In 2017 I had the opportunity to spend a year working as a devops or platform engineer. I have mainly worked as a software engineer before so moving in to an automate and operate role was a bit of a leap. This was a fully remote engagement where I was embedded with and helped bootstrap the client’s first platform team.
The first few months we focused on building out the CI/CD with Jenkins pipelines and a great deal of AWS cli scripting. Once we got the basics working teams started to come out of microservices training and began developing against it. This was the start of operational support for us and started a bit of a scramble while we tried to balance new features and the stability of the platform with hiring and onboarding.
We used jenkins pipelines, docker and cloudformation to provide our users with a solid customizable pipeline solution. Using our default templates development teams could easily bootstrap their pipeline with CI/CD from dev to canary deploys in production. If they needed more than a stateless microservice we enabled them to provide cloudformation templates in their github repository that would be run with each deploy to ensure the AWS environment was bootstrapped for their needs.
We started out with the intention of using Jenkins pipelines with ansible to automate things, but the client’s team was more experienced with CloudFormation and as a result I ended up writing most of our initial CI/CD code in a combination of groovy and AWS cli calls. This proved unwieldy and eventually led us to using Groovy + Cloudformation for nearly everything. Cloudformation works but it is locked into AWS and its programming model is a somewhat awkward. Cloudformation’s saving grace is the first class integration and editor. Next time I would recommend starting with a commitment to Terraform or Ansible.
In the 3rd quarter we started work on implementing Canary deployments. Our solution ended up being a combination of a customized client side load balancing http client and jenkins pipelines. I started us off with a proof of concept that proved easier to write than we expected which put us on good footing for the rest of the project. One of the client’s employees took advantage of the space we had to rewrite the shared jenkins pipeline library in more idiomatic language which turned out to be a great improvement.
We went live in Q4 and I moved on to another project. I am moving back into application development, I ended up doing 100% automation scripting instead of the 50-50 split I was expecting. So it will be good to get back to writing applications.