I know the answer to that can be "you should know your product" but I'm not sure that answer is enough.
I know the answer to that can be "you should know your product" but I'm not sure that answer is enough.
Ok First, there are those, who care enough about the data, and for them dashboards are just not enough. Not enough data, not exactly what you are looking for and there's the element of ambiguity behind the large red bar on the chart.
Second, there are those who don't care enough and are honest enough to admit it, they would rather talk to someone who understood the data to get a sense of what's going on every once in a while.
Third, are those in the gray area in between these 2. They don't / can't care enough about the data but they also won't/can't admit/accept it. Dashboards, to them give an illusion of control and being in the know. And from my experience there are more of this type than the other two. So clearly Dashboards are a 'thing'!
I monitor my stuff based on scripts that I own and write myself Excel, Python and shell scripts. What I need is a reliable notification mechanism that's easy peasy to setup and move around. I could imagine a dashboard of this historical data that I have hand-picked but I don't think I will ever get there.
So, yeah I'll build this dashboard and keep people happy while I keep tabs based on what I can trust.
In our office we have giant screens all around (because screens are dirt cheap now) each team puts the metrics they care about on them. It's really not unusual for us to look at it, and be like "whoa, that metric is kind of spiking, let's take a look".
If you're in phase 1 of development, or even the first half of phase 2... you don't need one. If you're in phase 3 (maintence) you need one.
Looker is probably my favorite currently but it depends on your needs really.
I guess in a nutshell I feel like these dashboard products, while well meaning and often very well crafted are just throwing things at your eye sockets. Showing data because you have data is not a solution in of itself.
I think the problem is dashboards on their own are pretty low value - ie $40/y for Castor. But that doesn't create a very interesting or particularly sustainable business.
Example: MRR+ Today, MRR+/Day over last 7 days, MRR+/Day over last 30 days, etc. It's still not perfect, but it adds at least an element of that "at a glance" context.
One of my favorite ways to do this (that most charting packages struggle with) is to use an area full for last year, a solid line for this year, and a dotted line for the future based on current trajectory.
You can compare to multiple periods using stacked areas (particularly when you can assume previous periods had growth).
Dashboards are about visualizing how your application works over time, not whether your application is failing. You should know as soon as possible when something has gone wrong and not be waiting until you come in to work in the morning to figure it out. For us, a key stat trending up or down by more than 10% was sent to PagerDuty for someone to investigate. This didn't happen often, but when it did, it was frequently due to something that we were glad we investigated promptly (e.g. abuse/fraud, misbehaving release, etc). It was really rare that we just got that much more or less usage organically.
How is it hard to show a comparison of current state vs. average state? That's literally about as simple as it gets, and something I would expect as basic functionality out of any dashboard product I was using.
Also, gauges are almost always a terrible visual indicator. Even car dashboards are starting to understand this. Fuel gauges are good, speedometers are not.
The gas gauge however has a permanent meaning. Empty is bad. The Tachometer is also useful if you are driving a manual since you want to keep from redlining and keep from stalling.
On almost every business dashboard I have seen, gauges are more like speedometers.
People love to put revenue in a gauge. More is better and they usually have a goal that they want to hit. But what happens if they max out the gauge? Do they stop sales? Or do they adjust the gauge to go higher (thus making it even more meaningless and difficult to read).
I am just getting started with Graphite and wondering how to do this across all of the timeout metrics at the same time on the same graph. (It would probably be an all-or-nothing scenario but there is a chance only a portion of the system is affected by something...)
We're trying to tackle this entire experience by building a collaborative data tool that's easy enough for everyone to actually use. It's a good fit for technical leaders that are running non-tech teams or teams that simply don't have the time to spend on connecting all the data sources: Intercom, Github, JIRA, etc.