Maximizing Performance and Cost Efficiency in Amazon RDS and Aurora PostgreSQL: Strategies and Best Practices

RDS and Aurora PostgreSQL make a lot of the operational overhead disappear, but performance and cost still don't manage themselves. Most teams either overprovision out of caution or undertune out of unfamiliarity, and both mistakes get expensive over time.

Anurag S works through what performance monitoring actually looks like in these environments, beyond just watching CPU graphs. Parameter tuning gets specific attention too, since PostgreSQL's defaults are rarely the right settings for a production RDS or Aurora workload. Cost optimization runs alongside all of it, treated as part of the same decision-making process rather than a separate conversation that happens after performance is already sorted.

The session works whether someone is just getting started with RDS PostgreSQL or already running production workloads and looking to close the gap between what the infrastructure costs and what it's actually capable of.

• Which performance monitoring signals actually matter versus which ones are noise
• Parameter settings that make a measurable difference in Aurora and RDS PostgreSQL
• Where cost and performance tradeoffs show up, and how to make them intentionally
• Common inefficiencies that quietly inflate AWS spend without improving performance

Cost optimization that ignores performance usually backfires. Performance tuning that ignores cost usually gets rolled back. The two have to be solved together.

• How to use performance monitoring tools effectively in RDS and Aurora PostgreSQL
• Parameter tuning strategies that improve database performance in production
• Practical approaches to cost optimization without sacrificing reliability
• How to balance performance and cost decisions as part of the same strategy

Getting the most out of RDS and Aurora PostgreSQL isn't about choosing between performance and cost efficiency. It's about tuning both together, deliberately, instead of treating one as an afterthought.