解決方案構想 Solution Idea
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使用 Azure AI 工具和雲端平臺，新一代的 AI 啟用混合式應用程式可在您的資料所在位置執行。With the Azure AI tools and cloud platform, the next generation of AI-enabled hybrid applications can run where your data lives. 使用 Azure Stack Hub，將定型的 AI 模型帶到邊緣，並將其與您的應用程式整合，以獲得低延遲的智慧，而不需要為本機應用程式進行任何工具或程式變更。With Azure Stack Hub, bring a trained AI model to the edge and integrate it with your applications for low-latency intelligence, with no tool or process changes for local applications. 有了 Azure Stack Hub，您可以確保雲端解決方案即使在與網際網路中斷連線的情況下仍可運作。With Azure Stack Hub, you can ensure that your cloud solutions work even when disconnected from the internet.
架構Architecture
下載此架構的SVG 。
Download an SVG of this architecture.
資料流程Data Flow
- 資料科學家會使用 Azure Machine Learning Studio (傳統) 和 HDInsight 叢集來定型模型。Data scientists train a model using Azure Machine Learning Studio (classic) and an HDInsight cluster. 模型是容器化的，並放入 Azure Container Registry。The model is containerized and put in to an Azure Container Registry.
- 此模型會透過圖表中未顯示的步驟部署到 Azure Stack Hub 上的 Kubernetes 叢集。The model is deployed via steps not represented in the diagram to a Kubernetes cluster on Azure Stack Hub.
- 終端使用者提供對模型評分的資料。End users provide data that is scored against the model.
- 評分中的見解和異常會放置在儲存體中，以供稍後上傳。Insights and anomalies from scoring are placed into storage for later upload.
- 全域相關且符合規範的見解可在全域應用程式中取得。Globally-relevant and compliant insights are available in the global app.
- 來自邊緣評分的資料會用來改善模型。Data from edge scoring is used to improve the model.
元件Components
- HDInsight：布建雲端 Hadoop、Spark、R 伺服器、HBase 和風暴叢集HDInsight: Provision cloud Hadoop, Spark, R Server, HBase, and Storm clusters
- Azure Machine Learning Studio (傳統) ：輕鬆地建立、部署及管理預測性分析解決方案Azure Machine Learning Studio (classic): Easily build, deploy, and manage predictive analytics solutions
- 虛擬機器：在幾秒鐘內布建 Windows 和 Linux 虛擬機器Virtual Machines: Provision Windows and Linux virtual machines in seconds
- Azure Kubernetes Service (AKS) ：簡化 Kubernetes 的部署、管理和作業Azure Kubernetes Service (AKS): Simplify the deployment, management, and operations of Kubernetes
- 儲存體：持久、高可用性且可大幅調整的雲端儲存體Storage: Durable, highly available, and massively scalable cloud storage
- Azure Stack Hub：跨雲端界限建立並執行創新的混合式應用程式Azure Stack Hub: Build and run innovative hybrid applications across cloud boundaries
後續步驟Next steps
- HDInsight 文件HDInsight documentation
- Azure Machine Learning Studio (傳統) 文件Azure Machine Learning Studio (classic) documentation
- 虛擬機器文件Virtual Machines documentation
- Azure Kubernetes Service (AKS) 文件Azure Kubernetes Service (AKS) documentation
- 儲存體檔Storage documentation
- Azure Stack Hub 文件Azure Stack Hub documentation