dnviti
d6d44270ee
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BREAKING CHANGE: Monolithic ci.yml split into focused pipeline files ## Pipeline Reorganization Split single CI/CD pipeline into 7 specialized workflows: 1. **lint.yml** - Code quality checks (Black, Ruff, MyPy) 2. **test.yml** - Test suite with coverage reporting 3. **security.yml** - Security scanning (Bandit) 4. **build.yml** - Docker image builds and registry push 5. **deploy-staging.yml** - Staging environment deployment 6. **deploy-production.yml** - Production deployment (tags only) 7. **docs-generation.yml** - Scheduled documentation generation ## Benefits - **Modularity**: Each pipeline has single responsibility - **Performance**: Workflows run independently, faster feedback - **Clarity**: Easier to understand and maintain - **Flexibility**: Trigger pipelines independently - **Debugging**: Isolated failures easier to diagnose ## Dockerfile Improvements - Fix FROM AS casing (was 'as', now 'AS') in all Dockerfiles - Resolves Docker build warnings - Improves consistency across build files ## Documentation - Added .gitea/workflows/README.md with: - Workflow descriptions and triggers - Dependency diagram - Environment variables reference - Troubleshooting guide - Best practices ## Migration Notes - Old monolithic pipeline backed up as ci.yml.old - All triggers preserved from original pipeline - No changes to build or deploy logic - Same environment variables and secrets required 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
65 lines
1.7 KiB
Docker
65 lines
1.7 KiB
Docker
# Dockerfile for Celery Worker Service
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FROM python:3.12-slim AS builder
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WORKDIR /build
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# Install Poetry
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RUN pip install --no-cache-dir poetry==1.8.0
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# Copy dependency files
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COPY pyproject.toml poetry.lock ./
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# Export dependencies
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RUN poetry config virtualenvs.create false \
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&& poetry export -f requirements.txt --output requirements.txt --without-hashes
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# Runtime stage
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FROM python:3.12-slim
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LABEL maintainer="automation-team@company.com"
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LABEL description="Datacenter Documentation Background Worker"
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# Install system dependencies for network automation
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RUN apt-get update && apt-get install -y \
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gcc \
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libpq-dev \
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openssh-client \
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snmp \
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curl \
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&& rm -rf /var/lib/apt/lists/*
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WORKDIR /app
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# Copy requirements from builder
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COPY --from=builder /build/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 application code and package definition
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COPY src/ /app/src/
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COPY config/ /app/config/
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COPY templates/ /app/templates/
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COPY pyproject.toml README.md /app/
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# Install poetry-core (required for install with pyproject.toml)
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RUN pip install --no-cache-dir poetry-core
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# Install the package
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RUN pip install --no-cache-dir /app
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# Set PYTHONPATH to ensure module can be imported
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ENV PYTHONPATH=/app/src:$PYTHONPATH
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# Create necessary directories
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RUN mkdir -p /app/logs /app/output
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# Create non-root user
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RUN useradd -m -u 1000 appuser && \
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chown -R appuser:appuser /app
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USER appuser
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# Run the Celery worker with specific queues
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CMD ["celery", "-A", "datacenter_docs.workers.celery_app", "worker", "--loglevel=info", "--concurrency=4", "-Q", "documentation,auto_remediation,data_collection,maintenance,celery"]
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