Governance guide

How to govern Inventory in AWS Bedrock

A step-by-step guide to governing Inventory in AWS Bedrock with Rencore: detect, review by owner and severity, and remediate with an audit trail.

Definition

Governing Inventory in AWS Bedrock means finding where it goes wrong, reviewing the findings by owner and severity, and remediating with an audit trail. Rencore covers this concern for AWS Bedrock with the pre-built controls below, so it becomes a repeatable check rather than a one-off cleanup. The steps that follow apply the same detect, review, remediate loop to Inventory.

Steps

  1. Inventory AWS Bedrock

    Connect AWS Bedrock and let Rencore build a continuous inventory of its resources, owners, and configuration, so governance starts from what exists rather than a stale export.

  2. Detect with policies

    Turn on the pre-built policies that cover Inventory in AWS Bedrock to surface oversharing, sprawl, and misconfiguration on the first scan, before writing a single custom rule.

  3. Review by owner and severity

    Use the AWS Bedrock reports to review findings by owner, category, and severity, and to share them with stakeholders who do not have a seat in the platform.

  4. Remediate and automate

    Apply automations to fix findings at scale, route sensitive changes through approvals, and keep every action reversible and logged for the audit trail.

AWS Bedrock controls for Inventory

Grounded in the Rencore catalog. See the full AWS Bedrock catalog on the AWS Bedrock connector page.

  • AWS Bedrock Account Region

    An AWS account and region combination representing a Bedrock deployment scope

  • AWS Bedrock Foundation Model

    Available AI foundation models in AWS Bedrock that can be used for inference

  • AWS Bedrock Custom Model

    Custom fine-tuned or distilled models created in AWS Bedrock

  • AWS Bedrock Guardrail

    Content filtering guardrails that control AI model inputs and outputs in AWS Bedrock

  • AWS Bedrock Agent

    AI agents that orchestrate foundation models, knowledge bases, and action groups in AWS Bedrock

  • AWS Bedrock Knowledge Base

    Knowledge bases for retrieval-augmented generation (RAG) in AWS Bedrock

  • AWS Bedrock Provisioned Throughput

    Dedicated throughput capacity provisioned for specific models in AWS Bedrock

  • AWS Bedrock Flow

    Orchestration workflows that chain AI operations in AWS Bedrock

  • AWS Bedrock Agent Action Group

    Action groups that define the actions an AWS Bedrock agent can perform

  • AWS Bedrock Agent Knowledge Base

    Knowledge base associations for AWS Bedrock agents

  • AWS Bedrock KB Data Source

    Data sources connected to AWS Bedrock knowledge bases

  • AWS Bedrock Model Customization Job

    Fine-tuning and continued pre-training jobs for customizing foundation models in AWS Bedrock

  • AWS Bedrock Model Evaluation Job

    Model quality evaluation jobs for benchmarking foundation and custom models in AWS Bedrock

  • AWS Bedrock Prompt

    Prompt templates in the AWS Bedrock prompt library for standardized AI interactions

  • AWS Bedrock Cost

    Daily cost breakdown for AWS Bedrock services from AWS Cost Explorer

  • AWS Bedrock IAM User

    AWS IAM users with access to Bedrock services

  • AWS Bedrock IAM Role

    AWS IAM roles with access to Bedrock services

  • AWS Bedrock IAM Policy

    AWS IAM policies related to Bedrock service permissions

  • AWS Bedrock User Activity

    Bedrock API activity events from AWS CloudTrail

Explore the full AWS Bedrock governance catalog | All guides

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