Vertex AI Agent Engine 是 Vertex AI 平台的一部分,這組服務可讓開發人員在正式環境中部署、管理及調度 AI 代理。Agent Engine 會處理基礎架構,以便在正式環境中調度代理,讓您專心打造應用程式。Vertex AI Agent Engine 提供下列服務,可單獨或搭配使用:
Vertex AI Agent Engine 支援多項功能,可協助您符合企業安全防護規定、遵守貴機構的安全防護政策,以及遵循安全防護最佳做法。支援的功能如下:
客戶自行管理的加密金鑰 (CMEK):Vertex AI Agent Engine 支援 CMEK,可使用您自己的加密金鑰保護資料,讓您擁有及全權控管用來保護 Google Cloud靜態資料的金鑰。詳情請參閱「Agent Engine CMEK」。
VPC Service Controls:Vertex AI Agent Engine 支援 VPC Service Controls,可強化資料安全性並降低資料竊取風險。設定 VPC Service Controls 後,已部署的代理程式會保留 Google API 和服務 (例如 BigQuery API、Cloud SQL Admin API 和 Vertex AI API) 的安全存取權,確保在您定義的範圍內順暢運作。最重要的是,VPC 服務控管機制可有效封鎖所有公開網際網路存取權,將資料移動限制在授權網路邊界內,大幅提升企業安全狀態。
[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["難以理解","hardToUnderstand","thumb-down"],["資訊或程式碼範例有誤","incorrectInformationOrSampleCode","thumb-down"],["缺少我需要的資訊/範例","missingTheInformationSamplesINeed","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間:2025-09-04 (世界標準時間)。"],[],[],null,["# Vertex AI Agent Engine overview\n\n| [VPC-SC security controls](/vertex-ai/docs/general/vpc-service-controls)\n| and [Customer-managed encryption keys (CMEK)](/vertex-ai/docs/general/cmek) are\n| supported by Vertex AI Agent Engine. Data residency (DRZ) and Access Transparency (AXT)\nsecurity controls aren't supported. \n| To see an example of getting started with Vertex AI Agent Engine,\n| run the \"Building and Deploying an Agent with \" notebook in one of the following\n| environments:\n|\n| [Open in Colab](https://colab.research.google.com/github/GoogleCloudPlatform/generative-ai/blob/main/gemini/agent-engine/intro_agent_engine.ipynb)\n|\n|\n| \\|\n|\n| [Open in Colab Enterprise](https://console.cloud.google.com/vertex-ai/colab/import/https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fgenerative-ai%2Fmain%2Fgemini%2Fagent-engine%2Fintro_agent_engine.ipynb)\n|\n|\n| \\|\n|\n| [Open\n| in Vertex AI Workbench](https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fgenerative-ai%2Fmain%2Fgemini%2Fagent-engine%2Fintro_agent_engine.ipynb)\n|\n|\n| \\|\n|\n| [View on GitHub](https://github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/agent-engine/intro_agent_engine.ipynb)\n\nVertex AI Agent Engine, a part of the Vertex AI Platform, is a\nset of services that enables developers to deploy, manage, and scale AI agents\nin production. Agent Engine handles the infrastructure to scale agents in\nproduction so you can focus on creating applications.\nVertex AI Agent Engine offers the following services that you can\nuse individually or in combination:\n\n- **Runtime**:\n\n - [Deploy](/vertex-ai/generative-ai/docs/agent-engine/deploy) and scale agents with a managed runtime and end-to-end management capabilities.\n - Customize the agent's container image with build-time installation scripts for system dependencies.\n - Use security features including VPC-SC compliance and configuration of authentication and IAM.\n - Access models and tools such as [function calling](/vertex-ai/generative-ai/docs/multimodal/function-calling).\n - Deploy agents built using [different Python frameworks](#supported-frameworks):\n - Understand agent behavior with [Google\n Cloud Trace](/vertex-ai/generative-ai/docs/agent-engine/manage/tracing) (supporting [OpenTelemetry](https://opentelemetry.io/)), [Cloud Monitoring](/vertex-ai/generative-ai/docs/agent-engine/manage/monitoring), and [Cloud Logging](/vertex-ai/generative-ai/docs/agent-engine/manage/logging).\n- **Quality and evaluation** (Preview): Evaluate agent quality with the integrated\n [Gen AI Evaluation service](/vertex-ai/generative-ai/docs/agent-engine/evaluate) and optimize agents with Gemini model training runs.\n\n- [**Example Store**](/vertex-ai/generative-ai/docs/example-store/overview) (Preview): Store and dynamically retrieve few-shot examples to improve agent performance.\n\n- [**Sessions**](/vertex-ai/generative-ai/docs/agent-engine/sessions/overview) (Preview): Agent Engine Sessions lets you store individual interactions between users and agents, providing definitive sources for conversation context.\n\n- [**Memory Bank**](/vertex-ai/generative-ai/docs/agent-engine/memory-bank/overview) (Preview): Agent Engine Memory Bank lets you store and retrieve information from sessions to personalize agent interactions.\n\nVertex AI Agent Engine is part of [Vertex AI Agent Builder](/vertex-ai/generative-ai/docs/agent-builder/overview), a suite of features for discovering, building, and deploying AI agents.\n| **Note:** Because the name of Vertex AI Agent Engine changed over time, the name of the resource in the API reference is [`ReasoningEngine`](/vertex-ai/generative-ai/docs/reference/rest/v1/projects.locations.reasoningEngines) to maintain backwards compatibility.\n\nCreate and deploy on Vertex AI Agent Engine\n-------------------------------------------\n\n**Note:** For a streamlined, *IDE-based* development and deployment experience with Vertex AI Agent Engine, consider the [agent-starter-pack](https://github.com/GoogleCloudPlatform/agent-starter-pack). It provides ready-to-use templates, a built-in UI for experimentation, and simplifies deployment, operations, evaluation, customization, and observability.\n\nThe workflow for building an agent on Vertex AI Agent Engine is:\n\nThe steps are illustrated by the following diagram:\n\n\u003cbr /\u003e\n\nSupported frameworks\n--------------------\n\nThe following table describes the level of support Vertex AI Agent Engine provides for various agent frameworks:\n\nDeploy in production with Agent Starter Pack\n--------------------------------------------\n\nThe [Agent Starter Pack](https://github.com/GoogleCloudPlatform/agent-starter-pack) is a collection of production-ready generative AI agent templates built for Vertex AI Agent Engine. The Agent Starter Pack provides the following:\n\n- **Pre-built agent templates:** ReAct, RAG, multi-agent, and other templates.\n- **Interactive playground**: Test and interact with your agent.\n- **Automated infrastructure** : Uses [Terraform](https://cloud.google.com/docs/terraform) for streamlined resource management.\n- **CI/CD pipelines**: Automated deployment workflows leveraging Cloud Build.\n- **Observability**: Built-in support for Cloud Trace and Cloud Logging.\n\nTo get started, see the [Quickstart](https://github.com/GoogleCloudPlatform/agent-starter-pack?tab=readme-ov-file#-get-started-in-1-minute).\n\nUse cases\n---------\n\nTo learn about Vertex AI Agent Engine with end-to-end examples, see the following\nresources:\n\nEnterprise security\n-------------------\n\nVertex AI Agent Engine supports several features to help you meet\nenterprise security requirements, adhere to your organization's security\npolicies, and follow security best practices. The following features are\nsupported:\n\n- **Customer-managed encryption keys (CMEK)** : Vertex AI Agent Engine\n supports [CMEK](/kms/docs/cmek) to protect your data with your own encryption keys,\n which gives you ownership and full control of the keys that protect your data at\n rest in Google Cloud. For more information, see\n [Agent Engine CMEK](/vertex-ai/generative-ai/docs/agent-engine/manage/access#cmek).\n\n- **VPC Service Controls** : Vertex AI Agent Engine supports\n [VPC Service Controls](/vertex-ai/docs/general/vpc-service-controls) to strengthen data\n security and mitigate the risks of data exfiltration. When VPC Service Controls\n is configured, the deployed agent retains secure access to Google APIs and\n services, such as BigQuery API, Cloud SQL Admin API, and Vertex AI API,\n verifying seamless operation within your defined perimeter. Critically,\n VPC Service Controls effectively blocks all public internet access, confining\n data movement to your authorized network boundaries and significantly\n enhancing your enterprise security posture.\n\n | **Note:** If you use Vertex AI Agent Engine in a VPC-SC environment, you must create an ingress rule in your perimeter to allow ingress from the Reasoning Engine Service Agent (`service-`\u003cvar translate=\"no\"\u003ePROJECT_NUMBER\u003c/var\u003e`@gcp-sa-aiplatform-re.iam.gserviceaccount.com`) to `storage.googleapis.com` service and `artifactregistry.googleapis.com` service.\n- **Private Service Connect interface** : [PSC-I](/vpc/docs/about-private-service-connect-interfaces)\n lets your agents interact with privately hosted services in user's VPC. For\n more information, see [Configure VPC Service Controls interface](/vertex-ai/generative-ai/docs/agent-engine/deploy#psc-i).\n\n- **HIPAA** : As a part of Vertex AI Platform,\n Vertex AI Agent Engine supports [HIPAA](/security/compliance/hipaa)\n workloads.\n\nSupported regions\n-----------------\n\nVertex AI Agent Engine is supported in the following regions:\n\nFor [Agent Engine Memory Bank](/vertex-ai/generative-ai/docs/agent-engine/memory-bank/overview) (Preview), the following regions are supported:\n\nQuota\n-----\n\nThe following limits apply to [Vertex AI Agent Engine](/vertex-ai/generative-ai/docs/agent-engine/overview) for a given project in each region: \n\nPricing\n-------\n\nThe pricing for the Agent Engine Runtime is based on\nthe compute (vCPU hours) and memory (GiB hours) your agent uses to process\nrequests. There is no charge for the time a deployed agent is idle.\n\nFor more information, see [pricing](/vertex-ai/pricing#agent_engine).\n\nWhat's next\n-----------\n\n- [Set up the environment](/vertex-ai/generative-ai/docs/agent-engine/set-up).\n- [Get support](/vertex-ai/generative-ai/docs/agent-engine/support)."]]