#!/usr/bin/env bash
set -euo pipefail

# ==============================================================================
# End-to-End Local Cloud Production Environment Simulation
# Emulates:
# 1. Amazon SNS / EventBridge (Floci Topic)
# 2. AWS Lambda Function (dispatcher.py)
# 3. AWS ECS / Fargate Task (ephemeral docker container with --rm)
# 4. Headless Execution (evidence, policy, repro, diff)
# 5. Audit & Tear Down (S3 bucket archival & CloudWatch logging, immediate termination)
# ==============================================================================

SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
SIM_DIR="$(cd "${SCRIPT_DIR}/.." && pwd)"
PROJECT_ROOT="$(cd "${SIM_DIR}/../.." && pwd)"

COMPOSE_FILE="${SIM_DIR}/docker-compose.cloud.yml"
ENDPOINT_URL="http://localhost:4568"
CONTAINER_ENDPOINT="http://personal-lifecycle-cloud-emulator:4566"
S3_BUCKET="lifecycle-on-call-incidents"
SNS_TOPIC="on-call-alerts"
AWS_REGION="us-east-1"

export AWS_ACCESS_KEY_ID="test"
export AWS_SECRET_ACCESS_KEY="test"
export AWS_DEFAULT_REGION="${AWS_REGION}"

echo "================================================================"
echo "    LOCAL SIMULATION OF CLOUD PRODUCTION ON-CALL PIPELINE      "
echo "================================================================"
echo "1. Cloud Emulator:   Amazon SNS, EventBridge, S3, CloudWatch"
echo "2. Serverless:       AWS Lambda (dispatcher.py)"
echo "3. Container Task:   AWS ECS / Fargate (ephemeral --rm container)"
echo "4. Agent Execution:  Headless triage loop"
echo "5. Audit & Cleanup:  S3 archival & immediate container termination"
echo "================================================================"
echo ""

# 1. Start Local Cloud Emulator
echo "==> [STEP 1] Starting local cloud emulator (Floci S3/SNS) on port 4568..."
docker compose -f "${COMPOSE_FILE}" up -d
echo "==> Waiting for cloud emulator to report healthy..."
for i in $(seq 1 30); do
  if curl -sf "${ENDPOINT_URL}/_floci/health" >/dev/null 2>&1; then
    echo "[x] Cloud emulator is healthy and ready."
    break
  fi
  sleep 1
done

# Ensure network connectivity to observability network
docker network connect personal-lifecycle-observability-net personal-lifecycle-cloud-emulator 2>/dev/null || true

# 2. Provision AWS Cloud Infrastructure in Emulator
echo ""
echo "==> [STEP 2] Provisioning AWS Cloud resources (S3 Bucket & SNS Topic)..."
# Create S3 Bucket
docker run --rm \
  --network personal-lifecycle-observability-net \
  -e AWS_ACCESS_KEY_ID=test \
  -e AWS_SECRET_ACCESS_KEY=test \
  -e AWS_DEFAULT_REGION="${AWS_REGION}" \
  amazon/aws-cli:latest \
  --endpoint-url "${CONTAINER_ENDPOINT}" \
  s3 mb "s3://${S3_BUCKET}" 2>/dev/null || true
echo "[x] S3 Bucket provisioned: s3://${S3_BUCKET}"

# Create SNS Topic
TOPIC_ARN=$(docker run --rm \
  --network personal-lifecycle-observability-net \
  -e AWS_ACCESS_KEY_ID=test \
  -e AWS_SECRET_ACCESS_KEY=test \
  -e AWS_DEFAULT_REGION="${AWS_REGION}" \
  amazon/aws-cli:latest \
  --endpoint-url "${CONTAINER_ENDPOINT}" \
  sns create-topic --name "${SNS_TOPIC}" --output text --query 'TopicArn')
echo "[x] Amazon SNS Topic provisioned: ${TOPIC_ARN}"

# 3. Publish Alert Event to Amazon SNS Topic
echo ""
echo "==> [STEP 3] Emulating Alertmanager / Monitoring triggering Amazon SNS..."
TIMESTAMP="$(date -u +"%Y-%m-%dT%H:%M:%SZ")"
ALERT_PAYLOAD=$(cat <<EOF
{
  "alert_name": "HighHttpErrorRate",
  "severity": "critical",
  "service_name": "api-backend",
  "deployment_environment": "production",
  "summary": "Elevated HTTP 5xx error rate on api-backend",
  "description": "5xx error rate exceeded 5% threshold (current: 100.0%)",
  "observed_value": 100.0,
  "threshold": 5.0,
  "timestamp": "${TIMESTAMP}"
}
EOF
)

MESSAGE_ID=$(docker run --rm \
  --network personal-lifecycle-observability-net \
  -e AWS_ACCESS_KEY_ID=test \
  -e AWS_SECRET_ACCESS_KEY=test \
  -e AWS_DEFAULT_REGION="${AWS_REGION}" \
  amazon/aws-cli:latest \
  --endpoint-url "${CONTAINER_ENDPOINT}" \
  sns publish \
  --topic-arn "${TOPIC_ARN}" \
  --message "${ALERT_PAYLOAD}" \
  --output text --query 'MessageId')
echo "[x] Alert published to Amazon SNS! Message ID: ${MESSAGE_ID}"

# 4. Trigger AWS Lambda Function
echo ""
echo "==> [STEP 4] Invoking AWS Lambda Function (Serverless Dispatcher)..."
SNS_EVENT=$(cat <<EOF
{
  "Records": [
    {
      "EventSource": "aws:sns",
      "EventVersion": "1.0",
      "EventSubscriptionArn": "${TOPIC_ARN}:sub-01",
      "Sns": {
        "MessageId": "${MESSAGE_ID}",
        "TopicArn": "${TOPIC_ARN}",
        "Message": $(echo "${ALERT_PAYLOAD}" | jq -c -R .)
      }
    }
  ]
}
EOF
)

# Run Lambda handler script
python3 "${SIM_DIR}/lambda/dispatcher.py"

# 5. Verify ECS / Fargate Ephemeral Container Termination
echo ""
echo "==> [STEP 5] Verifying ephemeral Fargate container lifecycle..."
ACTIVE_TASKS=$(docker ps --filter "name=fargate-task-" --format "{{.Names}}")
if [ -z "${ACTIVE_TASKS}" ]; then
  echo "[x] SUCCESS: Ephemeral Fargate container terminated and destroyed immediately upon task completion."
else
  echo "[!] Warning: Lingering task container detected: ${ACTIVE_TASKS}"
fi

# 6. Audit & Archival Verification in Amazon S3
echo ""
echo "==> [STEP 6] Verifying S3 Audit & Archival Bucket contents..."
echo "--- S3 Object Tree (s3://${S3_BUCKET}/) ---"
docker run --rm \
  --network personal-lifecycle-observability-net \
  -e AWS_ACCESS_KEY_ID=test \
  -e AWS_SECRET_ACCESS_KEY=test \
  -e AWS_DEFAULT_REGION="${AWS_REGION}" \
  amazon/aws-cli:latest \
  --endpoint-url "${CONTAINER_ENDPOINT}" \
  s3 ls "s3://${S3_BUCKET}/" --recursive

# 7. Print Sample Archived Diff & Transcript from S3
echo ""
echo "==> [STEP 7] Inspecting archived git diff from Amazon S3..."
docker run --rm \
  --network personal-lifecycle-observability-net \
  -e AWS_ACCESS_KEY_ID=test \
  -e AWS_SECRET_ACCESS_KEY=test \
  -e AWS_DEFAULT_REGION="${AWS_REGION}" \
  amazon/aws-cli:latest \
  --endpoint-url "${CONTAINER_ENDPOINT}" \
  s3 cp --quiet $(docker run --rm --network personal-lifecycle-observability-net -e AWS_ACCESS_KEY_ID=test -e AWS_SECRET_ACCESS_KEY=test amazon/aws-cli:latest --endpoint-url "${CONTAINER_ENDPOINT}" s3 ls "s3://${S3_BUCKET}/" --recursive | grep "diff.patch" | head -n1 | awk '{print "s3://'${S3_BUCKET}'/" $4}') -

echo ""
echo "================================================================"
echo "  LOCAL CLOUD PRODUCTION SIMULATION COMPLETED SUCCESSFULLY!     "
echo "  1. Alert ingested via Amazon SNS topic                       "
echo "  2. Lambda function processed event & launched Fargate task   "
echo "  3. Headless agent executed triage, evidence & diff creation  "
echo "  4. Transcript, diff & evidence archived to Amazon S3 bucket  "
echo "  5. Ephemeral compute container terminated immediately        "
echo "================================================================"