Deploying PaddleOCR PDF OCR service on Azure Container Apps
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This practical infrastructure guide details deploying a PaddleOCR document extraction service to Azure Container Apps using single-container HTTP ingress. It breaks down the trade-offs across three distinct workload engines—text, vision-language, and structure—and their corresponding resource profiles on Azure. While the lightweight text engine runs cost-effectively on standard CPU Consumption profiles (0.25 to 4 vCPUs), higher-capacity document processing demands specialized GPU workload profiles to accommodate up to 10.5 GB of VRAM. Backend developers running containerized workloads get a step-by-step model for balancing memory constraints, workload profile selection, and scaling costs on Azure platform infrastructure.