Introduction

It is curious how often you humans manage to obtain that which you do not want.

- Spock

Dashboards are useless! They are a waste of time. Get Netflix if you want to watch something. It’s cheaper than any other option.

Why dashboards?#

I repeated those words on many public occasions. I think that companies exaggerate the need for dashboards. They spend a lot of effort creating a bunch of graphs and put a lot of people in charge of staring at them. As if that’s going to help anyone. The main advantage of dashboards is that they are colorful and full of lines, boxes, and labels. Those properties are always an easy sell to decision-makers like CTOs and heads of departments. When a software vendor comes to a meeting with decision-makers with the authority to write checks, they know that there is no sale without “pretty colors”. It does not matter what that software does, but how it looks. That’s why every software company focuses on dashboards.

Think about it. What is a dashboard good for? Are we going to look at graphs until a bar reaches a red line indicating that a critical threshold is reached? If that’s the case, why not create an alert that will trigger under the same conditions and stop wasting time staring at screens and waiting until something happens. Instead, we can be doing something more useful (like staring Netflix).

Dashboards with graphs#

Is our “panic criteria” more complex than what can be expressed through alerts? I do think that it is more complex. However, that complexity cannot be reflected through pre-defined graphs. Sure, unexpected things happen, and we need to dig through data. However, the word “unexpected” defies what dashboards provide. They are all about the expected outcomes. Otherwise, how are we going to define a graph without knowing what to expect? “It can be anything” cannot be translated to a graph. Dashboards with graphs are our ways to assume what might go wrong and put those assumptions on a screen or, more often than not, on a lot of screens. However, unexpected can only be explored by querying metrics and going deeper and deeper until we find the cause of an issue. That’s investigative work that does not translate well to dashboards. We use Prometheus queries for that.

And yet, here I am dedicating a chapter to dashboards.

Conclusion#

I do admit that dashboards are not (fully) useless. They are useful, sometimes. What I truly wanted to convey is that their usefulness is exaggerated and that we might require different construction and use dashboards differently than what many are used to.

But, I’m jumping ahead of myself. We’ll discuss the details of the dashboards a bit later. For now, we need to create a cluster that will allow us to experiment and take this conversation to a more practical level. Let’s see that in the next lesson.