gatekeeper-library VS prometheus

Here is a library or rules for the Open Policy Agent.

https://github.com/open-policy-agent/gatekeeper-library is the library of OPA Gatekeeper policies.

Many more examples are available in the OPA Gatekeeper library project!

by default and exposes metrics on path ```/metrics``` . It can run locally on your development box as long as you have a valid Kubernetes configuration in your home folder (i.e. if you can run kubectl and have the right permissions). When running on the cluster a ```incluster``` parameter is passed in so that it knows where to look up for the cluster credentials. Exporter program connects to Kubernetes API every 10 seconds to scrape data from Kubernetes API. We've used [this](https://medium.com/teamzerolabs/15-steps-to-write-an-application-prometheus-exporter-in-go-9746b4520e26) blog post as the base for the code. ## Demo Let's go ahead and prepare our components so that we have a Grafana dashboard to show us which constraints have been violated and how the number of violations evolve over time. ### 0) Required tools - [Git](https://git-scm.com/downloads): A git cli is required to checkout the repo and - [Kubectl](https://kubernetes.io/docs/tasks/tools/) and a working K8S cluster - [Ytt](https://carvel.dev/ytt/): This is a very powerful yaml templating tool, in our setup it's used for dynamically overlaying a key/value pair in all constraints. It's similar to Kustomize, it's more flexibel than Kustomize and heavily used in some [Tanzu](https://tanzu.vmware.com/tanzu) products. - [Kustomize](https://kustomize.io/): Gatekeeper-library relies on Kustomize, so we need it too. - [Helm](https://helm.sh/): We will install Prometheus and Grafana using helm - Optional: [Docker](https://www.docker.com/products/docker-desktop): Docker is only optional as we already publish the required image on dockerhub. ### 1) Git submodule update Run ```git submodule update --init``` to download gatekeeper-library dependency. This command will download the [gatekeeper-library](https://github.com/open-policy-agent/gatekeeper-library) dependency into folder ```gatekeeper-library/library``` . ### 2) Install OPA/Gatekeeper If your K8S cluster does not come with Gatekeeper preinstalled, you can use install it as explained [here](https://open-policy-agent.github.io/gatekeeper/website/docs/install/). If you are familiar with helm, the easiest way to install is as follows: ```bash helm repo add gatekeeper https://open-policy-agent.github.io/gatekeeper/charts helm install gatekeeper/gatekeeper --generate-name

Gatekeeper library has example policies for restricting image repositories: https://github.com/open-policy-agent/gatekeeper-library/tree/master/library/general

You should check out the Gatekeeper project. There's plenty of templates available for use without having to write a single line of rego for most use cases (e.g https://github.com/open-policy-agent/gatekeeper-library)

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.