Evolution of application deployment over the past 20 years.
Configure your local and remote lab environments.
Covers the resource types that are included with Kubernetes.
•Pod
•Job
Using helm to manage Kubernetes resources
Example microservice application.
Kubernetes manifests to deploy the demo application.
Explore how custom resources can add functionality
Install additional software to enhance the deployment.
Improving the DevX when working with Kubernetes.
How to safely upgrade your clusters and nodes.
Implement CI/CD for your applications (with GitOps!)
One nice thing about GKE is that out of the box you get log aggregation. I can go here to my cluster and get logs from the control plane, or I can go to the logging page and get logs from all of my different services. I can filter down to specific ones. This is important. Previously, we've been only looking at logs by issuing a kubectl log command. Those logs would only persist through the lifecycle of the pod, and so you'll want to ship your logs to some log aggregation system. Here, Google is handling that for us and pulling those logs off of our containers into its logging platform where we can then observe and search over time as well as see them all in one aggregated place. If we click into the workloads tab here, in the overview it shows all the different services that we've deployed as well as their status. We can then click into the observability tab and see the usage of various services. In this case, let's narrow down to our demo app namespace, and now you can see the various apps that we've deployed. It also gives us different events that we've created. Here, this is showing me when I've modified a deployment or when I've deleted a deployment. If you're looking at this and you see a spike, you can very easily dive in and see whether it corresponded to some action that you took. Maybe you upgraded a deployment, and that caused your memory usage to spike. You could then go back and look at what changed in that version of your application and figure out why that had happened. Of the managed cluster offerings, I would say Google's observability tooling is the most mature that I've seen. On Civo, there is some log aggregation that's still in kind of a beta state, but I don't think they have anything quite like this in terms of being able to see your metrics and correlate those to events in the cluster. You could deploy your own observability stack. You can deploy something like Prometheus to collect the metrics and Grafana, which is a tool for building dashboards, and you could query Prometheus and build dashboards like this, but having it work with no additional configuration on our end is pretty nice here within GKE.