> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cloudthinker.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Assessment

> Run Well-Architected assessments on your cloud resources — start with one resource and one pillar, then scale across your infrastructure.

## What You'll Learn

[Assessment](/guide/infrastructure/assessment) analyzes your cloud resources against the AWS Well-Architected Framework. You can select a single resource or multiple, one pillar or all six. Start small to learn the workflow, then scale up to surface patterns across your infrastructure.

<Note>
  Assessment requires the **Advanced plan**. Only resources that appear in your **Resources** inventory can be assessed — make sure discovery has run first.
</Note>

<Steps>
  <Step title="Navigate to Assessment">
    Go to **Infrastructure** > **Assessment** in your workspace.
  </Step>

  <Step title="Select Resources">
    Choose which resources to assess. For your first run, **start with one resource** — a good candidate is:

    * An **EC2 instance** running a production workload
    * An **RDS database** you suspect is over-provisioned
    * An **S3 bucket** with unknown access patterns

    As you get comfortable, scale up by selecting multiple resources using filters:

    | Filter           | Examples                                   |
    | ---------------- | ------------------------------------------ |
    | **Service type** | All EC2 instances, all RDS databases       |
    | **Tags**         | Environment: `production`, Team: `backend` |
    | **Region**       | `us-east-1`, all US regions                |

    You can select resources individually or click **Select All** on a filtered list.
  </Step>

  <Step title="Choose Pillars">
    Select which Well-Architected pillars to evaluate:

    | Pillar                     | What It Checks                              |
    | -------------------------- | ------------------------------------------- |
    | **Cost Optimization**      | Right-sizing, reserved capacity, idle spend |
    | **Security**               | Encryption, access control, compliance      |
    | **Reliability**            | Backup, redundancy, fault tolerance         |
    | **Performance Efficiency** | Throughput, latency, resource utilization   |
    | **Operational Excellence** | Monitoring, automation, runbook coverage    |
    | **Sustainability**         | Resource efficiency, carbon footprint       |

    **Start with one pillar** — **Cost Optimization** or **Security** typically surface the most actionable findings. Add more pillars as you scale up.

    <Tip>
      More resources and pillars means longer assessment time. A single resource with one pillar takes 1-2 minutes. Scale gradually.
    </Tip>
  </Step>

  <Step title="Run the Assessment">
    Click **Run Assessment**. The AI agent:

    1. Collects current resource configuration
    2. Analyzes metrics and usage patterns
    3. Evaluates against best practices for each pillar
    4. Generates findings with severity ratings

    You'll see a progress indicator as resources are analyzed.
  </Step>

  <Step title="Review Results">
    The analytics dashboard shows:

    * **Findings by pillar**: How many issues were found in each category
    * **Severity breakdown**: Critical, High, Medium, Low distribution
    * **Potential savings**: Estimated cost reduction if recommendations are implemented

    When assessing multiple resources, the dashboard also shows:

    * **Top affected resources**: Which resources need the most attention
    * **Pattern detection**: Systemic issues across resources (e.g., 80% of EC2 instances over-provisioned, no S3 buckets with versioning enabled)
  </Step>

  <Step title="Explore Recommendations">
    Each finding includes a recommendation with:

    * **Description**: What needs to change and why
    * **Impact level**: High, Medium, Low
    * **Effort**: How much work to implement
    * **Risk**: What could go wrong during implementation

    For each recommendation, you have four actions:

    1. **Impact Analytics**: See projected impact before making changes
    2. **Generate Guidelines**: Create implementation documentation
    3. **Custom Prompt**: Ask agents follow-up questions about the finding
    4. **Implement**: Apply the fix with agent assistance

    When reviewing multiple resources, sort by **Potential savings**, **Severity**, or **Effort** to prioritize. Focus on systemic issues — fixing one policy can resolve findings across many resources.
  </Step>

  <Step title="Save to Plan">
    Recommendations are saved as **drafts** by default. To track them:

    1. Select the recommendations you want to act on
    2. Click **Save to Plan** (batch select works for multiple recommendations)
    3. Assign priority and timeline on the **Plan** page
    4. Track implementation status over time

    The Plan page gives you a central view of all pending and completed optimizations across your infrastructure.
  </Step>
</Steps>

***

## Example: First Assessment

**Resource**: `i-0abc123def456` (m5.2xlarge, us-east-1)
**Pillar**: Cost Optimization

**Findings**:

* Instance is over-provisioned — average CPU at 12% over 30 days
* No Reserved Instance or Savings Plan coverage
* Recommendation: Downsize to m5.large, saving \~\$180/month

Once you've seen how it works, run the same pillar across all your EC2 instances to see if over-provisioning is a systemic pattern.

***

## Tips

* **Start small**: 1 resource + 1 pillar for your first run, then scale up
* **Use filters to group**: Tag-based filtering (environment, team) makes multi-resource assessments much more targeted
* **Check Impact Analytics first**: Always review projected impact before clicking Implement
* **Run periodically**: Weekly assessments catch drift and new issues over time
* **Use [Anna](/guide/agents/anna) for summaries**: After a large assessment, ask `@anna #report summarize the top 5 issues and create an action plan`

***

## Next Step

<Card title="Skills" icon="sparkles" href="/guide/tutorial/skills">
  Create custom skills to give AI agents your organization's domain-specific knowledge
</Card>