Compare Scenarios

Migration Step 1

Both scenarios define a migration step at this stage. Distributed Job Queue Platform: triggered by 'Background jobs competing with user-facing API requests for '. Realtime Collaborative Editor: triggered by 'User-visible edit conflicts > 5% of sessions; poll interval '.

Migration Step 2

Both scenarios define a migration step at this stage. Distributed Job Queue Platform: triggered by 'High-priority transactional jobs (e.g., payment processing, '. Realtime Collaborative Editor: triggered by 'Data loss complaints from users editing simultaneously; conf'.

Migration Step 3

Distributed Job Queue Platform has a defined migration; Realtime Collaborative Editor does not at this stage.

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 .

Server memory growing with active connections; file descriptor limits approached; new WebSocket connections refused

Tier 1: WebSocket Connection Ceiling: WebSocket server process connection limit or OS file descriptor ceiling. Recommended evolution: Increase file descriptor limits (ulimit); move to dedicated WebSocket server tier; implement connection multiplexing (multiple documents per connection where safe) .

Consecutive writes to the same document causing lock contention; write latency rising; auto-save batching queue depth increasing

Tier 2: Database Write Contention: High-frequency auto-save operations conflicting at the document row level; row-level locking under concurrent user edits . Recommended evolution: Move to operational transformation or CRDT-based conflict resolution; batch writes and resolve conflicts in-process before database commit; consider append-only event log for document operations .