Quick reference
Instance Size | CPU | Memory | Use Case | Throughput |
---|---|---|---|---|
Minimal | 1 vCPU | 1-2 GB | Development, testing | Up to 10k ops/sec |
Small | 2 vCPU | 4 GB | Small production | Up to 15k ops/sec |
Medium | 4 vCPU | 8 GB | Standard production | Up to 30k ops/sec |
Large | 8+ vCPU | 16+ GB | High-volume production | 50k+ ops/sec |
Minimal instance (1 vCPU, 1-2 GB)
Configuration
Not recommended for: >10k ops/sec, large backfills (>10M rows), or multiple high-throughput sinks.
Small instance (2 vCPU, 4 GB)
Configuration
When to scale
Monitor these saturation metrics (scale when >90%):sequin_ingestion_saturation_percent
sequin_processing_saturation_percent
sequin_delivery_saturation_percent
- Processes using >100MB memory
- Message queues with >1000 pending
- Growing ETS tables
erlang_vm_memory_bytes_total
approachingMAX_MEMORY_MB
Optimization tips
Batch configuration
Performance tuning
- Filter specific tables instead of entire schemas
- Use filters to reduce message volume
- Use transforms to reduce message sizes
- Set
BACKFILL_MAX_PENDING_MESSAGES
lower (e.g., 100k) for small instances
Cloud instances
Provider | Minimal | Small | Production |
---|---|---|---|
AWS | t3.micro | t3.small | t3.medium+ |
GCP | e2-micro | e2-small | e2-medium+ |
Azure | B1s | B2s | D2s_v3+ |
Getting help
- Start minimal and monitor metrics
- Join Discord or Slack for sizing advice
- Consider our managed offering for automatic scaling