Capstone for Udacity Cloud DevOps

Git Repo

https://github.com/boods/UdacityDevOpsCapstone

Planning

I'm interested in playing the violin, and have been thinking about building an application for tracking practice progress. This project will setup a CI/CD pipeline for the first component of that application - a very basic python webapi, built using flask, to return a list of skills that can be practiced.

The target environment for deployments will comprise a VPN with two public subnets, an EKS cluster and nodegroup, and two bastion hosts (one in each subnet)

The pipeline will work as follows:

1. Code will be checked into a github repo
2. A Jenkins server, running on an EC2 will monitor changes in the repo, and trigger builds
3. Jenkins will download the latest source
4. Jenkins will run pylint on the python code, and hadolint on the dockerfile
5. Jenkins will run the python unit tests
6. On successful linting, the Jenkins will build a docker image and push it to dockerhub, with the 'latest' tag
7. Finally, jenkins will perform a rolling update on the kubernetes cluster

The following diagram depicts the typical pipline flow:

Soure Code

The repo consists for the following:

• Jenkinsfile - the build pipline file used by the Jenkins instance
• skills.yaml - kubernetes manifest for the skills webserver
• skills-service.yaml - kubernetes manifest for the kubernetes load balancer
• skills/tests - python unit tests (test_skills.py)
• infrastructure/ - AWS cloudformation templates for setting up the target environment, and bash scripts to create, update and delete the environment
• skills/ - the python application (skills.py), Makefile, DockerFile, and requirements.txt (detailing python library dependencies)

Proving the pipline

Linting

Make a breaking change to the python code and check it into github:

Confirm that the build fails on the pylint step:

Fix the python error, but make a breaking change to the dockerfile and check that into git hub:

Confirm that the build is still failing, this time on the hadolint step:

Fix the dockerfile issue, commit the change and confirm that the linting is successful

And full deployment is working:

Rolling Deployment

View the output with curl prior to deployment:

Make a small change to the skills.py to publish a new skill, and commit the change:

Confirm the rolling deployment is performed by Jenkins:

Confirm the output with curl after deployment - notice the additional skill appearing:

Perform a test where an EC2 instance in the cluster is taken offline, and a replacement instance started: