Fail2Ban VS thanos

now some things you need to think about: - cloud init - this will need to be secure so lock it down hard anything not needed an alternative OS to look at if you have the ability's is https://www.alpinelinux.org/ also as these devices are not that powerfull every extra agent / abstaction layer you add impacts performance need to look at low over head security https://www.crowdsec.net/ and https://github.com/fail2ban/fail2ban (if you call fail2ban security) - using certificates to authenticate ssh login

See https://github.com/fail2ban/fail2ban for beginner's guide, basically you set it up to monitor logfiles and it would act accordingly (plenty of built-in config to handle various daemons so you don't have to write yourself).

- Nginx & crowdsec/fail2ban if you are exposing your parts (services) to the public ( https://hub.docker.com/r/baudneo/nginx-proxy-manager, https://www.crowdsec.net, https://www.fail2ban.org )

— In /etc/fail2ban/action.d/cloudflare.conf I copied the file from https://github.com/fail2ban/fail2ban/blob/master/config/action.d/cloudflare.confand added my ‘cftoken’ and ‘cfuser’ on the bottom

https://github.com/fail2ban/fail2ban is a mature, easy to set up way to have some dynamic firewall rules that respond to attacks. There are more sophisticated options, but they are probably not worth the return on time investment for you.

You can create your own regexes for custom services: https://github.com/fail2ban/fail2ban/wiki/Developing-Regex-in-Fail2ban

Others seem to be (or were) experiencing this too: https://github.com/fail2ban/fail2ban/issues/3100

Monitoring = netdata on each RPi https://www.netdata.cloud/ binded to the vpn interface being scraped into a prometeus thaons https://thanos.io/ setup with grafana to give management the Green all is good screens (very important).

Sounds like you want something like Thanos

Yes, but also no. The Prometheus ecosystem already has two FOSS time-series databases that are complementary to Prometheus itself. Thanos and Mimir. Not to mention M3db, developed at Uber, and Cortex, then ancestor of Mimir. There's a bunch of others I won't mention as it would take too long.

Long term storage all depends on your needs and sophistication. I use Thanos for our system since it has an extremely flexible scaling system. But there is also Grafana Mimir. They're both similar in that they use Prometheus TSDB format as part of the underlying storage. One nice Thanos advantage is that it does do downsampling in addition to being able to store raw metric data for a long time. It will auto-select downsampled data to make requests faster.

You can aggregate all your clusters Prometheus metrics together with a wonderful tool called Thanos. This will allow you to use just a single Grafana instance against Thanos and using a label select which cluster you wish to see metrics from. The downside of this, is that none of the Grafana dashboards from the internet will work as-is. You'll need to customize all of them for Thanos support. The other downside is, you have a single point of failure, and (see next item) you can't customize who can access what in regards to your dev vs production data/metrics/access.

Depending on how you want to set things up, you can use Thanos or Mimir to create the single-pane-of-glass view of your data.

You could look at something like Thanos and store your data in S3: https://thanos.io/