Amazon Q Guide: Developer, Business and the 2026 Changes

What Is Amazon Q?

Developers know the friction well: hunting through AWS documentation for the right API call, writing boilerplate CloudFormation, debugging a Lambda timeout or digging an answer out of an internal wiki. Business analysts, meanwhile, want plain-English answers from scattered company data. They also want them without filing a ticket. Amazon Q was AWS’s answer to both problems. In 2026, though, the product family changed a lot. So this guide also covers what is still open to new customers and what replaced the rest.

Amazon Q is a family of generative AI assistants from Amazon Web Services, built for two audiences: developers building on AWS and employees working with company data. It is integrated closely with AWS services and draws on AWS documentation and best practices. That sets it apart from general-purpose chatbots.

Amazon Q was introduced in preview at re:Invent 2023 and reached general availability in April 2024. AWS then added Q Apps for no-code automation in July 2024. It also added Q in QuickSight for natural language BI, Q in Connect for contact centers and IDE integrations for VS Code, JetBrains and the CLI. Q Developer also absorbed Amazon CodeWhisperer. In 2026 the picture changed again. Q Developer closed to new sign-ups on May 15, 2026, and its IDE plugins and paid subscriptions reach end of support on April 30, 2027. AWS points users to Kiro instead. Amazon Q Business moved to maintenance mode and closed to new customers on July 30, 2026. Its successor is Amazon Quick.

Amazon Q is not a single product: it is a suite of specialized abilities that share the same underlying AI infrastructure (built on Amazon Bedrock) but serve different use cases:

The Q Product Family

• Amazon Q Developer: An AI coding assistant for software developers and IT professionals. Handles code generation, debugging, testing, security scanning, application modernization, and AWS infrastructure guidance.
• Amazon Q Business: An enterprise knowledge assistant that connects to your company’s data sources (Slack, Confluence, SharePoint, S3, Salesforce, and 40+ others) to answer questions, generate content, and automate tasks.
• Q in QuickSight: A natural language BI assistant that lets analysts build dashboards, create visualizations, and perform scenario analysis using plain English.
• Q in Connect: An AI assistant for contact center agents that delivers real-time, personalized responses during customer conversations.

Q Impact and Adoption

AWS has published strong numbers for Q Developer. Using it for application modernization, AWS reported $260 million in annual cost savings and 4,500 developer-years of effort saved. At general availability, AWS also cited BT Group accepting 37% of Q Developer’s code suggestions and National Australia Bank 50%. These results came from the Q Developer era, and similar work now continues in Kiro.

How Amazon Q Developer Works

Amazon Q Developer is a full-lifecycle AI assistant for software development, not just a code completion tool. While competitors like GitHub Copilot primarily focus on inline code suggestions, Q Developer spans the entire development workflow: writing code, testing, debugging, deploying, security scanning, infrastructure optimization, and legacy application modernization.

Code Generation and Inline Assistance

Q Developer generates real-time code suggestions, from single-line completions to whole functions, directly in your IDE. It works in VS Code and JetBrains IDEs. It also offers inline chat, so you can select a block of code and ask it to “optimize this”, “add error handling” or “write unit tests” without leaving the editor.

Also, Q Developer supports workspace context awareness. Rather than generating suggestions based only on the current file, it considers your entire project structure, imports, dependencies, configuration files, and related modules, to produce more accurate, project-aware recommendations. For enterprise teams, this context awareness extends further: you can securely connect Q Developer to your private code repositories, enabling it to generate suggestions informed by your internal libraries, APIs, and coding patterns.

Also, Q Developer goes beyond the IDE. In the command line, it provides CLI completions, natural language-to-bash translation, and interactive chat for operational tasks. You can ask “show me all Lambda functions with errors in the last hour” directly from your terminal, and Q translates that into the appropriate AWS CLI commands. For teams that live in the terminal, this eliminates constant context-switching between documentation and command execution.

Agentic Development Abilities

Beyond basic code completion, Q Developer can autonomously handle multi-step implementation tasks. Simply describe a feature in natural language (for example, “build an SMS notification system for delivery confirmations”), and Q Developer will analyze your existing codebase, create a step-by-step implementation plan spanning multiple files, and, upon your approval, execute all required code changes and generate tests.

This agentic approach shifts the developer’s job from writing every line to reviewing and approving AI-generated changes. For common patterns, such as CRUD APIs, event-driven Lambda functions, DynamoDB integrations and Step Functions workflows, it can produce working code much faster than writing it by hand. AWS cited BT Group accepting 37% and National Australia Bank 50% of Q Developer’s suggestions.

Also, Q Developer supports Console-to-Code: an ability that captures your actions in the AWS Management Console and generates reusable infrastructure-as-code from them. This bridges the gap between prototyping in the console and deploying production workloads via CloudFormation or CDK, eliminating the tedious manual translation step that slows many teams down.

Application Modernization with Q

One of Q Developer’s most distinctive features is automated application modernization. It can upgrade Java applications from version 8 or 11 to Java 17 or 21, including dependency migrations, API changes and test adjustments. AWS used this internally and reported 4,500 developer-years of effort saved. Note that code transformation for Java upgrades and .NET porting will no longer be available after April 30, 2027, so finish in-progress transformations before then.

Similarly, Q Developer supports .NET porting from Windows to Linux, reducing migration effort and enabling organizations to move legacy applications to cost-effective Linux-based infrastructure on AWS. For enterprises running thousands of legacy Java or .NET applications, these transformation abilities represent millions of dollars in saved engineering effort and accelerated modernization timelines.

Also, the modernization workflow is interactive rather than fully autonomous. Q Developer proposes a transformation plan and shows exactly what it intends to change. It then waits for your approval before executing. After transformation, it runs the existing test suite to verify that behavior is preserved. This human-in-the-loop approach gives engineering teams confidence that automated changes will not introduce regressions: a critical requirement for production codebases in regulated industries.

Security Scanning and AWS Expertise

Unlike generic code assistants, Q Developer includes built-in security scanning that understands AWS-specific vulnerabilities. It checks for overpermissive IAM policies, misconfigured S3 buckets, exposed secrets, and OWASP-standard code vulnerabilities: going beyond basic linting to identify security risks that require AWS context to detect. Also, Q Developer serves as an AWS architecture expert: you can ask it to review your CloudFormation templates, suggest cost optimizations, diagnose networking issues, or explain any AWS service, and it responds with guidance grounded in 20 years of AWS documentation and best practices.

Also, Q Developer is available in the AWS Management Console, the CLI, and integrated with Microsoft Teams and Slack for operational troubleshooting, enabling DevOps teams to investigate incidents, check resource status, and run diagnostics without context-switching between tools.

How Amazon Q Business Works

While Q Developer targets software teams, Amazon Q Business serves the broader workforce: anyone in the organization who needs to find information, generate content, or automate tasks using company data. In most organizations, employees spend hours each week searching across fragmented systems, internal wikis, shared drives, Slack channels, project management tools, and email archives, to find the information they need. Q Business eliminates this friction by indexing all of these sources and making them searchable through a single conversational interface.

Enterprise Knowledge Search with Q

Q Business connects to your organization’s existing data sources and makes them searchable through natural language. It supports over 40 data connectors out of the box, including Slack, Microsoft Teams, Confluence, SharePoint, Jira, Salesforce, ServiceNow, Amazon S3, RDS, and many more. Then Q Business indexes your content and lets employees ask questions like “What is our return policy for enterprise clients?” or “Summarize the key decisions from last quarter’s board meeting.”

Q Business respects existing access controls. If a user cannot view a document in SharePoint, they cannot see it through Q Business either. This enterprise-grade permission inheritance is what separates Q Business from plugging a generic LLM into your data: it maintains governance without requiring a new access control layer.

Q Business can also generate content from company data, such as draft emails, summaries, meeting briefs and reports grounded in your own knowledge. For teams that spend hours each week searching across fragmented systems, it brings that search into one conversational interface.

Automating Tasks with Q Apps

Beyond search and Q&A, Amazon Q Apps lets employees build lightweight AI-powered applications using natural language, without any coding. Simply describe the app you want (for example, “create an onboarding checklist generator that pulls from our HR handbook”), and Q Apps generates it automatically. Then these apps can be shared across teams, creating a self-service automation layer that democratizes AI within the organization.

Q Apps represents a shift in how organizations think about internal tooling. Traditionally, building even a simple internal tool required submitting a request to the engineering team, waiting weeks for prioritization, and accepting a solution that may not match exactly what was needed. With Q Apps, the person closest to the problem builds the solution in minutes. They use plain English and their company’s own data.

For example, an HR team can build an app that answers benefits questions from the employee handbook. A sales team can create a tool that summarizes competitive intelligence from internal reports. A project manager can generate a status report app that pulls from Jira and Confluence automatically. Each of these would have taken days of developer time to build traditionally. With Q Apps, they take minutes and need no technical skills.

Q in QuickSight for Business Intelligence

For business analysts, Amazon Q in QuickSight changed how BI work gets done. Instead of writing SQL or building charts by hand, analysts describe what they want in plain English, for example “show me quarterly revenue by product category with year-over-year growth”, and Q builds the visualization and the metrics. AWS has since folded QuickSight into its Amazon Quick suite.

Also, Q in QuickSight supports natural language data exploration. Analysts can ask follow-up questions, drill down into specific segments, and request “what-if” scenarios without touching a formula or writing a single line of code. For organizations where BI expertise is concentrated in a small team, this ability democratizes data access, enabling product managers, marketing leads, and executives to self-serve their own analytics instead of filing requests with the data team.

Talk to an ExpertUsing Amazon Q today? Plan your move to Kiro and Amazon Quick with us.

Amazon Q Pricing Model

Rather than listing specific dollar amounts that change over time, here is how the pricing structure works for each Amazon Q product:

Developer Tier Pricing

Amazon Q Developer had a free tier with limited monthly usage, capped on code completions, chat interactions and agentic requests. Since May 15, 2026, new Free Tier accounts and new subscriptions can no longer be created. So the free tier only matters to people who already have it.

The Pro tier removes the usage caps and adds administrative controls, organizational policies, SSO through IAM Identity Center and a guarantee that your code is not used for service improvement. Existing Pro subscriptions can still add seats until the April 30, 2027 end of support. For current per-user pricing, see the official Q Developer pricing page.

Business Tier Pricing

Amazon Q Business uses a per-user subscription with two tiers. Lite covers basic Q&A and suits employees who mainly search company knowledge. Pro adds Q Apps for no-code app building, more integrations, higher usage limits and the full set of automation features, for people who use it daily. Since July 30, 2026, Q Business is closed to new customers.

Also, index unit fees apply based on the volume of content you connect. Organizations with large knowledge bases may require multiple index units, which adds to the monthly cost. For current pricing details, see the official Q Business pricing page.

Amazon Q Security and Compliance

Security is the primary concern when connecting an AI assistant to enterprise data. Amazon Q addresses this through several architectural decisions that distinguish it from consumer-grade AI tools.

First, Q Business respects existing access controls from connected data sources: users can only access information they are already authorized to see in the source system. This is a fundamental architectural commitment, not just a policy overlay. Second, Q Business content and Q Developer Pro code are not used to improve the service. On the Q Developer free tier, AWS may use content unless you opt out. Third, all data is encrypted in transit and at rest using AWS’s standard encryption infrastructure. Fourth, when using Q Developer Pro, your proprietary code is not used for service improvement of any kind.

Also, Amazon Q Business is HIPAA eligible, making it suitable for healthcare organizations handling protected health information. It also inherits compliance certifications from the broader AWS infrastructure including SOC, ISO 27001 and PCI DSS. Check AWS Services in Scope for current coverage. For organizations in regulated industries, these certifications mean that adopting Q Business does not introduce new compliance gaps: it operates within the same security boundary as your existing AWS workloads.

Also, Q Business supports fine-grained administrative controls. Administrators can manage which data sources are connected, which users have access, what topics the assistant is permitted to discuss, and how responses are filtered. Combined with CloudTrail logging of all Q interactions, organizations maintain complete auditability over how their AI assistant is used and what data it accesses.

Real-World Amazon Q Use Cases

Amazon Q’s versatility spans both developer workflows and business operations. Below are the use cases we implement most frequently for our enterprise clients:

Amazon Q vs GitHub Copilot

If you are evaluating AI coding assistants, here is how Amazon Q Developer compares with GitHub Copilot: the current market leader by user count:

Choosing the Right AI Coding Assistant

The choice depends on where you build. If your infrastructure runs on AWS and you need assistance with CloudFormation, CDK, Lambda, IAM policies, and AWS-specific architecture: Q Developer is unmatched. Conversely, if you are a platform-agnostic team primarily using GitHub for version control and CI/CD, Copilot offers a more polished general-purpose coding experience.

Q Developer’s application modernization ability (automated Java/.NET upgrades) was an early differentiator for enterprises with legacy codebases, although GitHub has since added app modernization features to Copilot. Similarly, Q Developer’s operational integration, diagnosing incidents via Slack/Teams, analyzing bills in the console, debugging networking via VPC Reachability Analyzer, extends far beyond what any code-focused assistant offers.

Many AWS-centric organizations used Q Developer for AWS-specific and infrastructure work, alongside a general-purpose coding assistant for everything else. New teams can apply the same split with Kiro and another assistant.

Getting Started with Amazon Q

Both Q Developer and Q Business offer quick setup paths. Here is how to get started with each.

Setting Up Q Developer

Existing users install the Amazon Q extension in VS Code or JetBrains (IntelliJ, PyCharm, WebStorm), or use Q Developer in the AWS Management Console or the CLI. New Free Tier accounts and new subscriptions have been closed since May 15, 2026. So new teams should start with Kiro, which AWS names as the successor. Q Developer in the console and in other AWS experiences such as the documentation site, the mobile app, Slack and Microsoft Teams is not affected by the IDE plugin end of support.

Once installed, start with simple prompts to test the experience. Try asking Q Developer to generate a Lambda function, review an IAM policy, or explain a CloudFormation error. The key to getting value quickly is focusing on AWS-specific tasks where Q Developer’s specialized knowledge provides an advantage over general-purpose assistants. Some effective starting prompts include:

# In the IDE chat panel, try:
"Generate a Lambda function that processes S3 events and stores metadata in DynamoDB"

# In the AWS Console, try:
"How can I reduce costs on my EC2 instances?"

# In the CLI, try:
q chat "Explain the difference between ALB and NLB"

Setting Up Q Business

Existing Q Business customers can still create applications in the console. They configure data source connectors, such as Slack, Confluence, SharePoint, Jira, Salesforce and S3, set up user access through IAM Identity Center so Q Business inherits existing permissions, and then invite users. New customers can no longer sign up and should evaluate Amazon Quick.

Start with a focused deployment rather than connecting every data source at once. Begin with one or two high-value knowledge repositories, such as your engineering wiki or HR policy documentation, and validate that Q Business delivers accurate, useful answers before expanding. This iterative approach lets you tune retrieval quality, identify gaps in your content, and build user confidence before scaling to the full organization.

Also, consider designating a small group of power users as champions who can provide feedback on answer quality, identify missing data sources, and train colleagues on effective prompting. Organizations that treat Q Business adoption as a change management initiative, not just a technology deployment, consistently see higher engagement and faster ROI.

Amazon Q Best Practices and Pitfalls

Recommendations for Effective Q Adoption

• Plan your move before the deadlines: If you use Q Developer, list the features you rely on, especially code transformation, and plan a move to Kiro before April 30, 2027. Measure code acceptance, time saved and developer satisfaction so you can compare.
• Use Q Developer for AWS-specific tasks first: After all, its competitive advantage is infrastructure knowledge: CloudFormation generation, IAM policy review, cost optimization, and architecture guidance. For general coding tasks, evaluate whether it outperforms your current tools.
• Curate your Q Business data sources carefully: Initially, connect high-value, frequently-searched knowledge repositories first (HR policies, product docs, engineering wikis). Otherwise, adding noisy or outdated data sources degrades answer quality.
• Monitor usage against subscription limits: Track agentic request consumption and code transformation usage to avoid overage charges. Set up AWS Budgets alerts for Q-related spending.
• Maintain code review discipline: AI-generated code, regardless of source, should go through the same review process as human-written code. Q Developer accelerates development, but it does not replace engineering judgment.

Our ServiceDevOps, IT Automation and Application Modernization

Frequently Asked Questions About Amazon Q

References

1. Q Developer Sign-Up Closure May 15, 2026; IDE Plugins and Subscriptions End of Support April 30, 2027; Kiro: AWS DevOps Blog — Amazon Q Developer End-of-Support Announcement
2. Upgrading From Q Developer to Kiro: AWS — Upgrade to Kiro
3. Amazon Q Business Moving to Maintenance July 30, 2026: AWS What’s New — AWS Service Availability Updates, June 2026
4. $260 Million Saved and 4,500 Developer-Years (AWS Internal Java Upgrades): Andy Jassy — Amazon Q Developer Java Upgrades at Amazon
5. BT Group 37% and NAB 50% Acceptance Rates: AWS — Amazon Q Developer