Senior LevelCloud Computing (AWS/GCP/Azure)
How do you execute Chaos Engineering experiments using AWS Fault Injection Simulator (FIS)?
❓ Interview Prompt: Explain Chaos Engineering principles, AWS Fault Injection Simulator (FIS), steady-state hypothesis, and controlled fault injection.
Chaos Engineering is the discipline of experimenting on a system to build confidence in its capability to withstand turbulent conditions in production.
AWS Fault Injection Simulator (FIS) Architecture:
1
Steady-State Hypothesis: Define measurable metrics proving normal system operation (e.g. HTTP 200 rate > 99.9%, Latency < 100ms).
2
Target Selection: Specify targets (EC2 instances, EKS pods, RDS databases, ASGs).
3
Action Injection: Inject real controlled faults:
•
Terminate random EC2 instances in an ASG.
•
Inject 500ms network latency on VPC ENIs.
•
Trigger RDS Primary failover.
4
Stop Conditions: CloudWatch alarms automatically abort the experiment if steady-state metrics breach safety thresholds!
Code Implementation Example
hcl
# AWS FIS Experiment Template injecting CPU stress fault
resource "aws_fis_experiment_template" "cpu_stress" {
description = "Inject CPU stress on staging workers"
role_arn = aws_iam_role.fis_role.arn
action {
name = "cpu-stress-action"
action_id = "aws:ec2:send-spot-instance-interruptions"
target { key = "Instances"; value = "app-instances" }
}
target {
name = "app-instances"
resource_type = "aws:ec2:instance"
selection_mode = "PERCENT(50)"
}
stop_condition {
source = "aws:cloudwatch:alarm"
value = aws_cloudwatch_metric_alarm.error_rate_alarm.arn
}
}💡Terraform AWS FIS experiment template injecting Spot interruptions with CloudWatch stop condition.
🎯 Interview Key Takeaway
AWS FIS injects controlled faults (instance crashes, network latency) to validate system self-healing resilience against CloudWatch stop conditions.
#Chaos Engineering#AWS FIS#Resilience#Testing#Senior
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