Compare Scenarios

Migration Step 1

Both scenarios define a migration step at this stage. Write-Heavy Transactional Platform: triggered by 'Dual-write inconsistency events observed in production: DB w'. Distributed Job Queue Platform: triggered by 'Background jobs competing with user-facing API requests for '.

Migration Step 2

Both scenarios define a migration step at this stage. Write-Heavy Transactional Platform: triggered by 'Primary write CPU > 70% sustained during peak windows; WAL v'. Distributed Job Queue Platform: triggered by 'High-priority transactional jobs (e.g., payment processing, '.

Migration Step 3

Both scenarios define a migration step at this stage. Write-Heavy Transactional Platform: triggered by 'Audit completeness requirements grow beyond point-in-time ba'. Distributed Job Queue Platform: triggered by 'Multi-step jobs (e.g., ingest file → validate → transform → '.

PgBouncer wait_queue > 0 sustained; application p99 write latency rising faster than PostgreSQL p99; pool_mode=transaction showing >80% utilization

Tier 1: Connection Pool Saturation: PgBouncer pool_size too small for write concurrency profile. Recommended evolution: Increase PgBouncer pool_size incrementally; profile transaction duration to right-size pool; consider separate pools for write-heavy and read-only workloads .

PostgreSQL checkpoint_completion_target warnings in logs; wal_buffers flushing more than once per second; pg_stat_bgwriter shows checkpoints_req rising; write p99 > 20ms without query explanation

Tier 2: WAL and Checkpoint Pressure: Write rate exceeding PostgreSQL's WAL flush and checkpoint throughput. Recommended evolution: Tune checkpoint_completion_target to 0.9; increase wal_buffers to 64MB; move PostgreSQL WAL to a dedicated NVMe volume separate from data directory .

Worker idle rate > 20% despite queue depth > 10k pending jobs; PostgreSQL pg_locks showing wait events on job table index; worker job claim p99 latency > 50ms (claim should be sub-10ms with correct indexing); CPU on PostgreSQL elevated from index scan overhead on job claim queries

Tier 1: Job Claim Lock Contention: Missing or misconfigured partial index on the job claim query; high worker concurrency driving SELECT FOR UPDATE SKIP LOCKED contention on a narrow hot page. Recommended evolution: Add a partial index on (priority DESC, created_at ASC) WHERE status = 'pending' AND run_at <= NOW(): the WHERE clause reduces the index to only claimable jobs, dramatically reducing index scan range; if contention persists, implement a job dispatch service (single dispatcher process) that batches claim queries and distributes job IDs to workers via an in-memory channel, removing per-worker database claims; tune FILLFACTOR on the job table to 70% to reduce hot page contention on SKIP LOCKED .

High-priority job queue depth growing despite workers available; low-priority batch jobs showing high throughput while transactional job latency (time from enqueue to execution start) p95 > 30s; worker pool metrics showing workers claiming jobs uniformly across priority levels rather than draining the high- priority queue first

Tier 2: Priority Inversion Under Load: Single worker pool consuming from all priority queues with equal weight; no priority-weighted polling implementation. Recommended evolution: Separate worker pools per priority tier (e.g., dedicated transactional workers for high-priority jobs, shared workers for low-priority batch); or implement priority-weighted polling in a unified worker pool (poll high-priority queue N times before polling low-priority queue once, where N is the priority weight ratio); add high-priority job execution latency as a first-class SLA metric with alerting threshold separate from batch job latency .