Best Practice: Chaos Engineering & Fault Injection

# chaos-experiments/exp-001-az-failure.yml
id: "EXP-001"
title: "Single AZ Instance Termination"
hypothesis: "Payment API continues serving requests with < 10% error rate when 25% of instances in AZ1 are terminated"
date: "2026-03-15"
team: "payments-team"
environment: "staging"

scope:
  service: "payment-api"
  blast_radius: "25% of instances in eu-west-1a"
  excluded: ["payment-db", "payment-queue"]

stop_conditions:
  - "SLO error rate > 2% for > 2 minutes"
  - "All circuit breakers in OPEN state"

expected_result:
  recovery_time: "< 60 seconds"
  error_rate_peak: "< 5%"
  slo_violation: false

observations:
  start_time: "14:00"
  actual_recovery_time: "42 seconds"
  actual_error_rate_peak: "2.3%"
  slo_violation: false
  issues_found:
    - "Startup probe initialDelaySeconds too short – 3 pods restarted unnecessarily"

actions:
  - id: "ACT-001"
    description: "Increase initialDelaySeconds from 10s to 20s"
    owner: "alice"
    due_date: "2026-03-22"
    status: "completed"

# terraform/chaos/fis-az-failure.tf

data "aws_iam_policy_document" "fis_assume" {
  statement {
    actions = ["sts:AssumeRole"]
    principals {
      type        = "Service"
      identifiers = ["fis.amazonaws.com"]
    }
  }
}

resource "aws_iam_role" "fis" {
  name               = "fis-execution-role"
  assume_role_policy = data.aws_iam_policy_document.fis_assume.json
}

resource "aws_iam_role_policy_attachment" "fis_ec2" {
  role       = aws_iam_role.fis.name
  policy_arn = "arn:aws:iam::aws:policy/AmazonEC2FullAccess"
}

# Stop Condition: SLO-Alarm löst aus
resource "aws_cloudwatch_metric_alarm" "fis_stop_condition" {
  alarm_name          = "fis-stop-condition-error-rate"
  comparison_operator = "GreaterThanThreshold"
  evaluation_periods  = 2
  metric_name         = "5XXError"
  namespace           = "AWS/ApiGateway"
  period              = 60
  statistic           = "Sum"
  threshold           = 50  # 50 Fehler/min = ~0.8% bei 6k req/min
}

# Experiment: 25% der Instanzen in AZ1 terminieren
resource "aws_fis_experiment_template" "az1_instance_termination" {
  description = "EXP-001: Terminate 25% of instances in AZ1 – validate auto-recovery < 60s"
  role_arn    = aws_iam_role.fis.arn

  stop_condition {
    source = "aws:cloudwatch:alarm"
    value  = aws_cloudwatch_metric_alarm.fis_stop_condition.arn
  }

  action {
    name      = "terminate-instances-az1"
    action_id = "aws:ec2:terminate-instances"

    parameter {
      key   = "startInstancesAfterDuration"
      value = "PT0S"  # Nicht auto-restart
    }

    target {
      key   = "Instances"
      value = "payment-api-instances-az1"
    }
  }

  target {
    name           = "payment-api-instances-az1"
    resource_type  = "aws:ec2:instance"
    selection_mode = "PERCENT(25)"

    resource_tag {
      key   = "app"
      value = "payment-api"
    }

    resource_tag {
      key   = "aws:autoscaling:groupName"
      value = "payment-api-asg"
    }

    filter {
      path   = "Placement.AvailabilityZone"
      values = ["eu-west-1a"]
    }
  }

  tags = merge(var.mandatory_tags, {
    "chaos-experiment" = "EXP-001"
    "environment"      = "staging"
  })
}

resource "azurerm_chaos_studio_experiment" "pod_failure" {
  name                = "payment-api-pod-failure-staging"
  location            = azurerm_resource_group.staging.location
  resource_group_name = azurerm_resource_group.staging.name

  identity {
    type = "SystemAssigned"
  }

  schema_version = "2.0"

  steps {
    name = "pod-failure-step"

    branches {
      name = "inject-pod-failure"

      actions {
        action_urn = "urn:csci:microsoft:azureKubernetesServiceChaosMesh:podChaos/2.2"
        duration   = "PT5M"

        parameters {
          key   = "jsonSpec"
          value = jsonencode({
            mode   = "one"
            action = "pod-kill"
            selector = {
              namespaces = ["payment"]
              labelSelectors = { "app" = "payment-api" }
            }
          })
        }

        target {
          id   = azurerm_chaos_studio_target.aks.id
          type = "ChaosTarget"
        }
      }
    }
  }
}

# GameDay: Payment Service Reliability – Q1 2026

**Datum:** 2026-03-21
**Dauer:** 4 Stunden (09:00–13:00)
**Team:** payments-team (8 Personen)
**Moderator:** @alice
**Observer:** @bob (Engineering Manager)

## 09:00 – Briefing (30 Min)
- Tagesablauf erklären
- Rollen zuweisen: Chaos-Operator, Incident Commander, Observer
- Dashboards öffnen, Baseline messen

## 09:30 – Experiment 1: Single Pod Failure (EXP-001)
- Hypothese: Service recovered in < 30s
- Tool: kubectl delete pod (ein Pod)
- Erwartung: Keine SLO-Verletzung

## 10:00 – Experiment 2: Database Connection Flood (EXP-002)
- Hypothese: Circuit Breaker öffnet bei > 80% DB-Fehlerrate
- Tool: AWS FIS – blockiere Security Group Rule zur DB
- Stop Condition: SLO-Alarm

## 10:30 – Pause & Analyse (30 Min)

## 11:00 – Experiment 3: AZ-Level Failure (EXP-003)
- Hypothese: Service recovered in < 60s nach 25% Instanz-Terminierung in AZ1
- Tool: AWS FIS Experiment Template az1_instance_termination
- Beobachte: Auto Scaling, LB Health Checks

## 12:00 – Retrospektive (60 Min)
- Was haben wir gelernt?
- Welche Hypothesen haben sich bestätigt / widerlegt?
- Action Items dokumentieren

## 13:00 – Ende