hardMultiple Select
AIF-C01 Practice Question: A company uses Amazon Bedrock Agents for customer…
A company uses Amazon Bedrock Agents for customer support. The agent needs to perform multi-step reasoning: first identify the customer's account, then check order status, and finally provide a resolution. Which THREE components must be configured to enable this workflow? (Select THREE.)
⚠ Common exam trap
A common mistake is assuming a Knowledge Base is required for any data retrieval, but here the agent needs to call live APIs (account lookup, order status) via action groups and Lambda, not query a static knowledge base.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Agent orchestration to plan and execute multi-step reasoning
Option A is correct because Amazon Bedrock Agents rely on the agent's orchestration (the ReAct-based prompt/orchestration layer) to decompose the user request into a plan and sequence the multi-step reasoning across account identification, order-status lookup, and resolution. Option C is correct because each action group is backed by a Lambda function that Bedrock invokes to actually execute the business logic/API calls (for example, calling the CRM or order-management API) and return results to the agent. Option E is correct because you must define an action group per API operation—such as one for account lookup and one for order status—with its OpenAPI schema so the agent knows the available actions, parameters, and when to invoke them. Option B is not required: a Knowledge Base is for retrieval-augmented generation over documents, not for executing the transactional API calls this workflow needs. Option D is not required: a Guardrail adds safety/content filtering but does not enable the multi-step action execution workflow.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Agent orchestration to plan and execute multi-step reasoning
Why this is correct
Agent orchestration is the reasoning engine that decomposes the request, sequences the account lookup, order status check, and resolution steps, and decides which action groups to invoke. It directly enables the multi-step reasoning the stem requires.
- ✗
A Bedrock Knowledge Base with customer data
Why it's wrong here
A knowledge base supplies retrieval-augmented context from documents; it cannot execute the account identification or order-status API calls that multi-step action reasoning needs. It is tempting because knowledge bases are a core Bedrock Agents component, and they would be correct when the agent must answer from indexed enterprise documentation.
- ✓
A Lambda function for each action group to execute the API calls
Why this is correct
Action groups require a Lambda function to execute the underlying API calls, so each action group needs its own function performing the account lookup or order status retrieval. This provides the actual execution layer the agent's orchestration invokes.
- ✗
A Bedrock Guardrail to block out-of-scope questions
Why it's wrong here
Guardrails filter or block content against defined policies; they do not perform the account lookup, order-status call or reasoning steps the workflow requires. It is tempting because guardrails are a genuine Bedrock Agents feature, and they would be correct when the requirement is restricting harmful or off-topic responses.
- ✓
An action group for each API call (account lookup, order status)
Why this is correct
An action group defines the API operations the agent may invoke, with one per call (account lookup, order status). These give the agent the discrete, invocable capabilities its orchestration sequences to complete the multi-step workflow.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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