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Yes: Kiro CLI can make AWS Well-Architected review work more repeatable by preparing inputs, inspecting infrastructure-as-code (IaC), and coordinating CI/CD steps. But it does not perform or certify an AWS review by itself. Use the AWS Well-Architected Tool for documented workload reviews, or the AWS Well-Architected Agent for its separate pre-deployment IaC architecture-review flow; Kiro is the workflow layer around those AWS services.
What can Kiro CLI automate?
Kiro CLI supports non-interactive prompts in CI/CD pipelines, along with project guidance, hooks, custom agents, and Model Context Protocol (MCP) connections. Those capabilities make it useful for repeatable preparation and orchestration: for example, inspecting Terraform or CDK files, checking that review inputs are present, formatting findings, and passing results into a pipeline. See the Kiro CLI documentation.
AWS owns the Well-Architected review services, their criteria, and their outputs. Kiro can help run the surrounding process, but a prompt asking an agent to “review my architecture” is not equivalent to an AWS Well-Architected Tool review or an AWS Well-Architected Agent architecture review.
Choose the AWS review path that matches your goal
| Question | Well-Architected Tool workload review | Well-Architected Agent architecture review |
|---|---|---|
| When does it fit? | Reviewing and documenting an existing workload | Checking IaC architecture before deployment |
| Primary input | Workload documentation, answers, and review findings | CDK or Terraform templates staged in Amazon S3 |
| How it is started | Workload and lens-review operations through the AWS Tool API or CLI | Manually started architecture recommendation generation |
| Output and follow-through | Lens review findings, milestones, and improvement items | Recommendations and updated templates |
| Lens or pillar scope | Workload review with an associated lens; the Framework is commonly described in six pillars | The documented architecture-review operation uses the Framework lens and lists COST_OPTIMIZATION, SECURITY, RESILIENCE, and PERFORMANCE as selectable values |
| Documented operational limit | No corresponding limit stated in the cited workload-review material | Five architecture reviews per day per profile |
The AWS Well-Architected Tool documentation describes workload reviews and improvement tracking. The separate Well-Architected Agent documentation describes the IaC architecture-review flow. AWS describes the Agent as preview in its API reference, so check current account and regional availability before designing around it.
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Can Kiro CLI review Terraform or CDK before deployment?
It can inspect those files and help prepare or interpret a review, but the documented AWS architecture-review path is the service that analyzes IaC and returns recommendations with updated templates. To use that path, stage the supported CDK or Terraform project in S3, configure the Agent profile and access, then start an architecture review and check its generation status. This is a manually started architecture-review operation, not the scheduled resource or application recommendation-generation path.
Prepare the architecture-review input
- Use a ZIP archive no larger than 25 MB, or an S3 folder no larger than 100 MB total, with no individual file above 1 MB. These are AWS service input limits, not performance measurements.
- Use an S3 bucket in the same Region as the Agent profile.
- Configure the profile with its account and Region context and the supported review scope. The documented operation lists COST_OPTIMIZATION, SECURITY, RESILIENCE, and PERFORMANCE; do not assume it selects all six Well-Architected Framework pillars.
Follow the current AWS architecture-review instructions for the API operation and generation-status workflow. AWS documents a limit of five architecture reviews per day per profile; that quota says nothing about review quality or time saved.
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How to automate a workload review through AWS CLI or API
For an existing workload, use the AWS Well-Architected Tool rather than the Agent’s pre-deployment IaC path. The Tool supports workload documentation, lens reviews, milestones, and improvement tracking. Its CLI reference includes workload and lens-review management operations: AWS CLI Well-Architected reference.
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- Create or select the workload. Use the Tool API or CLI to create the workload or work with an existing one, then associate the appropriate lens.
- Complete the review. Record answers and findings with the people who understand the system. Use Kiro to organize evidence or flag missing information, not to invent answers where the evidence is unclear.
- Save a milestone and track improvements. Preserve the reviewed state and assign follow-up actions so that the review feeds remediation rather than ending at a report.
AWS describes the WAFR as answering foundational questions to assess alignment with cloud best practices and receive improvement guidance. The AWS WAFR overview explains the process and its role in the Well-Architected Framework.
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Build Kiro into a repeatable pipeline
A practical design separates Kiro’s assistance from the AWS operation. Keep review context and evidence requirements in the repository, use Kiro for bounded inspection and formatting tasks, and let a pipeline wrapper call the AWS API or CLI, capture identifiers, poll asynchronous status where applicable, and save the results as build artifacts or review issues.
Define project guidance
Put team-specific review instructions in project-scoped Kiro configuration where appropriate. A steering file can identify the workload, selected lens, acceptable evidence, required output format, and how the agent should report uncertainty. Kiro supports project configuration under .kiro/ and agent configuration under .kiro/agents/; use explicit tool permissions and check the applicable configuration precedence in the Kiro configuration documentation.
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Choose how Kiro gets AWS context
Kiro CLI V3 removed its built-in aws_tool. If Kiro itself needs AWS tools, configure an AWS MCP server; AWS’s migration guide uses @aws/aws-mcp-server as an example and shows profile and Region settings. Alternatively, keep AWS CLI/API calls in the surrounding CI job and give Kiro only scoped local inputs and captured results. See the Kiro MCP documentation and AWS migration guidance. Verify the MCP package, authentication method, tool permissions, and compatibility with the installed Kiro version before production use.
Keep outputs reviewable
Have the pipeline preserve the AWS operation identifiers and status, then publish findings in a form engineers and architecture stakeholders can inspect. Require a person to validate recommendations and any generated template changes before they are applied. Kiro can help explain or format a result; it should not silently turn an assessment into a deployment.
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Set up access without coupling review and deployment
The AWS Agent API quickstart requires an execution role and a target-account access role before API use; the API does not create those roles. A profile defines selected pillars and account/Region aggregation, while goals and application context can tailor recommendations. Check profile eligibility before relying on scheduled generation. Start with the AWS Well-Architected Agent API quickstart.
- Use a dedicated review identity with only the AWS permissions needed for the chosen review path.
- Keep review roles separate from deployment roles, and do not put credentials in prompts or repository files.
- Scope MCP tools deliberately; a connected server can expose capabilities beyond reading local IaC.
- Validate the process in a limited profile and account before expanding it.
- Require human review before applying infrastructure changes suggested or generated by an agent.
These are prudent implementation safeguards for a role-based AWS setup and configurable Kiro tools, not a universal IAM policy prescribed for every combined workflow.
What automation does not prove
The official documentation establishes the available workflow capabilities and service limits, not outcome claims for Kiro-based reviews. It does not establish a percentage of time saved, improved coverage, or reduced risk. Treat a successful pipeline run as evidence that the configured steps executed—not as proof that stakeholders supplied complete answers or that an architecture is compliant, secure, or optimal.
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