⚡ Bolt: optimize ticket message counts with batch aggregation

[Woschj]

💡 What: Optimized the get_tickets_by_user method in TicketService by replacing the loop-based message count lookups with a single MongoDB aggregation pipeline.

🎯 Why: Previously, the service performed a separate database query for every single ticket to count its associated messages. In views with many tickets (especially for admins), this caused a significant performance bottleneck due to database round-trip overhead (N+1 query problem).

📊 Impact:

• Reduces database round-trips for message counts from $O(N)$ to $O(1)$.
• In a benchmark with 100 tickets, execution time dropped from ~0.57s to ~0.12s (~79% improvement).

🔬 Measurement: Verified using a custom benchmark script (benchmark_tickets.py - removed before submission) and confirmed data integrity for both String and ObjectId ticket_id formats.

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PR created automatically by Jules for task 14853306048367189451 started by @Woschj

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