A recommendation system stores 1 million embeddings in Azure Database for PostgreSQLDuring peak hours.

A recommendation system stores 1 million embeddings in Azure Database for PostgreSQL

During peak hours. P95 similarity-query latency increases, and the cache hit ratio drops significantly.

You suspect that the vector index working set no longer fits in memory, resulting in more disk reads.

You need to scale server resources and validate the outcome.

Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.