Wednesday, August 16

In the defense of sar (and how to configure it)

Let me discuss a topic that is not inherently PostgreSQL specific, but that I regularly run into while investigating issues on customer systems, evaluating “supportability” of those systems, etc. It’s the importance of having a monitoring solution for system metrics, configuring it reasonably, and why sar is still by far my favorite tool (at least on Linux).

On the importance of monitoring

Firstly, monitoring of basic system metrics (CPU, I/O, memory) is extremely important. It’s a bit strange having to point this in discussions with other engineers, but I’d say 1 in 10 engineers thinks they don’t really need monitoring. The reasoning usually goes along these lines:

It’s just another source of useless overhead. You don’t really need monitoring unless there’s an issue, and issues should be rare. And if there’s an issue, we can enable the monitoring temporarily.

It’s true monitoring adds overhead, no doubt about it. But it’s likely negligible compared to what the application is doing. Actually, sar is not really adding any extra instrumentation, it’s merely reading counters from the nernel, computing deltas and writing that to disk. It may need some disk space and I/O (depending on number of CPUs and disks) but that’s about it.

For example collecting per-second statistics on a machine with 32 cores and multiple disks will produce ~5GB of raw data per day, but it compresses extremely well, often to ~5-10%). And it’s barely visible in top. Per-second resolution is a bit extreme, and using 5 or 10 seconds will further reduce the overhead.

So no, turns out the overhead actually is not a valid reasons not to enable monitoring.

Costs vs. benefits

More importantly though, “How much overhead do I eliminate by not enabling monitoring?” is the wrong question to ask. Instead you should be asking “What benefits do I get from the monitoring? Do the benefits outweigh the costs?”

We already know the costs (overhead) are fairly small or entirely negligible. What are the benefits? In my experience, having monitoring data is effectively invaluable.

Firstly, it allows you to investigate issues – looking at a bunch of charts and looking for sudden changes is surprisingly effective, and often leads you directly to the right issue. Similarly, comparing the current data (collected during the issue) to a baseline (collected when everything is fine) is very useful, and impossible if you only enable monitoring when things break.

Secondly, it allows you to evaluate trends and identify potential issues before they actually hit you. How much CPU are you using? Is the CPU usage growing over time? Are there some suspicious patterns in memory usage? You can only answer those questions if you have the monitoring in place.

Why sar is my favorite tool

Let’s assume I’ve convinced you monitoring is important and you should definitely do it. But why is sar our favorite tool, when there are various fancy alternatives, both on-premise and cloud based?

  • It’s included in all distributions, ans is trivial to install/setup. This makes it fairly simple to convince people to enable it.
  • It’s right on the machine. So if you SSH to the machine, you can also get the monitoring data.
  • It’s using simple text output. Trivial process the data – import it into a database, analyze, attach it to a support ticket. That’s pretty difficult with other tools that generally don’t allow you to export the data easily, only show charts and/or significantly restrict what analysis you can perform, etc.

I do admit some of this comes from the fact that I work for a company providing PostgreSQL services to other companies (be it 24×7 support or Remote DBA. So we usually get only a very limited access to customer systems (mostly just database servers and nothing more). That means having all the important data on the database server itself, accessible over plain SSH, is extremely convenient and eliminates unnecessary round-trips only to request another piece of data from some other system. Which saves both time and sanity on both sides.

If you have many systems to manage, you’ll probably prefer a monitoring solution that collects data from many machines to a single place. But for me, sar still wins.

So, how to configure it?

I mentioned installing and enabling sar (or rather sysstat, which is the package including sar) is very simple. Unfortunately, the default configuration is somewhat bad. After installing sysstat, you’ll find something like this in /etc/cron.d/sysstat (or wherever your distribution stores cron configuration):

*/10 * * * * root /usr/lib64/sa/sa1 1 1

This effectively says the sa1 command will be executed every 10 minutes, and it will collect a single sample over 1 second. There are two issues, here. Firstly, 10 minutes is fairly low resolution. Secondly, the sample only covers 1 second out of 600, so the remaining 9:59 are not really included in it. This is somewhat OK for long-term trending, where low-resolution random sampling is sufficient. For other purposes you probably need to do something like this instead:

* * * * * root /usr/lib64/sa/sa1 -S XALL 60 1

Which collects one sample per minute, and every sample covers one minute. The -S XALL means all statistics should be collected, including interrupts, individual block devices and partitions, etc. See man sadc for more details.

Summary

So, to sum this post into a few simple points:

  • You should have monitoring, even if you think you don’t need it. Once you run into issues, it’s too late.
  • The costs of monitoring are probably negligible, but certainly much lower than the benefits of having the monitoring data.
  • sar is convenient and very efficient. Maybe you’ll use something else in the future, but it’s good first step.
  • The default configuration is not particularly great (low resolution, 1-second samples). Consider increasing the resolution.

One thing I haven’t mentioned is that sar only deals with system metrics – CPU, disks, memory, processes, not with PostgreSQL statistics. You should definitely monitor that part of the stack too, of course.

2 Comments

    • I don’t think there’s anything akin to sar, i.e. “simple and on the same machine”. You can snapshot the statistics catalogs, but that’s about it.

      With regular monitoring systems (collecting data from multiple machines/services to a central place), I’d say collectd/grafana is a good choice. A simple alternative is Munin, but it has various limitations as it’s RRD-based.

Leave a Reply

Your email address will not be published. Required fields are marked *