Block troublemakers using fail2ban

An article, posted about 2 years ago filed in how i do it, debian, unix, configuration, server & devops.

I don't mind running my own virtual servers. Fail2ban is a tool I've had running on my servers for years. It helps fencing of requests from ip-addresses that repeatedly misbehave when connecting to SSH and postfix. I never got to creating my own rules. I thought I had to write it in some arcane scripting language, but recently I learned it is pretty easy.

In this case I wanted to block 500 (internal server error) and 422 (Unprocessable Entity) errors. A server error once in a while is expected, but repeated server errors are suspicious. Common source of these errors are scripts that scan for things like SQL injections.

Examples given are for Debian.

/etc/fail2ban/filter.d/nginx-errors.conf

[Definition]

failregex = ^ -.*"(GET|POST|HEAD).*HTTP.*" (500|422)
port = http,https
ignoreregex =
backend = auto
logpath = /var/log/nginx/access.log
bantime = 600
maxretry = 10

And appending to /etc/fail2ban/jail.local

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Prometheus for slow stats

An article, posted about 5 years ago filed in development, engineering, cluster, management, devops, rails, ruby on rails, ruby, logging & monitoring.

Prometheus is a statistics collecting tool that originated from SoundCloud. Designed to be used in high performance environments, it is build to be blazingly fast. Hence, the client typically is expected to be blazingly fast as well, gathering and presenting data within nanoseconds. For Ruby on Rails applications however this has lead to an unresolved issue with the Prometheus ruby-client when the same application is forked (typical for Puma, Passenger and other popular ruby-servers). The Prometheus client collects data within its own fork before serving it to the exporter endpoint. This can or cannot be a problem. When you measuring response times, running averages from a random fork may be good enough. However, when you're also counting data over time you're having separate counters in …

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