Skip to content

Azure AI Services Containers Guide

🧩 Problem

You need to use Azure AI services in environments where: * Sensitive data must remain on-premises.
* Latency between services and local data must be minimized. * Full control over hosting, networking, and authentication is required.

🚀 Solution with Azure

Use Azure AI services containers to run Azure Cognitive Services locally or in your own Azure infrastructure. This allows for secure, low-latency AI capabilities without sending data to the cloud.

🧱 Required Components

Component Description
Azure AI Services Container Image Specific to the feature (e.g., sentiment analysis, speech-to-text).
Container Host Where the container is deployed (e.g., Docker, ACI, AKS).
Azure AI Services Resource Required in Azure to enable billing and usage tracking.
API Key Used in container configuration for billing.
Billing Endpoint URI of the Azure resource used for metering.
EULA Acceptance Required to run the container (Eula=accept).

🏗️ Architecture / Development

  1. Download Container Image
    Use docker pull to retrieve the relevant container from the Microsoft Container Registry (MCR).

  2. Deploy the Container
    On Docker, Azure Container Instances (ACI), or Azure Kubernetes Service (AKS).

  3. Configure the Container
    Set required parameters:

  4. ApiKey=<your_key>
  5. Billing=<your_azure_endpoint>

  6. Eula=accept

  7. Consume the Service

  8. Applications send requests directly to the local container endpoint.
  9. No subscription key needed for each request.

  10. Use your own network and authentication policies.

  11. Billing

  12. Usage metrics are periodically sent to Azure for billing purposes.
  13. Sensitive data stays local; only usage is reported.

✅ Best Practices / Considerations

  • 🔒 Security: You can fully control authentication and access at the network level.
  • 🗂️ Granularity: Each AI capability (e.g., key phrase extraction, sentiment analysis) is in a separate container image.
  • 🕒 Latency: Local deployment reduces latency when accessing local data.
  • 📦 Portability: Containers are portable across environments (Linux, Windows, on-prem, Azure).
  • 📜 Licensing: You must accept the EULA to run containers.

❓ Simulated Exam Questions

  1. What are the three required parameters when configuring an Azure AI services container?
    👉 ApiKey, Billing, Eula

  2. Can you use Azure AI services containers without an Azure subscription?
    ❌ No. An Azure resource is required for billing and usage reporting.

  3. Why might you prefer to use containers for Azure AI services?
    ✅ To keep data on-premises, reduce latency, and have more control over security.

  4. Where can you deploy Azure AI services containers?
    👉 Docker server, Azure Container Instances (ACI), Azure Kubernetes Service (AKS)

  5. Are all AI features available in a single container?
    ❌ No. Each feature (e.g., language detection, sentiment analysis) has its own image.