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AWS CodeBuild vs GitLab CI: What are the differences?
Introduction
In this article, we will compare AWS CodeBuild and GitLab CI to understand their key differences. Both services are popular choices for implementing continuous integration and delivery (CI/CD) pipelines, but they have distinct features and capabilities.
Pricing: AWS CodeBuild has a pay-per-use pricing model, where you are billed based on the number of minutes your build executes and the compute resources used. GitLab CI, on the other hand, is part of the GitLab platform and is typically priced as part of a subscription bundle. The pricing structure of these services differs significantly, and it is important to consider your specific requirements and budget when choosing between them.
Hosting: AWS CodeBuild is a fully managed service offered by Amazon Web Services (AWS), meaning that you don't have to worry about infrastructure management. It provides a scalable, reliable, and secure environment to build and test your code. On the other hand, GitLab CI can be self-hosted on your infrastructure or used as a SaaS offering provided by GitLab. This gives you more control over the environment and allows for customization, but it also requires additional effort for setup and maintenance.
Integration with other AWS Services: AWS CodeBuild seamlessly integrates with other AWS services like AWS CodeCommit, AWS CodePipeline, and AWS CodeDeploy. This integration enables you to easily build and deploy applications within the AWS ecosystem. GitLab CI, on the other hand, provides integrations with a wide range of tools and platforms, including AWS, but it does not have the same level of native integration with AWS services as CodeBuild.
Extensibility and Customization: GitLab CI allows you to define complex pipelines using a declarative YAML configuration file, providing a lot of flexibility and customization options. You can define stages, jobs, and workflows tailored to your specific needs. AWS CodeBuild also supports custom buildspec files to define your build process, but it may not offer the same level of extensibility and customization as GitLab CI.
Community and Ecosystem: GitLab CI benefits from a vibrant and active open-source community, with many contributors regularly adding new features, fixing bugs, and providing support. This community-driven aspect of GitLab CI results in a rich ecosystem of plugins, extensions, and integrations that can enhance your CI/CD workflow. While AWS CodeBuild has its own community and ecosystem, it may not have the same level of third-party contributions as GitLab CI.
Ease of Use and Learning Curve: AWS CodeBuild provides a simple and intuitive interface that makes it easy to set up and configure builds. It integrates well with other AWS services and follows AWS best practices. GitLab CI, on the other hand, requires some familiarity with YAML configuration files and the GitLab platform. While it offers powerful features, it may have a steeper learning curve for beginners.
In summary, AWS CodeBuild and GitLab CI differ in terms of pricing, hosting options, integration with other services, extensibility, community support, and ease of use. Choosing between them depends on your specific requirements, budget, infrastructure preferences, and familiarity with the platform.
We are a mid-size startup running Scala apps. Moving from Jenkins/EC2 to Spinnaker/EKS and looking for a tool to cover our CI/CD needs. Our code lives on GitHub, artifacts in nexus, images in ECR.
Drone is out, GitHub actions are being considered along with Circle CI and GitLab CI.
We primarily need:
- Fast SBT builds (caching)
- Low maintenance overhead (ideally serverless)
- Everything as code
- Ease of use
I think I've tried most of the CI tools out there at some point. It took me a while to get around to Buildkite because at first I didn't see much point given it seemed like you had to run the agent yourself. Eventually it dawned on me why this approach was more ingenious than I realised:
Running my app in a production (or production-like) environment was already a solved problem, because everything was already in some form of "everything as code". Having a test environment where the only difference was adding the Buildkite agent was a trivial addition.
It means that dev/test/prod parity is simple to achieve and maintain. It's also proven to be much easier to support than trying to deal with the problems that come with trying to force an app to fit into the nuances and constraints that are imposed by the containers/runtime of a CI service. When you completely control all of the environment the tests are running in you define those constraints too. It's been a great balance between a managed service and the flexibility of running it yourself.
And while none of my needs have hit the scale of Shopify (I saw one of their engineers speak about it at a conference once, I can't find the video now though 😞) it's good to know I can scale out my worker nodes to hundreds of thousands of workers to reduce the time it takes for my tests to run.
I would recommend you to consider the JFrog Platform that includes JFrog Pipelines - it will allow you to manage the full artifact life cycle for your sbt, docker and other technologies, and automate all of your CI and CD using cloud native declarative yaml pipelines. Will integrate smoothly with all your other toolset.
more configurable to setup ci/cd: * It can provide caching when build sbt, just add this section to yml file * Easy to use, many documentation
Weakness: * Need use gitlab as repository to bring more powerful configuration
Buddy is one of the most easy-to-use tools for CI I ever met. When I needed to set up the pipeline I was really impressed with how easy it is to create it with Buddy with only a few moments. It's literally like: 1. Add repo 2. Click - Click - Click 3. You're done and your app is on prod :D The top feature that I've found is a simple integration with different notification channels - not only Slack (which is the one by default), but Telegram and Discord. The support is also neat - guys respond pretty quickly on even a small issue.
Pros of AWS CodeBuild
- Pay per minute7
- Parameter Store integration for passing secrets5
- Integrated with AWS4
- Streaming logs to Amazon CloudWatch3
- Bit bucket integration3
- GitHub Webhooks support2
- AWS Config and Config rule integration for compliance2
- VPC PrivateLinks to invoke service without internet2
- Windows/.NET support1
- Jenkins plugin integration1
- Ondemand scaling of build jobs1
- Scheduled builds with CloudWatch Events integration1
- Local build debug support1
- Native support for accessing Amazon VPC resources1
- Docker based build environment1
- Support for bringing custom Docker images1
- Fully managed (no installation/updates, servers to mai1
- PCI, SOC, ISO, HIPAA compliant1
- Full API/SDKs/CLI support1
- YAML based configuration1
- Great support (forums, premium support, SO, GitHub)1
- Perpetual free tier option (100 mins/month)1
- GitHub Enterprise support1
Pros of GitLab CI
- Robust CI with awesome Docker support22
- Simple configuration13
- All in one solution9
- Source Control and CI in one place7
- Integrated with VCS on commit5
- Free and open source5
- Easy to configure own build server i.e. GitLab-Runner5
- Hosted internally2
- Built-in Docker Registry1
- Built-in support of Review Apps1
- Pipeline could be started manually1
- Enable or disable pipeline by using env variables1
- Gitlab templates could be shared across logical group1
- Easy to setup the dedicated runner to particular job1
- Built-in support of Kubernetes1
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Cons of AWS CodeBuild
- Poor branch support2
Cons of GitLab CI
- Works best with GitLab repositories2