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 '. Streaming Media Platform: triggered by 'Upload API p99 exceeding 30 seconds due to in-process transc'.

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, '. Streaming Media Platform: triggered by 'PostgreSQL viewing history table exceeding 500M rows; write '.

Migration Step 3

Both scenarios define a migration step at this stage. Distributed Job Queue Platform: triggered by 'Multi-step jobs (e.g., ingest file → validate → transform → '. Streaming Media Platform: triggered by 'CDN provider incident causing total origin failover; CDN mis'.

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 .

Kafka consumer group lag on the transcoding topic growing during peak upload hours; content availability delay > 10 minutes for newly uploaded videos; transcoding worker CPU consistently above 85% across all instances

Tier 1: Transcoding Worker Throughput: Transcoding consumer group undersized relative to peak upload volume. Recommended evolution: Increase transcoding consumer instances up to the transcoding topic partition count; tune partition count to match the maximum desired worker parallelism (set this at topic creation, not after lag appears); implement per-uploader upload rate limits to smooth burst input; consider priority queuing so premium-tier content does not wait behind bulk ingest jobs .

MinIO GET request rate spikes > 10x baseline immediately after content publish or CDN invalidation; MinIO p99 latency > 500ms; CDN miss ratio > 5% on popular content

Tier 2: CDN Origin Thundering Herd: CDN cache miss storm on first-play of new or recently-updated content. Recommended evolution: Implement origin request coalescing (single origin fetch per CDN node per object, queue subsequent requestors for the in-flight response); pre-warm CDN edges for anticipated high-traffic content before publish; add rate limiting at the origin gateway to cap per-second origin requests per content_id .