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First, check which Bedrock agent product you can use. AWS documentation says Amazon Bedrock Agents Classic is no longer open to new customers, although existing customers can continue using it; AWS points people seeking similar capabilities to Amazon Bedrock AgentCore. So the settings below are for existing Classic customers configuring an agent—not a claim that Classic is the path for a new build. See AWS’s Amazon Bedrock Agents overview for current product guidance.
If you are an eligible Classic customer, decide the agent’s task, model, permissions, capabilities, safety controls, and session behavior before implementation. AWS identifies the resource role, foundation model, and instructions as minimum setup, and recommends configuring at least one action group or knowledge base before preparing an agent for testing or deployment.
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Which Amazon Bedrock agent settings should you decide first?
Use this checklist to turn the use case into configuration choices. Exact model and feature availability, Region support, console labels, and permissions can change, so confirm them for your account and target Region before you commit.
- Define the job. List the tasks the agent should handle, what it must not do, what information it may need from a user, and whether it must retrieve information, take actions, or both.
- Select an eligible foundation model. Choose the model used for orchestration from those supported by Agents in your target Region. Bedrock availability alone does not establish agent eligibility.
- Write the instructions. Describe the agent’s purpose and how it should interact with users. In the console, these instructions populate the
$instructions$placeholder in the orchestration prompt template. - Choose its capabilities. Add an action group for defined operations such as API calls, a knowledge base for retrieval from data sources, or both where the workflow needs both.
- Plan identity and access. Decide whether to let AWS create the agent service role or manage a custom role, then grant only permissions needed by the selected model and capabilities.
- Set safety, encryption, and interaction behavior. Decide whether to associate a guardrail, use a customer-managed key, allow the agent to request missing information, and set an idle-session timeout.
- Test before release. Work with the draft, inspect traces, and deploy an immutable version through an alias used by the application.
How should you choose the model and write instructions?
Choose from models supported by Agents
Start with the model’s suitability for the orchestration task, then verify that Agents supports it in the Region where the agent will run. AWS says the console defaults to models optimized for agents; clearing that filter displays all models supported by Agents. For API use with cross-Region inference, AWS says to specify an inference profile ID in foundationModel. Check the current Agents-supported models guidance before choosing: model availability and support can vary.
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Make instructions operational
Instructions are not just a description of the product. Give the agent a defined task, identify what it should ask the user before proceeding, set boundaries on the requests it should handle, and explain how it should respond when required information is missing or uncertain. Treat these as behavioral requirements to test; prose instructions alone are not proof that the agent will reliably follow them.
Should the agent use an action group, a knowledge base, or both?
| Capability | Use it for | Configuration consideration |
|---|---|---|
| Action group | Defined actions, API calls, or other work that changes or retrieves information from an application. | Specify what information the agent must elicit, where it goes, and how the result returns. Lambda-backed action groups also require a Lambda resource-based policy that permits access. |
| Knowledge base | Answering questions by retrieving from configured data sources; private data can augment responses. | Associate the knowledge base the agent should query and test that its retrieved material supports the intended answers. |
| Both | Workflows that need grounded information as well as an operation, such as retrieving relevant details before invoking an application action. | Configure and permission both capabilities, and test how the agent moves between retrieval and action. |
AWS recommends at least one action group or knowledge base for an agent prepared for testing or deployment. Without either, the agent responds using the foundation model, instructions, and base prompt templates. The AWS manual agent creation and configuration guide describes the setup choices.
What role and permissions does the agent need?
The agent service role gives Bedrock permission to perform operations for the configured agent. The console can create a role for you; a custom role gives you more direct control over its trust policy and permissions. In either case, scope access to the features actually in use rather than granting broad permissions preemptively.
- Allow access to the selected foundation model or inference profile as required by current AWS policy guidance.
- For action groups, allow access to their schemas in S3 when applicable; for Lambda functions, configure the separate Lambda resource-based policy as well.
- Include permissions for associated knowledge bases, guardrails, customer-managed KMS keys, provisioned throughput, or collaborators only when the agent uses them.
Review the current AWS permissions guidance for agents before deployment, especially if using inference profiles or a custom role.
Which safety, encryption, and interaction settings matter?
Guardrails
A guardrail association is optional. Use one when you need configured controls to block or filter harmful content in user messages or model responses, and select the intended guardrail version. A guardrail is one layer of the application’s safety design, not a substitute for testing end-to-end behavior.
Encryption key
In the documented console flow, agent resources use an AWS-managed key by default. A customer-managed KMS key is an optional choice that provides customer key control but also requires the appropriate key permissions for the role and related principals.
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User input and session timeout
Decide whether the agent may ask for missing information rather than guessing or proceeding with incomplete details. The AWS console guide documents a 30-minute idle-session timeout default; after that idle period, the agent no longer maintains conversation history. The timeout can be changed, and the documented default should not be treated as a permanent or universal guarantee.
Code interpretation is another optional capability for tasks that involve writing, running, testing, or troubleshooting code. Enable it only if that is part of the use case and account for its permissions and behavior in testing.
When should you customize prompts or session context?
Advanced prompt templates let you change prompts used at runtime steps, while session state can carry context set at build time or supplied when the agent is invoked. Start with the defaults when they satisfy the requirements; customize in response to a behavior you can identify and test, rather than changing prompts without a clear purpose.
Test an important AWS-documented caveat if your design combines exactly one knowledge base, default prompts, no action group, and disabled user input: in that configuration, instructions will not be honored. See the AWS advanced prompt templates guidance and verify the behavior in your draft agent.
How do you test and deploy a Classic agent safely?
Test the draft
- Use the draft and its test alias while configuring the agent.
- Exercise representative requests, including missing-information cases, uncertain requests, retrieval, and each action the agent is allowed to perform.
- Inspect traces to see orchestration steps and diagnose where the behavior diverges from expectations. Adjust settings or prompts, then repeat relevant tests.
Deploy through a version and alias
Create an agent version when you are ready to deploy. Versions are immutable snapshots; an alias points to a version, and your application calls the alias. To update or roll back the target, move the alias to a different version rather than treating a version as an editable draft. AWS documents this lifecycle in its agent deployment guidance.
Quick Recap
What should you verify before committing to the setup?
- Confirm that Amazon Bedrock Agents Classic is available to your account; AWS says it is not open to new customers.
- Verify the model, inference profile, feature, and Region support that apply to the target deployment.
- Check current role, Lambda, KMS, and other permissions against the capabilities you actually configured.
- Test user-input, session-expiry, instruction, retrieval, action, and guardrail behavior in the draft, then deploy an immutable version through an alias.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
