Clean up remaining in-memory rate limiting maps causing memory leaks

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Problem

Several rate limiting implementations still use in-memory Maps that grow indefinitely:

• Stock reservation rate limiting
• Product cache rate limiting
• Session-based rate limiting
• Any other in-memory rate limiting maps

These cause memory leaks with 200+ concurrent users.

Impact

• Memory usage grows with user count
• Rate limits don't work across server instances
• Memory pressure on application servers
• Inconsistent rate limiting behavior

Solution

Audit and replace all remaining in-memory rate limiting Maps with Redis-based solutions:

• Use existing cacheService for all rate limiting
• Implement proper TTL for automatic cleanup
• Ensure distributed rate limiting across instances
• Add proper error handling and fallbacks

Files to audit

• All API routes with rate limiting
• Session management code
• Cache implementations
• Any other in-memory storage

Acceptance Criteria

• Audit all in-memory rate limiting Maps
• Replace with Redis-based solutions
• Implement proper TTL and cleanup
• Test distributed rate limiting
• Verify no memory leaks under load
• Ensure rate limits work across instances