of your ECS tasks when the container images are updated, and validates the resilience and performance of your ECS tasks during image updates.
- Updates the Docker image of a container by modifying the task definition associated with the ECS service or task.
- Simulates scenarios where container images are updated, that may impact the behavior of your application or infrastructure. For example, you can update the Docker image of a container to a newer version or a different image to test how your application handles image updates.
- Validates the behavior of your application and infrastructure during simulated container image updates, such as:
- Testing the resilience of your system during image updates, including verifying if the updated image is pulled successfully and if the container starts with the new image.
- Validating the performance and availability of your application after container image updates, including checking if the updated image performs as expected and if there are any issues with the new image.
ECS network restrict
ECS network restrict allows you to restrict the network connectivity of containers in an Amazon ECS (Elastic Container Service) task by modifying the container security rules.
Use cases
- Tests the resilience and performance of your ECS tasks when network access is restricted.
- Validates the behavior of your application in a restricted networking environment.
- Restricts the network connectivity of containers by modifying the container security rules associated with the ECS task.
- Simulates scenarios where network access is restricted, which may impact the behavior of your application or infrastructure. For example, you can restrict outgoing internet access from containers to test how your application handles restricted networking environments or to validate the behavior of your application when certain network resources are not accessible.
- Validates the behavior of your application and infrastructure during simulated network restrictions, such as:
- Testing the resilience of your system when network access is restricted, including verifying if the containers can communicate with each other or with external resources when certain network restrictions are in place.
- Validating the performance and availability of your application in a restricted networking environment, including checking if the application can continue to function properly with limited network access.
ECS task scale
ECS task scale is an AWS fault that injects chaos to scale (up or down) the ECS tasks based on the services and checks the task availability. This fault affects the availability of a task in an ECS cluster.
Details
Use cases
ECS task scale affects the availability of a task in a cluster. It determines the resilience of an application when ECS tasks are unexpectedly scaled up (or down).ECS task stop
ECS task stop is an AWS fault that injects chaos to stop the ECS tasks based on the services or task replica ID and checks the task availability.
- This fault results in the unavailability of the application running on the tasks.
Details
Use cases
This fault determines the resilience of an application when ECS tasks unexpectedly stop due to task being unavailable.ECS update container resource limit
ECS update container resource limit allows you to modify the CPU and memory resources of containers in an Amazon ECS (Elastic Container Service) task.
Use cases
- Determines the behavior of your ECS tasks when their resource limits are changed.
- Verifies the scalability and resilience of your ECS tasks under different resource configurations.
- Modifies the resource limits of a container by updating the task definition associated with the ECS service or task.
- Simulates scenarios where containers experience changes in their allocated resources, which may affect their performance or availability. For example, you can increase or decrease the CPU or memory limits of a container to test how your application adapts to changes in resource availability.
- Validates the behavior of your application and infrastructure during simulated resource limit changes, such as:
- Testing how your application scales up or down in response to changes in CPU or memory limits.
- Verifying the resilience of your system when containers are running with lower resource limits.
- Evaluating the impact of changes in resource limits on the performance and availability of your application.
ECS update container timeout
ECS update container timeout modifies the start and stop timeout for ECS containers in Amazon ECS clusters. It allows you to specify the duration for which the containers should be allowed to start or stop before they are considered as failed.
Use cases
- Tests the resilience of ECS tasks and their containers to timeouts during updates or deployments.
- Verifies the behavior of ECS tasks and their containers when the start or stop timeout is exceeded during updates or deployments.
- Tests the recovery mechanisms of the ECS service and container instances in case of timeouts.
- Simulates scenarios where containers take longer than expected to start or stop.
- Evaluates the impact of above-mentioned scenarios on the overall application availability and performance.
ECS update task role
ECS update task role allows you to modify the IAM task role associated with an Amazon ECS (Elastic Container Service) task.
Use cases
- Determines the behavior of your ECS tasks when their IAM role is changed.
- Verifies the authorization and access permissions of your ECS tasks under different IAM configurations.
- Modifies the IAM task role associated with a container task by updating the task definition associated with the ECS service or task.
- Simulate scenarios where the IAM role associated with a task is changed, which may impact the authorization and access permissions of the containers running in the task.
- Validates the behavior of your application and infrastructure during simulated IAM role changes, such as:
- Testing how your application handles changes in IAM role permissions and access.
- Verifying the authorization settings of your system when the IAM role is updated.
- Evaluating the impact of changes in IAM roles on the security and compliance of your application.
Generic experiment template
Generic experiment template provides a template to natively inject faults using FIS for different services, such as EC2, EBS, DynamoDB, and so on.
- You need to create an FIS template and store it.
- Provide parameters to the pre-created FIS templates and execute experiments.
- You can specify the template ID and region on Harness to execute the experiments using these FIS templates.
- You can monitor and report the results of executing the experiment from these FIS templates.
Use cases
- Inject faults natively using FIS services.
- Monitor and report the results of executing the experiment from the FIS templates.
- Build chaos experiments with pre-defined templates or build experiments from scratch using FIS service.
Lambda delete event source mapping
Lambda delete event source mapping removes the event source mapping from an AWS Lambda function for a specific duration. Deleting an event source mapping from a Lambda function is critical. It can lead to failure in updating the database on an event trigger, which can break the service.
Use cases
- Determines the performance of the application (or service) without the event source mapping that may cause missing entries in a database.
- Determines whether proper error handling or auto-recovery options have been configured for the application.
Lambda delete function concurrency
Lambda delete function concurrency deletes the Lambda function's reserved concurrency, thereby ensuring that the function has adequate unreserved concurrency to run.
Use cases
- Lambda delete function concurrency examines the performance of the running Lambda application, if the Lambda function lacks sufficient concurrency.
Lambda toggle event mapping state
Lambda toggle event mapping state toggles (or sets) the event source mapping state to disable for a Lambda function during a specific duration. Toggling between different states of event source mapping from a Lambda function may lead to failures when updating the database on an event trigger. This can break the service and impact its delivery.
Use cases
- Checks the performance of the running application when the event source mapping is not enabled. This may cause missing entries in a database.
- Determines if the application has proper error handling or auto recovery actions configured.
Lambda update function memory
Lambda update function memory causes the memory of a Lambda function to update to a specific value for a certain duration. This fault:
- Determines a safe overall memory limit value for the function. Smaller the memory limit, higher will be the time taken by the Lambda function under load.
Use cases
- Helps build resilience to unexpected scenarios such as hitting a memory limit with the Lambda function, that slows down the service and impacts its delivery. Running out of memory due to smaller limits interrupts the flow of the given function.
- Checks the performance of the application (or service) running with a new memory limit.
Lambda update function timeout
Lambda update function timeout causes a timeout of a Lambda function, thereby updating the timeout to a specific value for a certain duration. Timeout errors interrupt the flow of the given function. Hitting a timeout is a frequent scenario with Lambda functions. This can break the service and impact the delivery. Such scenarios can occur despite the availability aids provided by AWS.
Use cases
- Checks the performance of the application (or service) running with a new timeout.
- Determines a safe overall timeout value for the function.
Lambda update role permission
Lambda update role permission is an AWS fault that modifies the role policies associated with a Lambda function. Sometimes, Lambda functions depend on services like RDS, DynamoDB, and S3. In such cases, certain permissions are required to access these services. This fault helps understand how your application would behave when a Lambda function does not have enough permissions to access the services.
Use cases
- Verifies the handling mechanism for function failures.
- Updates the role attached to a Lambda function.
- Determines the performance of the running Lambda application when it does not have enough permissions.
NLB AZ down
NLB AZ down takes down the access for AZ (Availability Zones) on a target network load balancer for a specific duration. This fault restricts access to certain availability zones for a specific duration.
Use cases
- Tests the application's ability to handle the loss of availability zones and maintain uninterrupted traffic flow.
- NLB AZ down fault disrupts the traffic routing through the network load balancer, testing the application's resilience to AZ failures.
- Simulating network failures and verifying the application's ability to recover and redirect traffic appropriately.
RDS instance delete
RDS instance delete removes an instances from AWS RDS cluster.
- This makes the cluster unavailable for a specific duration.
- It determines how quickly an application can recover from an unexpected cluster deletion.
Use cases
- This fault determines how quickly an application can recover from an unexpected RDS cluster deletion.
RDS instance reboot
RDS instance reboot can induce an RDS instance reboot chaos on AWS RDS cluster. It derives the instance under chaos from RDS cluster.
Use cases
- This fault determines the resilience of an application to RDS instance reboot.
Resource access restrict
Resource access restrict restricts access to a specific AWS resource for a specific duration.
Use cases
- Tests the application's resiliency and error handling when access to a critical AWS resource is restricted.
- Validates the application's ability to handle and recover from temporary resource unavailability.
- Test the application's response to restricted access to AWS resources, such as ec2, database storage.
- Evaluate the application's error handling and recovery mechanisms in the face of resource unavailability.
SSM chaos by ID
AWS SSM chaos by ID induces chaos on AWS EC2 instances using the Amazon SSM Run Command.
- It is executed using the SSM document that defines the actions which the systems manager can perform on your managed instances (that have SSM agent installed).
- This SSM document is uploaded beforehand to AWS, whose name is referenced in the faults.
- It helps execute custom chaos (like stress, network, disk or IO) on AWS EC2 instances for a specific duration using the given ID(s).
Use cases
AWS SSM chaos by ID:
- Tests the resilience of an application that uses custom SSM document as input to execute chaos on EC2 instances.
- Triggers the provided SSM document provided as an input to other AWS chaos.
- After chaos, this fault cleans up the SSM document provided as an input to the EC2 instance.
SSM chaos by tag
AWS SSM chaos by tag induces chaos on AWS EC2 instances using the Amazon SSM Run Command.
- It is executed using the SSM document that defines the actions which the systems manager can perform on your managed instances (that have SSM agent installed).
- This SSM document is uploaded beforehand to AWS, whose name is referenced in the faults.
- It helps execute custom chaos (like stress, network, disk or IO) on AWS EC2 instances for a specific duration using the given tag(s).
Use cases
AWS SSM chaos by tag:
- Tests the resilience of an application that uses custom SSM document as input to execute chaos on EC2 instances.
- Triggers the provided SSM document provided as an input to other AWS chaos.
- After chaos, this fault cleans up the SSM document provided as an input to the EC2 instance.
Windows EC2 blackhole chaos
Windows EC2 blackhole chaos results in access loss to the given target hosts or IPs by injecting firewall rules.
Use cases
Windows EC2 blackhole chaos:
- Degrades the network without the EC2 instance being marked as unhealthy (or unworthy) of traffic. This can be resolved by using a middleware that switches the traffic based on certain SLOs (performance parameters).
- Limits the impact, that is, blast radius to only the traffic that you wish to test, by specifying the destination hosts or IP addresses.
Windows EC2 CPU hog
Windows EC2 CPU hog induces CPU stress on the AWS Windows EC2 instances using Amazon SSM Run command.
Use cases
EC2 windows CPU hog:
- Simulates the situation of a lack of CPU for processes running on the instance, which degrades their performance.
- Simulates slow application traffic or exhaustion of the resources, leading to degradation in the performance of processes on the instance.
Windows EC2 memory hog
Windows EC2 memory hog induces memory stress on the target AWS Windows EC2 instance using Amazon SSM Run command.
Use cases
Windows EC2 memory hog:
- Causes memory stress on the target AWS EC2 instance(s).
- Simulates the situation of memory leaks in the deployment of microservices.
- Simulates application slowness due to memory starvation, and noisy neighbour problems due to hogging.