# Unnecessary multi-AZ configuration for non-production RDS instances

Canonical: https://www.pointfive.co/efficiency-hub/inefficiencies/unnecessary-multi-az-configuration-for-non-production-rds-instances

RDS Multi-AZ deployments are designed for production-grade fault tolerance.

By: Swapna Samuel

Updated: 2026-09-28

[Cloud Efficiency Hub](https://www.pointfive.co/efficiency-hub) 

# Unnecessary Multi-AZ Configuration for Non-Production RDS Instances

The short version

RDS Multi-AZ deployments are designed for production-grade fault tolerance.

[Swapna Samuel](https://www.linkedin.com/in/swapna-samuel-792745111/)

Head, Central Cloud FinOps & Clarity Business Management @ BMO

AWS service

[AWS RDS](https://www.pointfive.co/efficiency-hub/cloud-services/aws-rds)

Category

[Databases](https://www.pointfive.co/efficiency-hub/service-category/databases)

Reference

CER-0210

Type

Inefficient Configuration

## Explanation

Why the waste happens and who it affects.

In non-production environments, a Multi-AZ DB instance deployment roughly doubles the cost of database instances and storage, and a Multi-AZ DB cluster runs three DB instances (one writer and two readers), with little added value. Unless explicitly required for high-availability testing, Multi-AZ in dev, staging, or test environments typically results in avoidable expense.

## Billing model

The pricing dimensions that drive this cost.

RDS Multi-AZ instance deployments incur compute and storage charges for both the primary and the standby. Data transferred between Availability Zones for Multi-AZ replication is free.

## How to detect

How to find it in your estate.

Identify RDS instances in non-production accounts or environments with Multi-AZ enabled Use environment tags or naming conventions to distinguish staging and development workloads Evaluate instance-level metrics to assess whether failover capabilities are actively used or needed Check for duplicated storage and compute resources across Availability Zones

## How to fix

How to remove the waste.

Modify RDS instances in non-production environments to use single-AZ deployment Update provisioning templates and IaC modules to default to single-AZ for non-prod Create safeguards to prevent Multi-AZ deployments in dev/test unless explicitly approved

## Documentation

Vendor references for pricing and configuration.

- [Configuring and managing a Multi-AZ deployment for Amazon RDS  docs.aws.amazon.com](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Concepts.MultiAZ.html)

- [Multi-AZ DB cluster deployments for Amazon RDS  docs.aws.amazon.com](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/multi-az-db-clusters-concepts.html)

- [Amazon RDS Pricing  aws.amazon.com](https://aws.amazon.com/rds/pricing/)

## Related inefficiencies

[Browse the library](https://www.pointfive.co/efficiency-hub)

- AWS RDS  CER-0322

### [Non-Production RDS SQL Server Using Standard or Enterprise Edition Instead of Developer Edition](https://www.pointfive.co/efficiency-hub/inefficiencies/non-production-rds-sql-server-using-standard-or-enterprise-edition-instead-of-developer-edition)

Amazon RDS for SQL Server uses a License Included pricing model where the hourly instance rate bundles Microsoft SQL Server licensing fees on a per-vCPU basis. When non-production workloads - such as development, testing, staging, QA, or...

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- AWS RDS  CER-0320

### [Excess vCPU Licensing Costs on RDS for SQL Server Instances](https://www.pointfive.co/efficiency-hub/inefficiencies/excess-vcpu-licensing-costs-on-rds-for-sql-server-instances)

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- AWS RDS  CER-0086

### [Suboptimal RDS Instance Storage Type](https://www.pointfive.co/efficiency-hub/inefficiencies/suboptimal-rds-instance-storage-type)

An RDS instance uses a high-cost storage type such as io1 or io2 but does not require the performance benefits it provides. In many cases, provisioned IOPS are set at or below the free baseline included with gp3 (3,000 IOPS and 125 MiB/s,...

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Source: the public page above. Product screenshots and illustrative interfaces are examples, not live customer data.

