Optimizing cost for deploying Amazon Q

This post was made better through reviews from Khali Williams

Building on our previous discussions about AWS generative AI cost optimization, the fourth blog of the five-part blog series focuses on maximizing value from Amazon Q, AWS’s generative AI-powered assistant. While our earlier posts covered custom model development with Amazon EC2 and SageMaker AI and foundation models with Amazon Bedrock, today we’ll explore strategies to optimize costs when implementing Amazon Q. From selecting the right pricing tier and implementing strategic user management to optimizing content indexing and improving cost predictability, we’ll share practical approaches that help you balance functionality with cost efficiency. Whether you’re using Amazon Q Business for your generative AI–powered assistant or Amazon Q Developer to enhance developer productivity, these best practices will help you make informed decisions about your Q implementation.

Understanding Amazon Q: Business and Developer

Amazon Q Business is an AI-powered assistant designed to help find information, generate content, and automate tasks. Its benefits include increased productivity through fast, context-aware responses, enhanced decision-making with secure data access, and seamless integration with business tools. As you increasingly adopt Amazon Q Business for your generative AI needs, understanding cost optimization strategies becomes crucial for maximizing your return on investment.

Amazon Q Developer boosts software development through its real-time code suggestion system and automated task execution which produces higher productivity and shorter development periods. The tool provides fast onboarding, enhanced code quality, and security integration throughout the development lifecycle. Amazon Q Developer has per user pricing to accommodate businesses of any size and integrates with IDEs like JetBrains, VS Code, Visual Studio, and Eclipse. Speaking of Amazon Q Developer, we recently announced an exciting new cost optimization recommendation feature that helps you find cost savings opportunities, such as rightsizing instances, purchasing Savings Plans and Reserved Instances, terminating idle resources, through natural language conversations. This can be an efficient way for you to optimize resource usage and reduce costs, while working on your code.

Figure 1. Cost saving analysis in Amazon Q

Now, let’s return to our main topic – practical tips for optimizing your Amazon Q costs.

Pricing Tier Selection

Your first decision is to choose the right user pricing tier.

Amazon Q Business has two pricing tiers, Amazon Q Business Lite and Amazon Q Business Pro, see Amazon Q Business pricing. You can realize up to 85% in cost savings by carefully aligning your tier selection with business requirements. The Lite tier costs $3 per user per month. It provides basic features like secure data access and permission-aware responses, up to one page long. The Pro tier is $20 per user per month. It includes all Lite features plus Amazon Q Apps, content creation tools, and longer responses up to seven pages. Pro users can also gain insights on structured data with Q in QuickSight (Reader Pro), use custom and managed plugins for popular third-party apps, and receive image-based responses.

Amazon Q Business pricing tier change

Amazon Q Developer also has two pricing tiers, Amazon Q Developer Free Tier and Amazon Q Developer Pro Tier, see Amazon Q Developer pricing. The free tier provides an easy way to get started using Amazon Q Developer and includes code suggestions, CLI completions, CLI integration, and a selective amount of advanced features per month. The pro tier is $19/mo and includes everything in the free tier plus enterprise access controls, code base customization, and greater limits for advanced features like query authoring and code transformation.

Deciding on the user licensing tier should be driven by a thorough analysis of your use case, and user needs, rather than defaulting to the higher tier. This will ensure that your user licensing costs reflect the features your users are leveraging and will keep your costs efficient.

Strategic User Management

Managing user access in Amazon Q Business and Amazon Q Developer is crucial for cost optimization and operational efficiency since the service is priced on a per-user basis. By implementing strict user management practices, you can ensure that only users who truly need the capabilities have access, preventing unnecessary licensing costs from inactive or occasional users. You should regularly audit user accounts, removing access for departed users and reassessing the necessity of licenses for those who show minimal usage patterns. Additionally, by segmenting users into appropriate permission tiers and groups based on their roles and needs, you can better control data access, maintain security compliance, and prevent resource wastage. This strategic approach to user management not only reduces user costs but will also help you maintain better oversight of service usage.

Content Indexing Optimization

Amazon Q Business supports Retrieval Augmented Generation (RAG) through the connection of data sources, see Connecting Amazon Q Business data sources. The indexing process is priced per unit hour and is available using a single availability zone starter index or across three availability zones with an enterprise index. Minimizing the time and frequency of indexing has a positive impact on the indexing costs. See examples three through five in the ‘Pricing Examples’ section on the Amazon Q Business pricing page for examples of index costs. The two critical levers for controlling your indexing costs are the ‘Sync Mode’ and the ‘Sync run schedule’.

Sync mode offers two options. If you choose ‘Full sync’, Amazon Q syncs and indexes all content, regardless of the previous sync status. If you choose ‘New, modified, or deleted content sync’, Amazon Q only syncs new, modified, and deleted content. If you are incrementally adding or changing data, you should select ‘New, modified, or deleted content sync’ to minimize your costs. If you need to make a major change to your data source, it may make sense to do a, one time, sync using the ‘Full sync’ selection. Then you should revert to ‘New, modified, or deleted content sync’.

The ‘Sync run schedule’ allows you to set the indexing frequency. The available selections are hourly, daily, weekly, monthly, or custom (cron expression). You will want to optimize the indexing frequency based on the how often the connected data sources are updated and how frequently the data needs to be indexed for your solution. This setting can cause unexpected costs if it is set to run too frequently.

Conclusion

One of Amazon Q Business and Amazon Q Developers strongest advantages is its predictable cost structure. You can accurately forecast expenses while focusing on your core business objectives. This predictability, combined with the fully managed nature of the service, allows you to concentrate on delivering value rather than managing infrastructure.

We’ve covered the key components for optimizing Amazon Q Business and Amazon Q Developer costs through pricing tier selection, user management, and content indexing optimization. In our next blog, we’ll examine cost optimization strategies for services that operate as companions to AI solutions—storage, vector databases, data transfer, and reporting. Don’t miss these essential insights for building cost-effective, scalable AI applications.