More on dashboards for maintenance developers

Yesterday I wrote about providing tools to visualize & manage the internal workings of applications for maintenance developers. That note was long on advocacy and sort on detail. This note somewhere between those two.

We are all familiar with run-time debuggers. We can get our job done with gdb [1], but for day in and day out work a visual debugger is a must have. A debugger is a point-in-time dashboard of the execution of the programming language used to implement the application. It is not a dashboard of the application, it does not directly represent the application's data or processing models. Nor does it provide a history of where the application was or a prediction of where it will be heading too next. Nevertheless, it is a useful analogous image of the application dashboard to keep in your mind.

If, for example, your application relies on the observer pattern [2] then you will need to visualize & manage the actors (observed), their dependents (observers), and the messages. The effort to implement this dashboard can be significant, which is the exact opposite of implementing the pattern itself. The pattern is often implemented as a list of callbacks. This implementation is so insignificant that your high performing developers probably choose not to use a framework at all, but to re-implement for each use. And there is the root of the trouble ahead for the maintenance developers, there is no one place to watch this running application. Callbacks and messages are being created and dispatched all over the place.

Suppose there had been a reusable implementation. The management of the listeners was done in a single place. The dispatching of messages to the listeners was done in a single place. Each reuse required that the developer explain the purpose, configuration, and expectations of this reuse. For example, "Status of the nightly recalculations of base prices: the messages are life cycle events; messages are ticketed and numbered for correlation; the listeners can be local or remote; the listeners are contacted asynchronously; no receipt acknowledgement is wanted, but when given will be logged; expect a dozen messages over a 2 hour period in every 24 hour period to be sent to a few hundred listeners." When this pattern is visualized on the dashboard not only is the context clear, but timelines of planned to actual and switches to toggle synchronicity will automatically be included. And what if you could dynamically toggle receipt acknowledgement? How many of your application's ailments are the result of lost messages sent to remote listeners?

The rise of DevOps has brought with it both tools and new (renewed?) appreciation for visualizing processes and their artifacts. Lets keep on pushing these ever deeper into the application itself.

[1] gdb,
[2] Observer pattern,