Offload Read Spikes on Scalingo PostgreSQL with Native Read Replicas

Elevated Latency During Read Traffic Spikes

When a read-heavy application on Scalingo PostgreSQL experiences traffic spikes, the primary database instance becomes overloaded. It struggles to handle both transactional writes and high volumes of SELECT queries, leading to increased latency and elevated CPU pressure across the board.

The Optimal Scaling Strategy

The recommended engineering decision is to leverage Scalingo’s native read-replica feature. This provides horizontal read scaling without requiring significant changes to your application code, effectively separating read load from write load.

Implementing Read Replicas

Creation is typically managed via the Scalingo CLI or the management dashboard. The process involves configuring the primary instance to stream Write-Ahead Log (WAL) records to the new replicas. Once created, the application connection string must be updated to route all read-only queries to the replica endpoint, which is automatically load-balanced by the platform.

Performance Impact Example

A Django application initially handling 500 Reads Per Second (RPS) on the primary showed an average read latency of 120ms. After provisioning two read replicas and routing 70% of SELECT traffic to them, the average read latency dropped to 35ms, while write throughput remained stable.

Operational Trade-offs

The primary limitation is eventual consistency. Data written to the primary may take time (the replication lag) to appear on the replicas. This is unsuitable for workflows requiring immediate data visibility after a write. Additionally, each replica increases network overhead and cost.

Verification and Action

To confirm a replica is ready, run scalingo db:replica list in your terminal. Check that the status field for the desired replica shows active. To validate latency improvement, run a read-only benchmark like pgbench against both the primary and a replica endpoint and compare average response times.

Limitation: Failover handling for replicas is currently manual via the Scalingo UI; automated scripting is necessary for zero-downtime promotion.