GoCD vs. Google Kubernetes Engine

Previously, our team used Jenkins. However, since it's a shared deployment resource we don't have admin access. We tried GoCD as it's open source and we really like. We set up our deployment pipeline to run whenever codes are merged to master, run the unit test and revert back if it doesn't pass. Once it's deployed to the staging environment, we can simply do 1-click to deploy the appropriate version to production. We use this to deploy to an on-prem server and also AWS. Some deployment pipelines use custom Powershell script for.Net application, some others use Bash script to execute the docker push and cloud formation template to build elastic beanstalk.

Incentivized

If your application is complex, if it's planet-scale, or if you need autoscaling, then Kubernetes is best suited. If your application is straightforward, you can opt for App Engine or Cloud Run. In many cases, you can prefer to run the cloud on GKE. But once you deploy on Kubernetes, you get the flexibility to try different things. But if you don't seek flexibility, it's not an option for you.

Incentivized

• Pipeline-as-Code works really well. All our pipelines are defined in yml files, which are checked into SCM.
• The ability to link multiple pipelines together is really cool. Later pipelines can declare a dependency to pick up the build artifacts of earlier ones.
• Agents definition is really great. We can define multiple different kinds of environments to best suit our diverse build systems.

Incentivized

• Engine upgrade rollout strategy - well documented and configurable
• Integration with other Google Cloud services like the Compute Engine, SaaS databases, and some cloud networking like Cloud Armor
• Graphical interface for a lot of operations - either for a quick peek/overview or actual work done by administrators and/or developers (via the Google Cloud Console, for example)

Incentivized

• UI can be improved
• Location for settings can be re-arranged
• API for setting up pipeline

Incentivized

• Support of IPv6.
• Better GitOps.
• A "serverless" Kubernetes so we can install Google config connector will be really awesome.
• Container-native load balancers do not support internal TCP/UDP load balancers or network load balancers.

Incentivized

• Google Kubernetes Engine has a good UI and documentation that facilitates setup and helps get projects moving along quickly
• Its built-in logging integrations with StackDriver make it easier to monitor the application and log issues quickly
• Automated orchestration, deployment, and scaling of nodes and networking are all easily configurable with yaml files

Incentivized

Very good Kubernetes distribution with a reasonable total price. Integration with storage and load balancer for ingress and services speed up every process deployment.

Incentivized

GoCD is easier to setup, but harder to customize at runtime. There's no way to trigger a pipeline with custom parameters.

Jenkins is more flexible at runtime. You can define multiple user-provided parameters so when user needs to trigger a build, there's a form for him/her to input the parameters.

Incentivized

GKE spins up new nodes a LOT faster than AKS. GKE's auto scaler runs a lot smoother than AKS. GKE has a lot more Kubernetes features baked in natively.

Incentivized

• When issues came up, we reached out to some folks at GCP and they seemed to be very prompt and attentive to our needs. They were always willing to help and provide additional details or recommendations or links to resources. This kind of support is very helpful as it allows us to navigate GKE with more confidence.

Incentivized

• ROI has been good since it's open source
• Settings.xml need to be backed up periodically. It contains all the settings for your pipelines! We accidentally deleted before and we have to restore and re-create several missing pipelines
• More straight forward use of API and allows filtering e.g., pull all pipelines triggered after this date

Incentivized

• Reduced cloud computing costs.
• Easier management of applications.
• Extra time investment to learn how to setup applications in Google versus Amazon.

Incentivized