All metrics are scar tissue (unless they're Business Intelligence)

I've now spent over a decade teaching how alarms are supposed to work (specific, actionable, with the appropriate urgency) and even wrote a book on how to manage metrics systems. One topic I was repeatedly asked to cover in the book, but declined because the topic is big enough for its own book, is how to do metrics right. The desire for an expert to lay down how to do metrics right comes from a number of directions:

  • No one ever looked at ours in a systematic way and our alerts are terrible [This is asking about alerts, not metrics; but they still were indirectly asking about metrics]
  • We keep having incidents and our metrics aren't helping, how do we make them help?
  • Our teams have so many alarms important ones are getting missed [Again, asking about alerts]
  • We've half assed it, and now we're getting a growth spurt. How do we know what we should be looking for?

People really do conflate alarms/alerts with metrics, so any discussion about "how do we do metrics better" is often a "how do we do alarms better" question in disguise. As for the other two points, where people have been using vibes to pick metrics and that's no longer scaling, we actually do have a whole lot of advice; you have a whole menu of "golden signals" to pick from depending on how your application is shaped.

That's only sort of why I'm writing this.

In the mathematical construct of Site Reliability Engineering, where everything is statistics and numerical analysis, metrics are easy. Track the things that affect availability, regularly triage your metrics to ensure continued relevance, and put human processes into place to make sure you're not burning out your worker-units. But the antiseptic concept of SRE only exists in a few places, the rest of us have to pollute the purity of math with human emotions. Let me explain.

Consider your Incident Management process. There are certain questions that commonly arise when people are doing the post incident reviews:

  • Could we have caught this before release? If so, what sort of pre-release checks should we add to catch this earlier?
  • Did we learn about this from metrics or customers? If customers, what metrics do we need to add to catch this earlier? If metrics, what processes or alarms should we tune to catch this earlier?
  • Could we have caught this before the feature flag rolled out to the Emerald users? Do we need to tune the alarm thresholds to catch issues like this in groups with less feature-usage before the high value customers on Emerald plans?

And so on. Note that each question asks about refining or adding metrics. Emotionally, metrics represent anxieties. Metrics are added to catch issues before they hurt us again. Metrics are retained because they're tracking something that used to hurt us and might hurt again. This makes removing metrics hard; the people involved remember why certain metrics are present, intuitively know they needs tracking, which means emotion says to keep.

Metrics are scar tissue, and removing scar tissue is hard, bloody work. How do you reduce the number of metrics, while also not compromising your availability goals? You need the hard math of SRE to work down those emotions, but all it takes is one Engineering Manager to say "this prevented a SEV, keep it" to blow that effort up. This also means you'll have much better luck with a metric reformation effort if teams are already feeling the pinch of alert fatigue or your SaaS metric provider bills are getting big enough that the top of the company is looking at metric usage to reduce costs.

Sometimes, metrics feed into Business Intelligence. That's less about scar tissue and more about optimizing your company's revenue operations. Such metrics are less likely to lead to rapid-response on-call rotations, but still can lead to months long investigations into revenue declines. That's a different but related problem.

I could write a book about making your metrics suck less, but that book by necessity has to cover a lot of human-factors issues and has to account for the role of Incident Management in metrics sprawl. Metrics are scar tissue, keep that in mind.