GitLab CI and Kubernetes: deploying Applications continuously to Kubernetes | Alexander Trost

Alexander Trost
TestingAutomation

Deploy applications continuously to Kubernetes with GitLab CI and Kubernetes, automating the process from code changes to application availability with scalable and manageable container deployment.

Key takeaways
  • GitLab CI and Kubernetes can be used to deploy applications continuously to Kubernetes.
  • A container and Kubernetes are essential parts of the process.
  • To start, you need a Kubernetes cluster and a Git repository.
  • A developer creates a merge request in GitLab, which is a way to present changes to others.
  • After reviewing the changes, the code is merged, and the pipeline is triggered.
  • The pipeline runs the application and builds a Docker image.
  • The image is pushed to the GitLab registry, and a Kubernetes deployment is triggered.
  • The deployment spins up the containers, and the application is available.
  • Kubernetes provides a way to scale and manage the application.
  • To roll back or roll forward, a developer can use the GitLab CI and Kubernetes.
  • A typos in code can be caught during the normal testing phase.
  • The speaker recommends automating the testing and building process.
  • The speaker suggests using GitLab CI and Kubernetes for automating tasks.
  • The speaker suggests using templates for GitLab CI and Kubernetes.
  • There are different ways to integrate GitLab CI and Kubernetes, such as using a Kubernetes cluster per repository or per project.
  • The speaker thinks that having a private GitLab instance makes it easier to integrate with Kubernetes.
  • The speaker suggests revisiting some parts of the talk for further explanation.
  • The speaker recommends consulting the GitLab documentation for more information.
  • The speaker suggests using CI runners to automate tasks.
  • The speaker suggests making use of cascade deleting.
  • The speaker suggests using external tools, such as Prometheus operator.
  • The speaker recommends using metadata to automate tasks.
  • The speaker suggests using artifacts to store and share data.
  • The speaker recommends double-checking for typos.
  • The speaker recommends using wildcard certificates for external access.

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