mirror of
https://github.com/NVIDIA/dgx-spark-playbooks.git
synced 2026-04-23 02:23:53 +00:00
40 lines
1.0 KiB
Docker
40 lines
1.0 KiB
Docker
# Use latest NVIDIA PyG container which includes cuGraph and graph-related packages
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FROM nvcr.io/nvidia/pyg:25.08-py3
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# Ensure we're running as root for system package installation
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USER root
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# Set working directory
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WORKDIR /app
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# Install system dependencies
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RUN apt-get update && apt-get install -y \
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curl \
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wget \
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git \
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build-essential \
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&& rm -rf /var/lib/apt/lists/*
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# Copy requirements first to leverage Docker cache
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COPY requirements.txt .
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# Install Python dependencies
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RUN pip install --no-cache-dir -r requirements.txt
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# Copy the service code
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COPY unified_gpu_service.py .
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COPY pygraphistry_service.py .
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# Create a non-root user for security (using a different UID to avoid conflicts)
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RUN useradd -m -u 1001 appuser && chown -R appuser:appuser /app
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USER appuser
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# Expose unified service port
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EXPOSE 8080
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# Health check for unified service
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HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
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CMD curl -f http://localhost:8080/api/health || exit 1
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# Start unified service
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CMD ["python", "unified_gpu_service.py"] |