I'm currently working as a Software Development Engineer in Test (SDET), and while I've got a basic deployment script for AWS Beanstalk up and running, I'm feeling a bit lost when it comes to best practices for using GitLab in conjunction with AWS. Our team is transitioning from Azure to AWS, and previously we were using a combination of GitLab, TeamCity, and Octopus Deploy. Now, we're aiming to consolidate everything under GitLab.
Here are some specific concerns and questions I have:
1. I've seen that Azure typically uses VMs for builds, while I'm unsure how much of our Azure .yml files can actually be reused in AWS.
2. We're currently leveraging AWS Beanstalk for our environment, but we used Infrastructure as Code (IaC) previously. I think we're planning to move to Terraform soon. My question is, how is infrastructure setup related to build pipelines? I might be asking something obvious here.
3. Is Beanstalk the best option for our needs? It seems like a lot of people are shifting towards AWS ECS. Are Helm charts involved in that scenario?
4. Are there any other crucial considerations I should be aware of? I'm used to GitLab mainly for testing, so this is a lot to get used to.
Any insights would be greatly appreciated!
1 Answer
It sounds like you're in a pretty common situation when switching from Azure to AWS. First off, yes, your old Azure .yml files likely won't be compatible with AWS, so you might need to rewrite those for GitLab. GitLab can handle both VM and container-based builds, but you'll want to check which setup works best for your needs—like using a GitLab runner on ECS or Kubernetes.
Regarding AWS Beanstalk, while it's a decent option for simple applications, many teams are indeed moving towards AWS ECS or EKS for better scalability and management. Helm charts are great if you're going the ECS route since they help manage Kubernetes applications.
Make sure to check out the GitLab runners and the different executors they offer; this might really streamline your pipeline!
Definitely explore the autoscaler feature of GitLab runners if you need shared runners. It can save you a lot of headaches!