The concept is pretty expansive when you think about the kinds of data that can be shown. WebGL Globe combines data that has several dimensions of information encoded and visualized:
- Node Location - latitude and longitude
- Node connections - showing that two nodes are connected in some way (shown as an arc when you click on a country in the World of Oil visualization).
- Connection intensity - this one can have multiple dimensions depending on how creative you get. For example:
- the line color itself can indicate some sort of status (red/green/yellow/orange). It's even possible that you could show percentages of the arc length as certain colors to indicate distribution of the status (i.e. 10% is bad while 90% is good might mean a line that is mostly green with a segment of length 10% that is red).
- the thickness of the arc can be another dimension, indicating something like volume
- the maximum altitude of the arc can be another, indicating sample size
All this is neat, but what good does it do anyone. Well, if you've watched my Analyzing TCP Application Performance video, you know that monitoring of response time is the most important part of any infrastructure monitoring. If you're doing application response time monitoring, you should have data for each transaction showing how each transaction performed. That's a huge amount of data (big data anyone?).
Visualizing that data requires a few steps of summarization and grouping. First of all, every transaction's metrics should be retained individually so that you can dive into the details if needed. Second, you can start grouping by user then by summarizing by time buckets (1 minute or 5 minute). Another level of grouping that can be done is to group by network location. This can legitimately be done because most users at a particular location are going to share a very high percentage of the network path that gets them to the services they are consuming.
Let me rephrase: You should have data that describes sources, destinations, and the performance between them. Sound familiar? What I'm envisioning is taking this data and plotting it out using WebGL Globe. Each network location and each service hosting location is a node (hm, could cloud services actually be represented as clouds?!?). They'd be connected with arcs. Thickness of the arcs could represent the number of transactions between those two nodes. Height of the arc could represent the recent negative variability in performance or a way to highlight the selected arc. Color of the arc could show a measure of the deviance in performance.
Click on a node and you'd see the arcs from all the user locations consuming services from that site (if any) and the arcs to all the service hosting locations consumed by that site (if any) pop up in altitude (normally they'd be displayed at sea level or hidden based on a GUI setting). This is similar to the action you see in the Global Oil visualization when you click on a country (you see the countries connected to it).
From there, if you saw that all the arcs were showing problems, you would know (from problem domain isolation) that there is a problem common to all users at that site. You could click on the node again and get into performance stats for the infrastructure at that location (from a tool like LogicMonitor). Following the colors should get you to the root of the problem pretty quickly.
Alternatively, if you saw a problem in only one of the arcs (or a small selection) follow problem domain isolation tactics and click on the arc having the problem. That should dive you into the infrastructure connecting those two nodes so you can find the problem.
Nodes themselves can have problems that don't evidence themselves outside the node. If that's the case, you should be going into the node to look at why there are performance issues. You'd know to go to there because the node icon itself would be showing some color indicator that there's a problem.
