Continuous Integration and Continuous Deployment (CI/CD) are essential elements of modern software development practices, helping development teams build, test, and deploy code faster and more reliably. CircleCI is a popular CI/CD platform that enables developers to automate their workflows, reduce errors, and accelerate their deployment processes.

In this article, we will discuss five optimizations to help you speed up your deployment process with CircleCI. These optimizations may not be the most well-known, but they are highly effective and can greatly improve your development workflow. We will provide a thorough explanation of each optimization, along with practical examples and use cases.

1. Parallelism and Test Splitting

Parallelism is a powerful feature in CircleCI that allows you to run multiple jobs concurrently, significantly reducing the overall build time. To enable parallelism, you simply need to configure the parallelism setting in your CircleCI configuration file (.circleci/config.yml).

Test splitting is another powerful feature that complements parallelism. CircleCI's test splitting can automatically distribute your test suite across multiple containers, ensuring each container runs an equal amount of work. This helps to balance the workload and further reduces build times.

To enable test splitting, add the following to your CircleCI configuration file:

version: 2.1
jobs:
  build:
    parallelism: 4
    steps:
      - run:
          name: Run tests
          command: |
            circleci tests glob "tests/**/*_test.py" | circleci tests split --split-by=timings | xargs pytest

In this example, we set the parallelism to 4, which means that CircleCI will run the tests on four containers simultaneously. Test splitting ensures that the tests are evenly distributed across the containers, resulting in a faster build time.

2. Caching Dependencies and Workspaces

Caching dependencies and workspaces can significantly reduce build times by saving and reusing data across multiple jobs and workflows. CircleCI provides built-in support for caching dependencies and workspaces, making it simple to implement and optimize your build process.

To cache dependencies, add the following to your CircleCI configuration file:

- restore_cache:
    keys:
      - dependencies-{{ checksum "requirements.txt" }}
- save_cache:
    paths:
      - .venv
    key: dependencies-{{ checksum "requirements.txt" }}

In this example, CircleCI will cache the dependencies based on the checksum of the requirements.txt file. If the file hasn't changed, CircleCI will reuse the cached dependencies, reducing the time it takes to install them.

Workspaces can also be cached, allowing you to share data between jobs in a workflow. To cache a workspace, add the following to your CircleCI configuration file:

- persist_to_workspace:
    root: .
    paths:
      - output
In this example, the output directory is persisted to the workspace, allowing other jobs in the workflow to access and use the data.

3. Using CircleCI Orbs

CircleCI Orbs are reusable packages of YAML configuration that simplify the process of setting up and configuring CircleCI. They are designed to provide best practices and streamline the configuration process, enabling you to quickly integrate common tasks and tools into your CI/CD pipeline.

To use an Orb in your CircleCI configuration, you need to add the Orb to your configuration file:

version: 2.1
orbs:
  python: circleci/python@1.2.0

In this example, we added the CircleCI Python Orb, which provides a set of predefined jobs, commands, and executors for working with Python projects. By using Orbs, you can simplify your configuration and take advantage of the best practices provided by the community and CircleCI team.

Here's an example of using the Python Orb to set up a Python environment and run tests:

version: 2.1
orbs:
  python: circleci/python@1.2.0
jobs:
  build-and-test:
    executor: python/default
    steps:
      - checkout
      - python/install-packages
      - python/run-tests

In this example, the Python Orb handles the installation of packages and running tests, reducing the complexity of your CircleCI configuration and ensuring that you follow best practices.

4. Optimizing Docker Images

Using optimized Docker images can help to speed up your build process by reducing the size of the images and minimizing the time required for downloading and building them. CircleCI provides a set of pre-built Docker images that are optimized for use in CircleCI builds. These images are available in the CircleCI Docker Hub repository.

To use an optimized Docker image, update the docker section of your CircleCI configuration file:

jobs:
  build:
    docker:
      - image: circleci/python:3.8

In this example, we are using the CircleCI-provided Python 3.8 Docker image. By using optimized Docker images, you can ensure faster build times and a more efficient build process.

5. Conditional Job Execution

Conditional job execution allows you to run jobs only when certain conditions are met, such as when changes are made to specific files or branches. This can help to speed up your build process by skipping unnecessary jobs and focusing on the parts of your project that require attention.

To enable conditional job execution, you can use the when and unless keywords in your CircleCI configuration file:

jobs:
  deploy:
    steps:
      - run:
          name: Deploy to production
          command: ./deploy.sh
          when: << pipeline.parameters.deploy_to_production >>

In this example, the deploy job will only run when the deploy_to_production pipeline parameter is set to true. This allows you to control when certain jobs are executed, helping to optimize your build process and reduce build times.

Conclusion

CircleCI offers a wide range of powerful features and optimizations that can help you accelerate your deployment process. From parallelism and test splitting to caching and conditional job execution, these optimizations can greatly improve your development workflow and reduce build times.

By leveraging CircleCI's features and best practices, you can streamline your CI/CD pipeline, reduce errors, and ensure faster, more reliable deployments. Whether you're a seasoned developer or just getting started with CircleCI, these optimizations can help you get the most out of your CI/CD pipeline and focus on what really matters: delivering high-quality software.

However, simply using CircleCI might not be enough to get the best out of your project space, an engineering analytics tool can equip you with the data-driven insights you need to place your team on top. Hatica offers metrics across 13 dashboards, powered by CI/CD tools, JiraGitHub, Azure, CircleCI and GitLab. By collating tool activities at one place, Hatica helps teams streamline their workflow and improve productivity.

Subscribe to the Hatica blog today to read more about unblocking developers, and boosting productivity with engineering analytics. 

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Table of Contents
  • 1. Parallelism and Test Splitting
  • 2. Caching Dependencies and Workspaces
  • 3. Using CircleCI Orbs
  • 4. Optimizing Docker Images
  • 5. Conditional Job Execution
  • Conclusion
  • TL;DR