Part 1 - Set Up A CI Pipeline

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Introduction

In the world of software development, Continuous Integration (CI) is a crucial practice that helps automate the build, test, and deployment of software applications. By implementing a CI pipeline, developers can ensure that their code is of high quality, reliable, and meets the required standards. In this article, we will explore the process of setting up a CI pipeline for a Python application using GitHub Actions.

What is a CI pipeline?

A CI pipeline is a series of automated processes that are triggered by code changes in a repository. The pipeline consists of several stages, including:

  1. Build: The code is compiled and packaged into a deployable format.
  2. Test: The code is executed and tested to ensure it meets the required standards.
  3. Scan: The code is scanned for security vulnerabilities and compliance issues.

Setting up a CI pipeline with GitHub Actions

To set up a CI pipeline with GitHub Actions, we need to create a .github/workflows folder in our repository. This folder will contain our action files, which define the pipeline's workflow.

Step 1: Create a new workflow file

Create a new file in the .github/workflows folder, e.g., ci.yml. This file will define the pipeline's workflow.

name: CI Pipeline

on:
  push:
    branches:
      - main

jobs:
  build-and-test:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
        uses: actions/checkout@v2
      - name: Lint code
        run: |
          python -m pylint --output-format=text .
      - name: Run tests
        run: |
          python -m pytest

This workflow file defines a pipeline that runs on the main branch. The pipeline consists of two steps:

  1. Checkout code: This step checks out the code from the repository.
  2. Lint code: This step runs the linter on the code to check for programmatic or stylistic errors.
  3. Run tests: This step runs the unit tests on the code.

Step 2: Add a linter to the Dockerfile

To add a linter to the Dockerfile, we need to use the Hadolint linter. Hadolint is a Dockerfile linter that checks for security vulnerabilities and compliance issues.

# Use an official Python runtime as a parent image
FROM python:3.9-slim

# Set the working directory to /app
WORKDIR /app

# Copy the requirements file
COPY requirements.txt .

# Install the dependencies
RUN pip install --no-cache-dir -r requirements.txt

# Copy the application code
COPY . .

# Run the linter
RUN hadolint Dockerfile

This Dockerfile uses the Hadolint linter to check for security vulnerabilities and compliance issues.

Step 3: Add unit and integration tests with Pytest

To add unit and integration tests with Pytest, we need to create a pytest.ini file in the root of our repository.

[pytest]
addopts = --junit-xml=report.xml

This file defines the Pytest configuration, including the output format and the test report file.

Step 4: Add a Static Application Security Testing (SAST) with Bandit

To add a SAST with Bandit, we need to install the Bandit library and add it to our requirements.txt file.

pip install bandit

This library checks for common security vulnerabilities in Python code.

Step 5: Build our container application with Docker and add a container vulnerability scanning with Trivy

To build our container application with Docker and add a container vulnerability scanning with Trivy, we need to create a Dockerfile and a trivy.yml file in the root of our repository.

# Use an official Python runtime as a parent image
FROM python:3.9-slim

# Set the working directory to /app
WORKDIR /app

# Copy the requirements file
COPY requirements.txt .

# Install the dependencies
RUN pip install --no-cache-dir -r requirements.txt

# Copy the application code
COPY . .

# Run the linter
RUN hadolint Dockerfile

trivy:
  enabled: true
  ignore_unfixed: true
  ignore_vulnerable: true

This file defines the Trivy configuration, including the vulnerability scanning settings.

Step 6: Add a Software Component Analysis (SCA) by generating an SOBM with Syft and scan the recently generated SOBM with Grype

To add a SCA by generating an SOBM with Syft and scan the recently generated SOBM with Grype, we need to install the Syft and Grype libraries and add them to our requirements.txt file.

pip install syft grype

This library checks for security vulnerabilities in software components.

Conclusion

Introduction

In the previous article, we explored the process of setting up a CI pipeline for a Python application using GitHub Actions. In this article, we will answer some frequently asked questions (FAQs) related to setting up a CI pipeline with GitHub Actions.

Q: What is a CI pipeline?

A CI pipeline is a series of automated processes that are triggered by code changes in a repository. The pipeline consists of several stages, including building, testing, scanning, and deployment.

Q: Why do I need a CI pipeline?

A CI pipeline helps ensure that your code is of high quality, reliable, and meets the required standards. It automates the build, test, and deployment process, reducing the risk of errors and improving the overall development experience.

Q: How do I set up a CI pipeline with GitHub Actions?

To set up a CI pipeline with GitHub Actions, you need to create a .github/workflows folder in your repository and define a workflow file (e.g., ci.yml) that specifies the pipeline's stages and actions.

Q: What are the different stages of a CI pipeline?

The different stages of a CI pipeline include:

  1. Build: The code is compiled and packaged into a deployable format.
  2. Test: The code is executed and tested to ensure it meets the required standards.
  3. Scan: The code is scanned for security vulnerabilities and compliance issues.
  4. Deployment: The code is deployed to a production environment.

Q: How do I add a linter to my CI pipeline?

To add a linter to your CI pipeline, you need to install a linter library (e.g., Hadolint) and add it to your requirements.txt file. You can then specify the linter in your workflow file (e.g., ci.yml) to run it as part of the pipeline.

Q: How do I add unit and integration tests to my CI pipeline?

To add unit and integration tests to your CI pipeline, you need to install a testing library (e.g., Pytest) and add it to your requirements.txt file. You can then specify the testing library in your workflow file (e.g., ci.yml) to run it as part of the pipeline.

Q: How do I add a SAST to my CI pipeline?

To add a SAST to your CI pipeline, you need to install a SAST library (e.g., Bandit) and add it to your requirements.txt file. You can then specify the SAST library in your workflow file (e.g., ci.yml) to run it as part of the pipeline.

Q: How do I add a container vulnerability scanning to my CI pipeline?

To add a container vulnerability scanning to your CI pipeline, you need to install a container vulnerability scanning library (e.g., Trivy) and add it to your requirements.txt file. You can then specify the container vulnerability scanning library in your workflow file (e.g., ci.yml) to run it as part of the pipeline.

Q: How do I add a SCA to my CI pipeline?

To add a SCA to your CI pipeline, you need to install a SCA library (e.g., Syft) and add it to your requirements.txt file. You can then specify the SCA library in your workflow file (e.g., ci.yml) to run it as part of the pipeline.

Conclusion

In this article, we answered some frequently asked questions (FAQs) related to setting up a CI pipeline with GitHub Actions. We covered topics such as the different stages of a CI pipeline, adding a linter, unit and integration tests, SAST, container vulnerability scanning, and SCA. By following these steps, developers can ensure that their code is of high quality, reliable, and meets the required standards.

Additional Resources