Upload Gitlab CI artifacts to S3
Upload Gitlab CI artifacts to S3

With GitLab CI it is incredibly easy to build a Hugo website (like mine); you can even host it there. But in my case I use AWS S3 and Cloudfront because it is cheap and easy to setup. The CI pipeline to build and upload the static website is also straightforward with the following .gitlab-ci.yml: variables: GIT_SUBMODULE_STRATEGY: recursive stages: - build - upload build: stage: build image: monachus/hugo script: - hugo version - hugo only: - master artifacts: paths: - .

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Secure deployment to Kubernetes with a service account
Secure deployment to Kubernetes with a service account

Now that I have a number of pipelines running I would like to deploy these to Kubernetes through a service account. that is quite simple. As an admin user provide resources such as: the namespaces, optionally with limited resources; an isolated service account with restricted access to one namespace; an encoded config file to be used by the Gitlab pipeline. Service Account with permissions The following file serviceaccount.yaml creates the service account, a role, and attach that role to that account:

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Terraform Pipelines with GitLab CI
Terraform Pipelines with GitLab CI

Gitlab-CI is awesomelishiously simple. Let’s assume you have a Terraform Gitlab project with a folder structure like mine: README.md .gitignore terraform │ main.tf │ outputs.tf └──variables.tf You can find a .gitignore example here. Since we can provide our credentials via environment variables, the provider can look like: provider "aws" { version = ">= 2.28.1" } In the Gitlab project page, go to “Settings” > “CI/CD” > “Variables”, and set the following variables:

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Python Django with Docker and Gitlab CI
Python Django with Docker and Gitlab CI

For a project I was specifically asked to build an API using Python Django. So, my first starting point was to google “django cookiecutter” which immediately brought me to this amazing cookiecutter project. What I am going to demonstrate here is how to quickly setup the project (for the sake of completeness) and use Gitlab Continuous Integration to automatically unit test, run linters, generate documentation, build a container and release it.

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