openshift-docs VS Grafana

My first experience with OpenShift was with a task which was kind of a heavy task, I didn't know anything about OpenShift or K8s! but I was in charge of migrating resources from a cluster to one another! (twice!)

OpenShift is a container platform from Red Hat that's built on top of Kubernetes. It offers additional features like built-in CI/CD pipelines, enhanced security, and support for multiple programming languages and frameworks.

Openshift documentation can be hard to find, and installing an cluster without it can be hard. 🤗

For whatever reason, the PRs for adding CloudWatch and Loki/Vector to the docs haven't merged yet.

At your own pace, jump into orchestration using a Kubernetes distribution out there; but really, only do that fairly late in the game (e.g. OpenShift). Sadly, it's quite a jump from containers to orchestration, and there is no "smooth" in-between. Maybe as a prelude, you can look into etcd configuration clusters and Ceph storage clusters first, e.g. using a bunch of VMs on your machine, or a few Raspberry Pis. There are plenty of occasions to pinch your fingers with those, and thus valuable lessons to be learned :-)

Part of my job is to help document and assist with getting environment running offline, including OpenShift. While I don't use vSphere the general process is the same, while individual platforms may require different commands the concepts are all the same. Using docs.openshift.com you can find comprehensive guides in how you setup each platform Openshift supports "disconnected". But do realize that not all organizations agree on the exact definition of what disconnected means so you may need to adjust based on what you need. Some allow "sneaker net", others requires you to use old fashioned DVDs to bring all data onsite etc.

You want to be able to rebuild your clusters in case of a disaster, so, any time you install anything, export the yaml. And read https://docs.openshift.com/ for every new version.

- We are adding CNV docs to OKD

Monitoring application logs is a crucial aspect of the software development and deployment lifecycle. In this post, we'll delve into the process of observing logs generated by Docker container applications operating within HashiCorp Nomad. With the aid of Grafana, Vector, and Loki, we'll explore effective strategies for log analysis and visualization, enhancing visibility and troubleshooting capabilities within your Nomad environment.

To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along.

Visualization and Analysis: Choose a tool with intuitive and customizable dashboards, charts, and visualizations. A question to ask is, "Are the visualization features of this tool user-friendly and adaptable to our team's specific needs?" Tools like Grafana and Kibana provide powerful visualization capabilities.

Prometheus: Open-source monitoring system. Often used together with Grafana.

Grafana

Yes I'm aware that Grafana is open source but the method I used to find the API endpoints is far quicker than digging through hundreds of files in a codebase I'm not familiar with.

So, you will add one last container to allow us to visualize this data: Grafana, an open-source analytics and visualization platform that allows us to see traces and metrics simply. You can set Grafana to read data from both Tempo and Prometheus by setting them as datastores with the following grafana.datasource.yaml config file:

In example above, we use 2 additional parameters: code (HTTP response code) and page (page identifier), which provide detailed statistics. For example, you can build such graphs in Grafana:

Robin switched to the Grafana dashboard tab, and sure enough, the 5xx volume on web service was rising. It had not hit the critical alert thresholds yet, but customers had already started noticing.