gatekeeper-library VS cloud-custodian

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)

> The best optimization is simply shutting things off

This is the way.

A similar idea has been bouncing around in my mind for a while now. An ideal, turnkey system would do the following:

- Execute via Lambda (serverless).

- Support automated startup and shutdown of various AWS resources on a schedule influenced by specially formatted tags.

- Enable resources to be brought back up out of schedule when demand dictates.

- Operate as a TCP/HTTP proxy that can delay clients so that a given service can be started when it is dormant or, even better, the service isn't serverless but you want it to be. This can't work for everything, but perhaps enough things such that the need to run always on services is reduced.

Cloud Custodian [1] can purportedly do some of this, but I've been reluctant to learn yet another YAML-based DSL to use it.

So this is my "make things designed to be always-on serverless instead" project and the work AWS has done to make Java apps function on Lambda keeps me thinking about the potential to take things that 1) have a relatively long startup time and 2) are designed to be long running service loops, and find a way to force them into the serverless execution model.

[1] https://cloudcustodian.io/

Goal was to clear up anything old and set us up to rotate keys in use. Why did I do it in the end of December? It was a quarterly goal and I learned to push those across the line if I wanted a good review. Great incentive, that one. I used Cloud Custodian for this. It has a terrible bug where the code says you'll be acting on days since the key was used but actually is reading days since it was created.

What is wrong with https://github.com/cloud-custodian/cloud-custodian?

You can start reading about it here.

Use a tool like this https://cloudcustodian.io/ to manage instance on/off hours or go fargate.

Certs aside, there are some great compliance tools out there that you might want to become familiar with. Here is one that comes to mind (is open-source): https://cloudcustodian.io/

I'd use a combination of Cloudcustodian for start/stop scheduling and Apprise for notifications.

Cloud custodian is a good utility if config rules doesn’t satisfy your needs. It’s also cross platform.

AWS Security with open source – Cloud Custodian is a Cloud Security Posture Management (CSPM) tool. CSPM tools evaluate your cloud configuration and identify common configuration mistakes. They also monitor cloud logs to detect threats and configuration changes.