digraph execute_flow {
    "Load experiment directory" [shape=box];
    "Validate files" [shape=box];
    "Choose deployment method" [shape=diamond];
    "CLI deployment" [shape=box];
    "CFN deployment" [shape=box];
    "User confirms deployment" [shape=diamond];
    "Deploy resources" [shape=box];
    "User confirms experiment start" [shape=diamond, style=bold, color=red];
    "Start experiment" [shape=box];
    "Monitor experiment" [shape=box];
    "Experiment complete?" [shape=diamond];
    "Generate results report" [shape=box];

    "Load experiment directory" -> "Validate files";
    "Validate files" -> "Choose deployment method";
    "Choose deployment method" -> "CLI deployment" [label="CLI"];
    "Choose deployment method" -> "CFN deployment" [label="CFN"];
    "CLI deployment" -> "User confirms deployment";
    "CFN deployment" -> "User confirms deployment";
    "User confirms deployment" -> "Deploy resources" [label="Yes"];
    "User confirms deployment" -> "Load experiment directory" [label="No, abort"];
    "Deploy resources" -> "User confirms experiment start";
    "User confirms experiment start" -> "Start experiment" [label="Yes, I confirm"];
    "User confirms experiment start" -> "Generate results report" [label="No, abort"];
    "Start experiment" -> "Monitor experiment";
    "Monitor experiment" -> "Experiment complete?" ;
    "Experiment complete?" -> "Monitor experiment" [label="No, poll again"];
    "Experiment complete?" -> "Generate results report" [label="Yes"];
}

EXPERIMENT_DIR="{USER_PROVIDED_PATH}"

Read `README.md` to understand the experiment and present a summary to the user:
- Scenario name
- Target region and AZ
- Affected resources
- Estimated duration

undefined

**3b. Create CloudWatch Alarms (Stop Conditions)**

Read `alarms/stop-condition-alarms.json` and create each alarm:

```bash
aws cloudwatch put-metric-alarm --cli-input-json '{...}' --region {REGION}

aws cloudwatch put-dashboard \
  --dashboard-name "FIS-{SCENARIO}" \
  --dashboard-body "file://${EXPERIMENT_DIR}/alarms/dashboard.json" \
  --region {REGION}

aws fis create-experiment-template \
  --cli-input-json "file://${EXPERIMENT_DIR}/experiment-template.json" \
  --region {REGION}

aws cloudformation deploy \
  --template-file "${EXPERIMENT_DIR}/cfn-template.yaml" \
  --stack-name "fis-{SCENARIO}-{TIMESTAMP}" \
  --capabilities CAPABILITY_NAMED_IAM \
  --region {REGION}

aws cloudformation wait stack-create-complete \
  --stack-name "fis-{SCENARIO}-{TIMESTAMP}" \
  --region {REGION}

TEMPLATE_ID=$(aws cloudformation describe-stacks \
  --stack-name "fis-{SCENARIO}-{TIMESTAMP}" \
  --query 'Stacks[0].Outputs[?OutputKey==`ExperimentTemplateId`].OutputValue' \
  --output text --region {REGION})

⚠️  WARNING: Starting this FIS experiment will cause REAL impact:

Scenario:    {SCENARIO_NAME}
Region:      {REGION}
Target AZ:   {AZ_ID}
Duration:    {DURATION}

Resources that WILL be affected:
  - {list each affected resource type and count}

Stop Conditions:
  - {list each alarm that will stop the experiment}

Type "Yes, start experiment" to proceed, or "No" to abort.

aws fis start-experiment \
  --experiment-template-id "{TEMPLATE_ID}" \
  --region {REGION}

aws fis get-experiment \
  --id "{EXPERIMENT_ID}" \
  --region {REGION} \
  --query '{
    State: experiment.state.status,
    Reason: experiment.state.reason,
    StartTime: experiment.startTime,
    EndTime: experiment.endTime,
    Actions: experiment.actions
  }'

TIMESTAMP=$(date +%Y-%m-%d-%H-%M-%S)
SCENARIO_SLUG=$(echo "{SCENARIO_NAME}" | tr '[:upper:]' '[:lower:]' | tr ' :/' '-')

**Timeline emphasis:** Timestamps in the report header (Start Time, End Time) use full
ISO 8601 with timezone (e.g., `2025-03-30T14:05:32+08:00`). However, in timeline tables
and action results, use **time-only format in UTC** (e.g., `05:05:32`) — the report date
is already in the header, so repeating the date on every row adds clutter. Mark the
column header as "Time (UTC)" so the timezone is clear. No milliseconds anywhere. Timeline events are embedded directly
into each service's impact analysis section — do NOT create a separate standalone
timeline section. This allows readers to see the full picture (timeline + impact +
findings) for each service without jumping between sections.

**Per-service analysis:** Read `expected-behavior.md` from the experiment directory to
identify all services under test. For each service, create a sub-section under
"Per-Service Impact Analysis" that includes: (1) the timeline events relevant to that
service, (2) observed behavior from monitoring, (3) key findings. Also check for
indirectly affected services (e.g., MSK affected by network disruption) and include
them.

The results report file must include:

```markdown

After saving the file, print a brief summary to the terminal listing only:
- The file path of the saved results report
- Experiment ID and final status
- Start time, end time, and duration (all timestamps in ISO 8601 with timezone)
- Per-action status (one line each)
- Per-service recovery status (one line each)
- Issues requiring attention (if any)
- Cleanup instructions

undefined

undefined

aws cloudformation delete-stack --stack-name "fis-{SCENARIO}-{TIMESTAMP}" --region {REGION}