vcluster VS Grafana

Kubernetes? You mean the container orchestration system where they forgot to add Multi-tenancy? And no namespaces are not Multi-tenancy...

https://www.vcluster.com/

Whats the difference between this and vcluster (https://github.com/loft-sh/vcluster)?

Yep, as we see it they compliment each other quite well. DevPod takes your workspace to the cloud and DevSpace let's you develop against your Kubernetes cluster - potentially the same one you used to start your workspace.

Internally we use both in our development setup, spinning up remote workspaces using DevPod, installing DevSpace and kind into the devcontainer, then using DevSpace to develop against the cluster. See the vcluster setup[1] as an example

[1]https://github.com/loft-sh/vcluster/tree/main/.devcontainer

The tenants are internal dev teams so yeah maybe not. I was considering multi-tenanting different environments isolated at the kube layer with vCluster and have the vCluster pods running in Kata containers giving maximum isolation but still having a single management cluster. Ideally also avoiding the need to buy a second set of hardware for a dev environment

Vcluster

Looks interesting. How does this solution compare to vcluster?

sounds like the best option for you , is a tool called VCluster by loft ( https://www.vcluster.com/) , this way you can install as many k8s cluster as you want in the same k8s host cluster , those cluster share workers nodes and networking, but each has a separated "api server" , so it looks like you have a dedicated cluster with their own namespaces and tools . take a look at the docs to get a better understanding and how they work.

We're about to run a PoC with vcluster for isolated sandboxes, this might be relevant to you too

I think namespaces, RBAC and network policies are sufficient to partition users from the same organisation. I would investigate the use of vcluster ig you want to give your users even more isolation and capability (such as installing CRDs)

Depends on the use case. Namespaces provides soft isolation (so it means they share same Apiserver, PV's and global resources such as CRD's), but can be restricted with network policies. So it means, there's still potential in breaking other namespaces if you change PV's or CRD's which are used by other namespaces. Multi-Cluster solution can provide full isolation, but its also really expensive in resource consumption and maintenance/management effort. If namespaced-isolation isnt enough for your use case, you can consider vclusters (https://www.vcluster.com/)

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.