Monitoring sucks, don’t make it worse

You don’t have to go too far to find someone who thinks monitoring sucks. It’s definitely true that monitoring can be big, ugly, and complicated. I’m convinced that many of the problems in monitoring are not technical, but policy issues. For the sake of clarity (and because I’m like that), let’s start with some definitions. These definitions may or may not have validity outside the scope of this post, but at least they will serve to clarify what I mean when I say things.

  • Monitoring – an automatic process to collect metrics on a system or service
  • Alerting – notification when a critical threshold has been reached

In the rest of this post, I will be throwing some former colleagues under the bus. It’s not personal, and I’m responsible for some of the problem as well. The group in question has a monitoring setup that is dysfunctional to the point of being worthless. Not all of the problems are policy-related, but enough are to prompt this post. It should be noted that I’m not an expert on this subject, just a guy with opinions and a blog.

Perhaps the most important thing that can be done when setting up a monitoring system is coming up with a plan. It sounds obvious, but if you don’t know what you’re monitoring, why you’re monitoring it, and how you’re monitoring it, you’re bound to get it wrong. This is my first rule: in monitoring, failing to plan is planning to not notice failure.

It’s important to distinguish between monitoring and alerting. You can’t alert on what you don’t monitor, but you don’t need to alert on everything you monitor. This is one area where it’s easy to shoot yourself in the foot, especially at a large scale. Many of the monitoring checks were in reaction to something going wrong. As a result, Nagios ended up alerting for things like “a compute node has 95% memory utilization.” For servers, that’s important. For nodes, who cares? The point of the machines is to do computation. Sometimes that means chewing up memory.

Which brings me to rule number two: every alert should have a reaction. If you’re not going to do something about an alert, why have it in the first place? It’s okay to monitor without alerting — the information can be important in diagnosing problems or analyzing usage — but if an alert doesn’t result in a human or automated reaction, shut it off.

Along that same line, alerts should be a little bit painful. Don’t punish yourself for something failing, but don’t make alerts painless either. Perhaps the biggest problem in the aforementioned group is that most of the admins filtered Nagios messages away. That immediately killed any incentive to improve the setup.

I took the alternate approach and weakly lobbied for all alerts to hit the pager. This probably falls into the “too painful” category. You should use multiple levels of alerts. An email or ticket is fine for something that needs to be acted on but can wait until business hours. A more obnoxious form of alert should be used for the Really Important Things[tm].

The great thing about having a little bit of pain associated with alerts is that it also acts as incentive to fix false alarms. At one point, I wrote Nagios checks to monitor HTCondor daemons. Unfortunately, due to the load on the Nagios server, the checks would timeout and produce alerts. The daemons were fine and the cond0r_master process generally does a good job of keeping things under control. So I removed the checks.

The opposite problem is running checks outside the monitoring system. One colleague had a series of cron jobs that checked the batch scheduler. If the checks failed, he would email the group. Don’t work outside the system.

Finally, be sure to consider planned outages. If you can’t suppress alerts when things are broken intentionally, you’re going to have a bad time. As my friend tweeted: “Rough estimates indicate we sent something like 180,000 emails when our clusters went down for maintenance.”

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  1. Pingback: Monitored self « Blog Fiasco

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