I am unsure about which monitoring framework to use. Currently I am looking at either Nagios or Sensu.
Can anybody give me a good reference which shows a comparison of these two (or any other monitoring tool which may be a good solution)? My main intention is to scale-out on EC2. I am using Opscode Chef for system integration.
One important difference between Nagios and Sensu -
Nagios requires all the configuration for 1)checks 2)handlers but most importantly 3)hosts to be written in configuration files on the Nagios server. This means that each time one of the 3 above is changed (for example new hosts added, old hosts removed) you need to re-write the configuration files and restart Nagios.
Sensu is almost the same as the above, with one important difference -- when hosts are added or removed from your architecture (as is the case in most auto-scaling cloud deployments) -- the hosts themselves run a sensu-client that "subscribes" to different available checks. So when a new server comes into existence and says "I'm a webserver", the sensu-client running on it will ask the sensu-server "what checks should a webserver run on itself?" and run those.
Other than this, operations wise both Nagios (also Icinga) and Sensu are great and have a lot of facilities for checks, handlers, and visibility through a dashboard (YMMV).
From a little recent experience with Sensu and quite a bit of experience with Nagios I'd say both are excellent choices.
Sensu is definitely the new kid. It has a nice UI and nice API. It does however require Redis and RabbitMQ in your setup to work. So consider if you'll therefore want something to monitor those dependencies outside the sensu monitoring stack. Sonian provide Chef recipes for trying it out too.
https://github.com/sensu/sensu-chef
Nagios has been around for an awfully long time. It's generally packaged for most distros which makes installation simple and it has few dependencies. It's track record also means that finding people who know it or that have used it and can offer advice is easy. On the other hand the UI is ugly and programatic access is often hacky or via third party add-ons. Chef recipes also exist for Nagios:
https://github.com/bryanwb/chef-nagios
If you have time I'd try both, there is little harm in having two monitoring systems running as a trial. The main think to focus on, especially in a dynamic EC2 setup, is how easily the monitoring configuration files can be generated by your configuration management tool.
In terms of other tools I'd personally include something to record time series data, for instance requests per second or load over time. Graphs are a great help with monitoring, and can be used to drive alerting via Nagios or similar. Personally I'm a fan of both Ganglia and Graphite while Librato Metrics (https://metrics.librato.com/) is a very nice non-free option.
I tried using Nagios for a while: I got the feeling that the only reason that it's common is that 'everyone else uses it', because it's absolutely hideous to work with. Massively overcomplicated, difficult and long-winded to make it do anything new: if you find something it doesn't do, you know you're in for a week of swearing at crummy documentation of an archaic design. At the end of all your efforts and it's all working, it looks hideous. Scrapping it made me sleep better.
Cacti looks nice, but again it's unnecessarily complex when creating new plugins.
For graphing I'd recommend Munin: it's completely trivial to write new plugins in any language, there are hundreds available, and it looks reasonable. It's incredibly easy to install - one command to install and set one access rule, so works well for automated deployments, easy to wrap into a chef recipe. 2.0 is out soon and addresses most of its shortcomings (in particular adding variable update intervals, zoomable graphs, ssh transport). Munin can talk to Nagios for notifications, or it can do that itself, and it provides a basic dashboard.
For local process/file/service monitoring, monit is simpler and works better than god. I've not tried it with m/monit.
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