Before we dive into the carnage, let's remind ourselves why we fell for event sourcing in the first place:

  • Complete audit trail? Check.
  • Ability to reconstruct past states? Check.
  • Flexibility to evolve our domain model? Check.
  • Scalability and performance benefits? Double-check.

It all sounded too good to be true. Spoiler alert: it was.

The Setup: Our Inventory Management System

Our system was designed to handle millions of SKUs across multiple warehouses. We chose event sourcing to maintain a precise history of every stock movement, price change, and item attribute update. The event store was our source of truth, with projections providing the current state for quick queries.

Here's a simplified version of our event structure:

{
  "eventId": "e123456-7890-abcd-ef12-34567890abcd",
  "eventType": "StockAdded",
  "aggregateId": "SKU123456",
  "timestamp": "2023-04-01T12:00:00Z",
  "data": {
    "quantity": 100,
    "warehouseId": "WH001"
  },
  "version": 1
}

Looks innocent enough, right? Oh, how naive we were.

The Unraveling: Event Versioning Pitfalls

Our first major hiccup came when we needed to update our StockAdded event to include a reason field. Simple enough, we thought. We'll just bump the version and add a migration strategy. What could go wrong?

Everything. Everything could go wrong.

Lesson 1: Version Your Events Like Your Life Depends On It

We made the classic mistake of using a single version number for all events. This meant that when we updated StockAdded, we inadvertently broke the processing of all other events.

Here's what we should have done:

{
  "eventType": "StockAdded",
  "eventVersion": 2,
  "data": {
    "quantity": 100,
    "warehouseId": "WH001",
    "reason": "Initial stock"
  }
}

By versioning each event type independently, we could have avoided the domino effect that brought our system to its knees.

Lesson 2: Migrations Are Not Optional

We initially thought we could get away with just handling both versions in our event handlers. Big mistake. As the system grew, this approach became unsustainable.

Instead, we should have implemented a robust migration strategy:


def migrate_stock_added_v1_to_v2(event):
    if event['eventVersion'] == 1:
        event['data']['reason'] = 'Legacy import'
        event['eventVersion'] = 2
    return event

# Apply migrations when reading from the event store
events = [migrate_stock_added_v1_to_v2(e) for e in read_events()]

The Snapshot Saga: When Optimizations Backfire

As our event store grew, rebuilding projections became painfully slow. Enter snapshots: our supposed savior that turned into yet another nightmare.

Lesson 3: Snapshot Frequency Is a Delicate Balance

We initially created snapshots every 100 events. This worked fine until we hit a sudden spike in transactions, causing our snapshot creation to fall behind and our projections to become increasingly out of date.

The solution? Adaptive snapshot frequency:


def should_create_snapshot(aggregate):
    time_since_last_snapshot = current_time() - aggregate.last_snapshot_time
    events_since_last_snapshot = aggregate.event_count - aggregate.last_snapshot_event_count
    
    return (time_since_last_snapshot > MAX_TIME_BETWEEN_SNAPSHOTS or
            events_since_last_snapshot > MAX_EVENTS_BETWEEN_SNAPSHOTS)

Lesson 4: Snapshots Need Versioning Too

We forgot to version our snapshots. When we changed our aggregate structure, all hell broke loose. Older snapshots became incompatible, and we couldn't rebuild our projections.

The fix? Version your snapshots and provide upgrade paths:


def upgrade_snapshot(snapshot):
    if snapshot['version'] == 1:
        snapshot['data']['newField'] = calculate_new_field(snapshot['data'])
        snapshot['version'] = 2
    return snapshot

# Use when loading snapshots
snapshot = upgrade_snapshot(load_snapshot(aggregate_id))

The Corruption Conundrum: When Your Source of Truth Lies

The final nail in our coffin was event store corruption. A perfect storm of network issues, a bug in our event store, and some overly aggressive error handling led to duplicate and missing events.

Lesson 5: Trust, but Verify

We blindly trusted our event store. Instead, we should have implemented checksums and periodic integrity checks:


def verify_event_integrity(event):
    expected_hash = calculate_hash(event['data'])
    return event['hash'] == expected_hash

def perform_integrity_check():
    for event in read_all_events():
        if not verify_event_integrity(event):
            raise IntegrityError(f"Corrupt event detected: {event['eventId']}")

Lesson 6: Implement a Recovery Strategy

When corruption happens (and it will), you need a way to recover. We didn't have one, and it cost us dearly. Here's what we should have done:

  1. Maintain a separate, append-only log of all incoming commands.
  2. Implement a reconciliation process to compare the command log with the event store.
  3. Create a recovery process to replay missing events or remove duplicates.

def reconcile_events():
    command_log = read_command_log()
    event_store = read_event_store()
    
    for command in command_log:
        if not event_exists_for_command(command, event_store):
            replay_command(command)
    
    for event in event_store:
        if is_duplicate_event(event, event_store):
            remove_duplicate_event(event)

The Phoenix Rises: Rebuilding with Resilience

After countless sleepless nights and more coffee than I care to admit, we finally stabilized our system. Here are the key takeaways that helped us rise from the ashes:

  • Event versioning is not optional – do it from day one.
  • Implement robust migration strategies for both events and snapshots.
  • Adaptive snapshot creation balances performance and consistency.
  • Trust nothing – implement integrity checks at every level.
  • Have a clear recovery strategy before you need it.
  • Extensive testing, including chaos engineering, can save your bacon.

Conclusion: The Double-Edged Sword of Event Sourcing

Event sourcing is powerful, but it's also complex. It's not a silver bullet, and it requires careful consideration and robust engineering practices to succeed in production.

Remember, with great power comes great responsibility – and in the case of event sourcing, a lot of sleepless nights. But armed with these lessons, you're now better prepared to tackle the challenges of event sourcing in the wild.

Now, if you'll excuse me, I have some PTSD to work through. Anyone know a good therapist who specializes in event sourcing trauma?

"In event sourcing, as in life, it's not about avoiding failures – it's about failing gracefully and recovering stronger."

Further Reading

Have you battled your own event sourcing demons? Share your war stories in the comments – misery loves company, after all!