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使用 Amazon Bedrock Projects 管理 AI 成本

使用 Amazon Bedrock Projects 管理 AI 成本
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☁️閱讀原文： AWS Machine Learning Blog
#cost-attribution#tagging-strategy#cost-analysisamazon-bedrock-projectsamazon-bedrockaws-cost-exploreraws-data-exports

💡依工作負載追蹤 Bedrock 推論成本，優化 AI 支出（24字）

⚡ 30 秒速覽

有什麼變化

將推論成本歸因於特定 AI 工作負載

為什麼重要

此功能幫助 AI 團隊控制基礎模型支出，實現無預算超支的可擴展部署。它與現有 AWS 工具無縫整合，提供細粒度可見性。

下一步行動

在 AWS 主控台建立 Bedrock Project，並將標記應用於推論呼叫以開始追蹤成本。

誰應關注：Developers & AI Engineers

關鍵要點

  • •將推論成本歸因於特定 AI 工作負載
  • •在 AWS Cost Explorer 和 Data Exports 中分析成本
  • •包含標記策略設計的端到端設定

🧠 深度解析

本篇為 AI 生成分析，非原文內容。

🔑 增強重點摘要

  • •Bedrock Projects utilize a logical grouping mechanism that acts as a container for resources, allowing organizations to enforce cost allocation tags at the project level rather than relying solely on individual API call metadata.
  • •The integration with AWS Cost Explorer enables granular cost visibility by leveraging the 'aws:resource:tag' key, which automatically populates cost allocation reports once the project-level tags are activated in the Billing and Cost Management console.
  • •Beyond cost tracking, Bedrock Projects facilitate improved governance by allowing administrators to manage access control and resource isolation for specific AI initiatives, reducing the risk of cross-workload budget overruns.
📊 競品分析▸ Show
FeatureAWS Bedrock ProjectsGoogle Vertex AI (Projects/Labels)Azure AI Studio (Resource Groups)
Cost AttributionProject-based taggingLabel-based billingResource group/Tag-based
Pricing ModelPay-as-you-go (Inference)Pay-as-you-go (Inference)Pay-as-you-go (Inference)
GovernanceIAM-integrated ProjectsIAM-integrated ProjectsRBAC-integrated Resource Groups

🛠️ 技術深入

  • •Bedrock Projects function as a management layer that abstracts underlying API calls, allowing users to associate specific model invocation requests with a Project ID.
  • •The system relies on the AWS Resource Groups Tagging API to propagate metadata, ensuring that costs are correctly attributed in the AWS Cost and Usage Report (CUR) files.
  • •Implementation requires the creation of a 'Project' resource within the Bedrock console, which then generates a unique Amazon Resource Name (ARN) used to scope permissions and track usage metrics.
  • •Integration with AWS Data Exports allows for the automated delivery of cost data to Amazon S3, enabling custom analysis via Amazon Athena or Amazon QuickSight.

🔮 前景展望基於引用來源的 AI 分析

Automated budget enforcement will become a native feature of Bedrock Projects.
As cost attribution matures, AWS is likely to integrate AWS Budgets directly into the Project interface to trigger automated alerts or throttling when project-specific spending thresholds are reached.
Multi-tenant AI application architectures will shift toward Project-based isolation.
The ability to map specific inference costs to individual tenants or business units will drive adoption of Bedrock Projects as the standard for SaaS providers building on AWS.

⏳ 時間線

2023-04
Amazon Bedrock announced in preview to provide foundation models via API.
2023-09
Amazon Bedrock becomes generally available to all AWS customers.
2024-11
AWS introduces Bedrock Projects to improve resource organization and cost management.
☁️閱讀原文： AWS Machine Learning Blog
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