Gemini 3.5 Flash

# Incident Report & Remediation Plan: System-Wide Inventory Desynchronization

**Prepared by:** Senior AI Engineer & Reliability Lead  
**Status:** Active Incident / Mitigation Phase  
**Classification:** Technical Post-Mortem & Action Plan  

---

## 1. Incident Timeline

All times are in Local Standard Time (LST) / Local Daylight Time (LDT) for the library's timezone.

```
                  [01:00 AM LDT] First occurrence of the 01:00-02:00 hour begins.
                        │        Fiscal-week rollover batch job is queued.
                        ▼
                  [01:30 AM LDT] Event A: Book returned & processed at Quarantine Zone ("QZ-9").
                        │        Client records local timestamp: 2026-11-01 01:30:00.
                        ▼
                  [02:00 AM LDT] DST Fallback occurs. Clocks set back 1 hour to 01:00 AM LST.
                        │
                        ▼
                  [01:00 AM LST] Second occurrence of the 01:00-02:00 hour begins.
                        │
                        ▼
                  [01:15 AM LST] Event B: Book physically shelved on Floor 3 ("FL-3").
                        │        Client records local timestamp: 2026-11-01 01:15:00.
                        ▼
                  [01:30 AM LST] Event C: Book checked out manually (bypasses batch queue).
                        │        Direct write to transactional DB succeeds with correct UTC.
                        ▼
                  [02:00 AM LST] Fiscal-Week Rollover Batch Job Executes.
                        │        - Processes conflicting writes for the week.
                        │        - Collates local timestamps: Event A (01:30) vs Event B (01:15).
                        │        - Lexicographical tie-breaker favors "QZ-9" over "FL-3".
                        ▼
                  [02:15 AM LST] Shelving Robots refresh cached maps (47-minute TTL).
                                 - Robots read reconciled "QZ-9" status.
                                 - Robot begins sealing "FL-3" books in archival capsules.
```

---

## 2. Root Cause Analysis (RCA)

### Rank 1: Non-Monotonic Local Timestamps & Lexicographical Tie-Breaking (Confidence: 98%)
*   **Mechanism:** The client devices (RFID shelving robots, pneumatic tubes) record transaction timestamps using local wall-clock time without timezone offset metadata (e.g., `YYYY-MM-DD HH:MM:SS`). During a Daylight Saving Time (DST) fallback, the hour between 01:00:00 and 02:00:00 repeats. 
*   **The Bug:** When the weekly reconciliation job processes writes, it groups conflicts by Book ID and sorts them using a compound key: `(timestamp, location_token)`. Because of the DST fallback, a physically later write (e.g., 01:15 AM LST) is assigned a timestamp that appears *earlier* than a physically prior write (e.g., 01:30 AM LDT). If two writes land on the exact same local timestamp (e.g., 01:30 AM LDT and 01:30 AM LST), the sorting algorithm falls back to the second element of the tuple: the `location_token`.
*   **Why `QZ-9`?** The location token for the quarantine/archival zone is `QZ-9`. Standard floor tokens are formatted as `FL-01`, `FL-02`, etc. In ASCII/lexicographical sorting, `"QZ-9"` evaluates as greater than `"FL-XX"` (`'Q'` > `'F'`). Consequently, `QZ-9` always wins the tie-breaker, causing the reconciliation service to overwrite the active floor location with the archival status.

### Rank 2: 47-Minute Robot Map Cache Invalidation Lag (Confidence: 90%)
*   **Mechanism:** The shelving robots cache the library's spatial floor maps and book-to-shelf mappings for 47 minutes to reduce Wi-Fi congestion.
*   **The Bug:** When the reconciliation job corrupted the database state at 02:00 AM LST, the robots continued to navigate using stale, pre-reconciliation maps for up to 47 minutes. This created a split-brain scenario where the physical location of the books, the e-ink wayfinding signs, and the robots' internal routing tables diverged, leading to patrons being routed to incorrect floors.

### Rank 3: Manual Checkout Bypass (Confidence: 85%)
*   **Mechanism:** Manual checkouts write directly to the primary transactional database using UTC timestamps and bypass the batch reconciliation queue.
*   **The Bug:** This explains why manual checkouts remained accurate throughout the incident, confirming that the corruption was isolated to the batch reconciliation service and did not affect the real-time transactional database engine.

---

## 3. Minimal Python Reproduction

This script simulates the DST fallback overlap, the local timestamp collision, and the lexicographical sorting bug that causes the `QZ-9` override.

```python
import datetime
from typing import List, Dict, Any

class BookUpdate:
    def __init__(self, book_id: str, location: str, local_time_str: str, physical_sequence: int):
        self.book_id = book_id
        self.location = location
        # The bug: Storing time as a naive local string without offset
        self.timestamp = datetime.datetime.strptime(local_time_str, "%Y-%m-%d %H:%M:%S")
        self.physical_sequence = physical_sequence

    def __repr__(self):
        return f"Update(Loc: {self.location}, Time: {self.timestamp}, Seq: {self.physical_sequence})"

def buggy_reconcile(updates: List[BookUpdate]) -> Dict[str, Any]:
    """
    Reconciles conflicting writes by sorting lexicographically by timestamp,
    then by location token as a tie-breaker, taking the last element (LWW).
    """
    # Group updates by book_id
    grouped: Dict[str, List[BookUpdate]] = {}
    for u in updates:
        grouped.setdefault(u.book_id, []).append(u)
    
    reconciled = {}
    for book_id, update_list in grouped.items():
        # Bug: Sorting by naive timestamp, then lexicographically by location
        update_list.sort(key=lambda x: (x.timestamp, x.location))
        reconciled[book_id] = update_list[-1]  # Last-Write-Wins
    return reconciled

# --- Deterministic Test Case ---
if __name__ == "__main__":
    # Scenario: 
    # 1. Book is returned to Quarantine Zone (QZ-9) at 01:30 AM LDT (Physical Seq 1)
    # 2. DST Fallback occurs (clocks roll back 1 hour)
    # 3. Book is physically moved to Floor 3 (FL-3) at 01:15 AM LST (Physical Seq 2)
    
    updates = [
        BookUpdate(
            book_id="978-0142437179", 
            location="QZ-9", 
            local_time_str="2026-11-01 01:30:00", 
            physical_sequence=1
        ),
        BookUpdate(
            book_id="978-0142437179", 
            location="FL-3", 
            local_time_str="2026-11-01 01:15:00", 
            physical_sequence=2
        )
    ]
    
    result = buggy_reconcile(updates)
    reconciled_update = result["978-0142437179"]
    
    print("--- RECONCILIATION RESULTS ---")
    print(f"Expected Location (Physical Last): FL-3")
    print(f"Actual Reconciled Location:        {reconciled_update.location}")
    
    if reconciled_update.location == "QZ-9":
        print("\n[BUG TRIGGERED] The book was incorrectly routed to the Archival/Quarantine Zone (QZ-9)!")
        print("Reason: 'FL-3' < 'QZ-9' lexicographically, and the DST fallback broke timestamp monotonicity.")
    else:
        print("\n[SUCCESS] Reconciled correctly.")
```

---

## 4. Patch Plan

### Step 1: Enforce UTC at Ingestion
Modify the API gateway and client ingestion schemas to reject any payload that does not provide an ISO 8601 UTC timestamp (e.g., `2026-11-01T06:30:00Z`). Naive local timestamps will be rejected with a `400 Bad Request`.

### Step 2: Implement Monotonic Sequence IDs
Add an auto-incrementing, client-side sequence number (`sequence_id`) or a vector clock to all client updates. This guarantees physical ordering preservation even if clock synchronization fails.

### Step 3: Refactor the Reconciliation Sorting Logic
Rewrite the sorting key in the reconciliation service to use the UTC timestamp and the sequence ID. Remove the location token from the sorting key to eliminate lexicographical bias.

```python
# Patched sorting key
update_list.sort(key=lambda x: (x.utc_timestamp, x.sequence_id))
```

### Step 4: Force Robot Cache Invalidation
Implement a WebSocket-based push notification system to force-invalidate the shelving robots' cached maps immediately following a successful reconciliation job run, bypassing the 47-minute TTL.

---

## 5. Testing Suite

### Unit Tests (Pseudocode)

```python
class TestInventoryReconciliation:
    
    def test_dst_fallback_monotonicity_resolution():
        """Ensure physical sequence wins over ambiguous local times."""
        updates = [
            {
                "book_id": "B01",
                "location": "QZ-9",
                "utc_timestamp": "2026-11-01T05:30:00Z", # 01:30 LDT
                "sequence_id": 101
            },
            {
                "book_id": "B01",
                "location": "FL-3",
                "utc_timestamp": "2026-11-01T06:15:00Z", # 01:15 LST (Physically Later)
                "sequence_id": 102
            }
        ]
        
        reconciled = patched_reconcile(updates)
        assert reconciled["B01"].location == "FL-3"
        assert reconciled["B01"].sequence_id == 102

    def test_tie_breaker_ignores_location_string():
        """Ensure location string value does not influence LWW outcome."""
        updates = [
            {"book_id": "B02", "location": "QZ-9", "utc_timestamp": "2026-11-01T05:00:00Z", "sequence_id": 1},
            {"book_id": "B02", "location": "FL-1", "utc_timestamp": "2026-11-01T05:00:00Z", "sequence_id": 2}
        ]
        reconciled = patched_reconcile(updates)
        assert reconciled["B02"].location == "FL-1"
```

### Property-Based Tests (Pseudocode)

```python
from hypothesis import given, strategies as st

@given(st.lists(st.fixed_dictionaries({
    'book_id': st.just("PROP-TEST-01"),
    'location': st.sampled_from(["FL-1", "FL-2", "FL-3", "QZ-9"]),
    'utc_timestamp': st.datetimes(min_value=datetime(2020, 1, 1), max_value=datetime(2030, 1, 1)),
    'sequence_id': st.integers(min_value=1, max_value=100000)
}), min_size=2, unique_by=lambda x: x['sequence_id']))
def test_reconciliation_always_favors_highest_sequence(updates):
    """Property: The update with the highest sequence_id must always win, regardless of location string."""
    sorted_updates = sorted(updates, key=lambda x: x['sequence_id'])
    expected_winner = sorted_updates[-1]
    
    reconciled = patched_reconcile(updates)
    actual_winner = reconciled["PROP-TEST-01"]
    
    assert actual_winner['location'] == expected_winner['location']
    assert actual_winner['sequence_id'] == expected_winner['sequence_id']
```

---

## 6. Risk Register & Rollback Steps

| Risk ID | Risk Description | Severity | Mitigation Strategy | Rollback Trigger | Rollback Procedure |
| :--- | :--- | :--- | :--- | :--- | :--- |
| **R-01** | Legacy client devices fail to parse/send ISO 8601 UTC timestamps, causing ingestion failures. | High | Deploy a translation layer at the API Gateway to append UTC offsets to legacy payloads based on known device IP subnets. | Ingestion error rate exceeds 5% within 10 minutes of deployment. | Revert API Gateway routing rules to the previous container image (`v2.4.1-legacy`). |
| **R-02** | Forced cache invalidation storm overloads library Wi-Fi, disconnecting shelving robots. | Medium | Throttle the WebSocket invalidation signals using a token-bucket algorithm (max 5 robots per minute). | Robot ping latency exceeds 500ms or packet loss exceeds 10%. | Disable the WebSocket invalidation service; fall back to the default 47-minute TTL. |
| **R-03** | Database lock contention during mass update of historical corrupted records. | High | Run the historical data migration in batches of 500 records during maintenance hours (02:00 AM - 05:00 AM). | Database CPU utilization exceeds 85% or transaction pool exhaustion occurs. | Kill the migration process PID; restore the pre-migration database snapshot (`snapshot-pre-patch-20261102`). |

---

## 7. Executive Brief

### What Happened
During Sunday's early morning calendar rollover, two rare events happened at the same time: our weekly system update and the end of Daylight Saving Time (when clocks fall back one hour). 

Because our automated systems (robots, pneumatic tubes, and signs) recorded times using local clock time rather than a single standardized time zone, the hour between 1:00 AM and 2:00 AM was recorded twice. When the system tried to resolve conflicting records for books moved during this hour, it got confused by the duplicate times. To break the tie, the system fell back to alphabetical sorting. 

Because the code for our Archival/Quarantine Zone (**QZ-9**) starts with a "Q", it sorted higher than our standard floors (like **FL-3**). The system concluded that books should be in the archival zone, causing one of our shelving robots to start sealing returned books in protective archival capsules and directing patrons to the wrong floors.

### Why Manual Checkouts Worked
Manual checkouts bypass this weekly batch update process and write directly to our main database using standard, non-conflicting time records. This is why human-operated desks experienced no errors.

### Action Plan to Fix It
1. **Standardize Time:** We are updating all devices to use Coordinated Universal Time (UTC), which does not change for Daylight Saving Time.
2. **Add Sequence Numbers:** We are adding a simple "step counter" to every book update so the system knows the true order of events, regardless of what the clock says.
3. **Fix the Robots:** We are fixing the communication lag so that robots get instant map updates rather than waiting 47 minutes.
4. **Restore the Books:** We are running a targeted database cleanup to identify books incorrectly marked as "archived" and will direct staff to retrieve and unseal them.

### 1. Root-Cause Analysis (Failure Modes)

The current implementation suffers from severe concurrency bugs due to Node.js event-loop yielding during asynchronous operations. Below are the five distinct failure modes identified in the system:

```
                      [ reserveBerth() Called ]
                                 │
                                 ▼
                    [ Push to Queue & Sort ]
                                 │
                                 ▼
                      [ processQueue() Runs ]
                                 │
                    ┌────────────┴────────────┐
                    ▼                         ▼
          [ Lock Berth A ]          [ Lock Berth A ]  ◄── (Race Condition!)
                    │                         │
                    ▼                         ▼
         [ await notifyClimber ]   [ await notifyClimber ]
                    │                         │
         ┌──────────┴──────────┐              │
         ▼                     ▼              ▼
  [ cancelReservation ]   [ Resolve ]     [ Resolve ]
         │                     │              │
         ▼                     ▼              ▼
  [ Delete Lock ]       [ Force Approved ] [ Force Approved ] ◄── (Duplicate Berth!)
```

#### I. Re-entrancy Race Condition in `processQueue`
`processQueue` is an `async` function containing an `await` statement (`await notifyClimber(...)`). Because it is called synchronously inside `reserveBerth` without being awaited, multiple microtask ticks of `processQueue` run concurrently. When the first execution yields at `await`, a second execution can start, leading to interleaved executions processing the same queue elements.

#### II. Unstable In-Place Array Mutation
`queue.sort()` mutates the shared `queue` array in-place. While one instance of `processQueue` is suspended at `await notifyClimber`, a new reservation triggers another `sort()` call. This re-orders the array mid-execution, causing the suspended loop to resume with corrupted index references, skipping elements, or processing them out of order.

#### III. Late-Write Cancellation Overwrite
If a reservation is cancelled via `cancelReservation` while `notifyClimber` is yielding, the reservation status is updated to `"cancelled"`. However, once `notifyClimber` resolves, the suspended `processQueue` execution unconditionally overwrites the status to `"approved"` (`next.status = "approved"`), resurrecting a cancelled reservation and causing battery-swap cancellations to be ignored.

#### IV. Premature Lock Release
`cancelReservation` immediately deletes the berth lock (`berthLocks.delete(reservation.berthId)`) without verifying if the reservation is currently in-flight (awaiting notification). This allows a pending reservation for the same berth to acquire the lock *before* the active notification finishes, resulting in duplicate active reservations.

#### V. Priority Inversion and Starvation
Because `queue.shift()` removes the item from the queue *before* the asynchronous notification completes, an incoming `emergency` reservation cannot preempt a lower-priority reservation that has already started processing. Furthermore, if the queue is constantly sorted on every insertion, standard reservations can suffer from indefinite starvation during peak ascent windows.

---

### 2. Corrected TypeScript Implementation

This production-ready implementation introduces a concurrency-safe coordinator using a processing lock, defensive state checks, and atomic state transitions.

```typescript
export type Priority = "emergency" | "urgent" | "standard";
export type ReservationStatus = "pending" | "processing" | "approved" | "cancelled";

export type Reservation = {
  id: string;
  climberId: string;
  berthId: string;
  priority: Priority;
  status: ReservationStatus;
  createdAt: number;
};

export class BerthReservationCoordinator {
  private reservations = new Map<string, Reservation>();
  private berthLocks = new Map<string, string>(); // berthId -> reservationId
  private queue: Reservation[] = [];
  private isProcessing = false;

  public async reserveBerth(input: Omit<Reservation, "status" | "createdAt">): Promise<Reservation> {
    // Prevent duplicate reservation IDs
    if (this.reservations.has(input.id)) {
      throw new Error(`Reservation with ID ${input.id} already exists.`);
    }

    const reservation: Reservation = {
      ...input,
      status: "pending",
      createdAt: Date.now()
    };

    this.reservations.set(reservation.id, reservation);
    this.queue.push(reservation);
    
    // Fire-and-forget queue processing safely guarded against re-entrancy
    this.triggerQueueProcessing();
    
    return { ...reservation };
  }

  public async cancelReservation(id: string): Promise<boolean> {
    const reservation = this.reservations.get(id);
    if (!reservation) return false;

    const previousStatus = reservation.status;
    if (previousStatus === "cancelled") return true;

    // Atomic state transition
    reservation.status = "cancelled";
    this.reservations.set(id, reservation);

    // If it was already approved or processing, release the lock safely
    if (previousStatus === "approved" || previousStatus === "processing") {
      const currentLockHolder = this.berthLocks.get(reservation.berthId);
      if (currentLockHolder === id) {
        this.berthLocks.delete(reservation.berthId);
      }
    }

    // Remove from queue if it was still pending
    if (previousStatus === "pending") {
      this.queue = this.queue.filter(r => r.id !== id);
    }

    // Trigger processing to allow waiting reservations to claim the freed berth
    this.triggerQueueProcessing();
    return true;
  }

  private triggerQueueProcessing(): void {
    if (this.isProcessing) return;
    
    this.processQueue().catch(err => {
      console.error("Critical error in queue processor:", err);
    });
  }

  private async processQueue(): Promise<void> {
    this.isProcessing = true;

    try {
      while (true) {
        this.sortQueue();

        // Find the next reservation that is pending and whose berth is not locked
        const nextIndex = this.queue.findIndex(
          r => r.status === "pending" && !this.berthLocks.has(r.berthId)
        );

        if (nextIndex === -1) break; // No actionable items

        const reservation = this.queue[nextIndex];
        this.queue.splice(nextIndex, 1); // Remove from queue

        // Transition to processing
        reservation.status = "processing";
        this.berthLocks.set(reservation.berthId, reservation.id);

        try {
          await this.notifyClimber(reservation.climberId, reservation.berthId);

          // Check if cancelled during the async yield
          if (reservation.status === "cancelled") {
            this.releaseLockIfHeld(reservation.berthId, reservation.id);
            continue;
          }

          reservation.status = "approved";
          this.reservations.set(reservation.id, reservation);
        } catch (error) {
          // Handle notification failure: Revert and re-queue
          console.error(`Notification failed for climber ${reservation.climberId}:`, error);
          
          if (reservation.status !== "cancelled") {
            reservation.status = "pending";
            this.releaseLockIfHeld(reservation.berthId, reservation.id);
            this.queue.push(reservation);
          }
          break; // Break loop to prevent rapid-fire retry storms
        }
      }
    } finally {
      this.isProcessing = false;
    }
  }

  private sortQueue(): void {
    const priorityRank: Record<Priority, number> = {
      emergency: 0,
      urgent: 1,
      standard: 2
    };

    this.queue.sort((a, b) => {
      if (priorityRank[a.priority] !== priorityRank[b.priority]) {
        return priorityRank[a.priority] - priorityRank[b.priority];
      }
      return a.createdAt - b.createdAt; // FIFO within same priority
    });
  }

  private releaseLockIfHeld(berthId: string, reservationId: string): void {
    if (this.berthLocks.get(berthId) === reservationId) {
      this.berthLocks.delete(berthId);
    }
  }

  protected async notifyClimber(climberId: string, berthId: string): Promise<void> {
    await new Promise(resolve => setTimeout(resolve, Math.random() * 50));
    console.log(`Approved ${climberId} for ${berthId}`);
  }

  // Helper for testing and observability
  public getReservation(id: string): Reservation | undefined {
    const res = this.reservations.get(id);
    return res ? { ...res } : undefined;
  }
}
```

---

### 3. State-Transition Policy

To guarantee system safety, state transitions must strictly adhere to the following directed acyclic graph (DAG):

```
     ┌──────────────┐
     │   PENDING    │
     └──────┬───────┘
            │
      ┌─────┴─────────────┐
      ▼                   ▼
┌────────────┐     ┌─────────────┐
│ PROCESSING │     │  CANCELLED  │◄─── (Terminal State)
└─────┬──────┘     └─────────────┘
      │                   ▲
      ├───────────────────┤ (If cancelled during notification)
      ▼                   │
┌────────────┐            │
│  APPROVED  ├────────────┘
└────────────┘
```

| Source State | Target State | Trigger | Action Required |
| :--- | :--- | :--- | :--- |
| `None` | `PENDING` | `reserveBerth()` called | Add to queue, register reservation. |
| `PENDING` | `PROCESSING` | Queue processor selects item | Acquire berth lock, remove from queue. |
| `PENDING` | `CANCELLED` | `cancelReservation()` called | Remove from queue, mark terminal. |
| `PROCESSING` | `APPROVED` | `notifyClimber()` resolves | Confirm lock ownership, mark terminal. |
| `PROCESSING` | `CANCELLED` | `cancelReservation()` called | Set status to `CANCELLED`. Release lock post-yield. |
| `APPROVED` | `CANCELLED` | `cancelReservation()` called | Release berth lock, mark terminal. |
| `CANCELLED` | *Any* | Invalid Transition | Reject transition. |

---

### 4. Deterministic Priority Queue Verification

The sorting mechanism uses a deterministic composite key: **Priority Rank (Primary)** and **Creation Timestamp (Secondary)**.

```typescript
const priorityRank: Record<Priority, number> = { emergency: 0, urgent: 1, standard: 2 };
```

#### Sorting Properties:
* **Deterministic Ordering:** If two reservations have different priorities, the higher priority (lower rank number) always takes precedence.
* **FIFO Stability:** If priorities are identical, the older reservation (`a.createdAt - b.createdAt`) is processed first, preventing starvation within the same priority class.

---

### 5. Focused Test Plan

These integration tests verify the edge cases using a test-harness subclass to control notification latency.

```typescript
import { BerthReservationCoordinator, Reservation } from "./coordinator";

class TestCoordinator extends BerthReservationCoordinator {
  public notifyDelay = 50;
  public notifyPromiseResolve!: () => void;
  public notifyPromise!: Promise<void>;

  constructor() {
    super();
    this.resetNotifyPromise();
  }

  public resetNotifyPromise() {
    this.notifyPromise = new Promise((resolve) => {
      this.notifyPromiseResolve = resolve;
    });
  }

  protected override async notifyClimber(climberId: string, berthId: string): Promise<void> {
    await this.notifyPromise;
  }
}

async function runTests() {
  console.log("Starting Safety-Critical Test Suite...");

  // Test 1: Duplicate Reservation Prevention
  await (async () => {
    const coordinator = new TestCoordinator();
    await coordinator.reserveBerth({ id: "res-1", climberId: "c-1", berthId: "berth-1", priority: "standard" });
    try {
      await coordinator.reserveBerth({ id: "res-1", climberId: "c-2", berthId: "berth-1", priority: "standard" });
      throw new Error("Test 1 Failed: Allowed duplicate reservation ID");
    } catch (e) {
      console.log("✅ Test 1 Passed: Duplicate reservation ID blocked.");
    }
  })();

  // Test 2: Cancellation During Notification Window
  await (async () => {
    const coordinator = new TestCoordinator();
    const p1 = coordinator.reserveBerth({ id: "res-1", climberId: "c-1", berthId: "berth-1", priority: "standard" });
    
    // Allow microtask tick to start processing
    await new Promise(resolve => setImmediate(resolve));
    
    // Cancel while notifyClimber is pending
    await coordinator.cancelReservation("res-1");
    
    // Resolve notification
    coordinator.notifyPromiseResolve();
    await p1;

    const res = coordinator.getReservation("res-1");
    if (res?.status !== "cancelled") {
      throw new Error(`Test 2 Failed: Status is ${res?.status}, expected 'cancelled'`);
    }
    console.log("✅ Test 2 Passed: Cancellation during notification respected.");
  })();

  // Test 3: Emergency Preemption
  await (async () => {
    const coordinator = new TestCoordinator();
    
    // Block the processor with an active standard reservation
    await coordinator.reserveBerth({ id: "res-low", climberId: "c-low", berthId: "berth-1", priority: "standard" });
    await new Promise(resolve => setImmediate(resolve));

    // Queue another standard and an emergency reservation
    await coordinator.reserveBerth({ id: "res-low-2", climberId: "c-low-2", berthId: "berth-2", priority: "standard" });
    await coordinator.reserveBerth({ id: "res-high", climberId: "c-high", berthId: "berth-2", priority: "emergency" });

    // Complete the first notification
    coordinator.notifyPromiseResolve();
    await new Promise(resolve => setImmediate(resolve));

    // Prepare for the next notification
    coordinator.resetNotifyPromise();
    coordinator.notifyPromiseResolve();
    await new Promise(resolve => setImmediate(resolve));

    const high = coordinator.getReservation("res-high");
    const low2 = coordinator.getReservation("res-low-2");

    if (high?.status !== "approved" || low2?.status !== "pending") {
      throw new Error("Test 3 Failed: Emergency reservation did not preempt pending standard reservation.");
    }
    console.log("✅ Test 3 Passed: Emergency preemption verified.");
  })();
}

runTests().catch(console.error);
```

---

### 6. Staged Production Rollout Plan

Deploying changes to an equatorial orbital elevator requires a zero-downtime, risk-mitigated rollout strategy.

```
[ Phase 1: Shadow Mode ] ──► [ Phase 2: Canary (Nadir) ] ──► [ Phase 3: Blue-Green Cutover ] ──► [ Phase 4: Active Monitoring ]
```

#### Phase 1: Shadow Execution (Read-Only Validation)
* **Action:** Deploy the new coordinator code alongside the legacy system.
* **Execution:** Mirror 100% of live production traffic to the new coordinator. Discard its outputs but log its state transitions and compare them against the legacy system.
* **Success Criteria:** Zero divergence in state decisions over 72 hours of peak ascent windows.

#### Phase 2: Canary Deployment (Low-Load Window)
* **Action:** Route 10% of active climber traffic (specifically targeting the low-velocity Nadir station berths) to the new service.
* **Execution:** Run for 24 hours during off-peak maintenance windows.
* **Success Criteria:** Zero unhandled exceptions, and p99 reservation latency remains below 150ms.

#### Phase 3: Blue-Green Cutover with State Synchronization
* **Action:** Perform a full cutover to the new service.
* **Execution:** 
  1. Drain the legacy queue until empty.
  2. Export active berth locks and pending reservations.
  3. Hydrate the new coordinator with the active state.
  4. Shift 100% of traffic to the new coordinator via DNS/gRPC routing.
* **Rollback Trigger:** If any duplicate reservation is detected or if queue processing latency exceeds 500ms, immediately route traffic back to the legacy system.

#### Phase 4: Post-Deployment Monitoring & Metrics
* **Key Performance Indicators (KPIs) to track:**
  * `berth_lock_collision_count`: Must be 0.
  * `emergency_reservation_latency_seconds`: Must be < 0.1s.
  * `cancellation_override_events`: Must be 0.

### Timeline of Events

* **00:00 – 00:01**: Robotic arm places bowls onto the moving conveyor belt.
* **00:02 – 00:03**: Automated dispenser pours sauce into the bowls as they pass.
* **00:04 – 00:05**: Bowls proceed down the line while kitchen staff monitor the automated process via tablets.

### Operational Status

No operational interruption or safety incident is observed; the automated food preparation line runs continuously and smoothly throughout the clip.

### Visible Evidence

* Conveyor belt and robotic arms maintain a steady, synchronized rhythm.
* Dispensing mechanisms trigger precisely as bowls position underneath.
* Monitoring staff remain in supervisory roles without needing to intervene or halt the line.

### Uncertainties and Alternate Explanations

* The brief video length prevents evaluation of long-term mechanical reliability or potential sensor drift.
* Visual observation alone cannot confirm if portion sizes or bowl placements meet exact quality control tolerances.

### Recommended Changes

1. **Install Physical Guardrails**: Add side rails along the conveyor to prevent bowls from slipping off the belt.
2. **Integrate Alignment Sensors**: Use optical sensors to halt dispensing if a bowl is misaligned, preventing spills.
3. **Define Safety Zones**: Mark designated floor areas around the robotic arms to keep human operators at a safe distance during operation.

### 1. Summary
Two suited operators transport a cargo container via an automated guided vehicle (AGV) down a corridor. A close-up reveals a prominent vertical crack on the front of the container, posing a potential containment or structural risk.

### 2. Timestamped Sequence
* **00:00 - 00:01**: Male operator guides the AGV.
* **00:01 - 00:02**: Female operator joins to assist.
* **00:03 - 00:05**: Camera focuses on a cracked cargo container on the AGV.

### 3. Readable Text and Labels
* **Crate labels**: "AUROA BAMFAU NMLY", "AXUWVF AR17 Y18", "B6EDBLW 38CЯ 14018"
* **Background display**: "9", "48", "16"

### 4. Equipment and People Present
* **People**: Two operators in pressurized suits and helmets.
* **Equipment**: One AGV with a conveyor platform, one damaged cargo crate.

### 5. Likely Safety Risks
* **Containment Breach**: Potential leakage of hazardous contents due to the cracked container.
* **Structural Failure**: Risk of the crate breaking apart during transit.

### 6. Recommended Next Actions
* Stop transport to assess container integrity.
* Scan for leaks or hazardous emissions.
* Transfer contents to a secure container.

### 7. Scene Uncertainties
* The exact contents of the container and their hazard level.
* The origin and depth of the crack.