argo-cd VS prometheus

The code above will create the argocd Kubernetes namespace and deploy the latest stable manifest. If you would like to install a specific manifest, have a look here.

In this blog post, we will demonstrate how easy and fast it is to deploy Sveltos on an RKE2 cluster with the help of ArgoCD, register two RKE2 Cluster API (CAPI) clusters and create a ClusterProfile to deploy Prometheus and Grafana Helm charts down the managed CAPI clusters.

Argo CD

$version = (Invoke-RestMethod https://api.github.com/repos/argoproj/argo-cd/releases/latest).tag_name Invoke-WebRequest -Uri "https://github.com/argoproj/argo-cd/releases/download/$version/argocd-windows-amd64.exe" -OutFile "argocd.exe"

This is cool - I can think of some projects that are amazing as first contributors, and others I can think of that are terrible.

One thing I think the tool doesn't address is why someone should contribute to a particular project. Having stars is interesting, and a proxy for at least historical activity, but also kind of useless here - take argoproj/argo-cd [1] as an example - 14.5k stars, with a backlog of 2.7k issues and an issue tracker that's a real mess.

Either way, I think this tool is neat for trying to gain some experience in a project purely based on language.

[1] https://github.com/argoproj/argo-cd/issues?q=is%3Aissue+is%3...

In our case, our team went ahead with Solution B, as that was the only solution present when the issue occurred. However, with the release of Argo CD 2.8.0 (released on August 7, 2023), things have changed - for the better :). Now, there are two ways to handle the sharding issue with the Argo CD Application Controller:

$ kubectl create namespace argocd //Next, let's apply the yaml configuration files for ArgoCd $ kubectl apply -n argocd -f https://raw.githubusercontent.com/argoproj/argo-cd/stable/manifests/install.yaml //Now we can view the pods created in the ArgoCD namespace. $ kubectl get pods -n argocd //To interact with the API Server we need to deploy the CLI: $ curl --silent --location -o /usr/local/bin/argocd https://github.com/argoproj/argo-cd/releases/download/v2.4.7/argocd-linux-amd64 $ chmod +x /usr/local/bin/argocd //Expose argocd-server $ kubectl patch svc argocd-server -n argocd -p '{"spec": {"type": "LoadBalancer"}}' //Wait about 2 minutes for the LoadBalancer creation $ kubectl get svc -n argocd //Get pasword and decode it. $ kubectl get secret argocd-initial-admin-secret -n argocd -o yaml $ echo WXVpLUg2LWxoWjRkSHFmSA== | base64 --decode

From here, we can explore other developments and tutorials on Kubernetes, such as o11y or observability (PLG, ELK, ELF, TICK, Jaeger, Pyroscope), service mesh (Linkerd, Istio, NSM, Consul Connect, Cillium), and progressive delivery (ArgoCD, FluxCD, Spinnaker).

lol! Wham! Third choice! https://github.com/argoproj/argo-cd

If you mean for each app, I don't think it's listed anywhere though you may find it in `repo-server` logs. Like so

WriteRequest::timeseries is a vector (https://github.com/prometheus/prometheus/blob/main/prompb/re...) and

Developers widely use Prometheus as a system for operational monitoring and alerting for their projects. Here is a list of tools for monitoring frontend services with Prometheus.

Just to give an example of the power of Go for CLI builds, you may have already used or at least heard of Docker, Kubernetes, Prometheus, Terraform, but what do they all have in common? They all have a large part of their usability via CLI and are developed in Go 🐿.

Distributed system administrators need mechanisms and tools for monitoring individual nodes in order to analyze the system and promptly detect anomalies. Developers also need effective mechanisms for analyzing, diagnosing issues, and identifying bugs in protocol implementations. Logging, tracing, and collecting metrics are common observability techniques to allow monitoring and obtaining diagnostic information from the system; most of the explored code bases use these techniques. OpenTelemetry and Prometheus are popular open-source monitoring solutions, which are used in many of the explored code bases.

Setting up monitoring for a system, especially one involving GRPC communication, provides crucial visibility into its operations. In this guide, we walked through the steps to instrument both a GRPC server and client with Prometheus metrics, exposed those metrics via an HTTP endpoint, and visualized them using Grafana. The Docker-Compose setup simplified the deployment of both Prometheus and Grafana, ensuring a streamlined process.

Alerting and Notification: Select a tool with flexible alerting mechanisms to proactively detect anomalies or deviations from defined thresholds. Consider asking questions like "Does this tool offer customizable alerting options and support notification channels that suit our team's communication preferences?" A tool like Prometheus provides robust alerting capabilities.

Prometheus

Prometheus is an open-source monitoring and alerting toolkit. It is designed to monitor highly dynamic containerized systems, making it an excellent choice for monitoring Docker containers and Kubernetes clusters.

wget https://github.com/prometheus/prometheus/releases/download/v2.46.0/prometheus-2.46.0.linux-amd64.tar.gz

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