Compare Scenarios

Migration Step 1

Both scenarios define a migration step at this stage. Gaming Backend Platform: triggered by 'Single game server instance running at connection ceiling; h'. Multi-Tenant SaaS Platform: triggered by 'Adding a second paying customer; first audit or security rev'.

Migration Step 2

Both scenarios define a migration step at this stage. Gaming Backend Platform: triggered by 'Game server instances blocking on PostgreSQL writes at end-o'. Multi-Tenant SaaS Platform: triggered by 'Database read load growing disproportionately with tenant co'.

Migration Step 3

Both scenarios define a migration step at this stage. Gaming Backend Platform: triggered by 'PostgreSQL event log table approaching 100B rows; reconnect '. Multi-Tenant SaaS Platform: triggered by 'Enterprise customer requesting dedicated infrastructure in c'.

Game server instance file descriptor count approaching OS limit (typically 65k open connections); WebSocket accept latency increasing; new connection establishment p99 > 200ms; CPU on game server instances > 70% during peak concurrent player count

Tier 1: WebSocket Connection Ceiling per Instance: Single game server instance WebSocket connection count limit; OS-level fd_max or application-level connection accept queue saturation. Recommended evolution: Increase OS fd_max to 512k and application connection accept queue depth; tune SO_REUSEPORT to allow multiple accept threads per socket; add game server instances and update consistent hashing ring; the affinity layer automatically routes new game rooms to the new instances as the ring expands: existing rooms are unaffected .

Redis command throughput > 500k/second; Redis CPU > 60%; per-tick Redis write latency p99 > 5ms (above the acceptable state sync threshold); game tick rate visibly dropping below target (30 ticks/second falling to 20) under load

Tier 2: Redis Game State Write Amplification: Game state serialization to Redis per tick producing more writes than expected; unoptimized state struct serialization writing entire state blob on any field change. Recommended evolution: Implement delta state serialization: only changed fields are written to Redis per tick using HSET with only the modified keys, not full state replacement; profile Redis command distribution per game tick to identify specific state fields with high churn; consider moving ephemeral per-tick state (player positions, projectile states) to local server memory with only durable state (scores, inventory changes) written to Redis .

PgBouncer pool wait queue > 0 during peak hours; application errors reporting "connection pool exhausted" or pool timeout; pool utilization > 90%

Tier 1: Connection Pool Exhaustion: Aggregate tenant connection demand exceeding PgBouncer pool_size. Recommended evolution: Implement per-tenant connection quotas at the application layer before hitting the pool; increase pool_size incrementally; identify top-N connection consumers by tenant and implement connection reuse within tenant request handlers .

pg_stat_activity shows one tenant's queries dominating query runtime; other tenants reporting p99 latency regression while their own query counts are stable; PostgreSQL shared_buffers cache eviction rate increasing

Tier 2: Noisy Tenant I/O Saturation: Single large tenant displacing other tenants' working sets from shared buffer cache. Recommended evolution: Implement pg_cgroups or connection-level resource groups if available; consider database-per-tenant for the top N largest tenants while keeping the shared schema for smaller tenants (hybrid isolation model) .