Weirdness of Experiment

My job in ops has always been to keep things running. I never considered myself “working in software”, but have recently begun embracing the fact that I do. What I accomplish as an operations and infrastructure engineer is part of the system, it isn’t dislocated from its composition.

Relatedly, I have been considering the nature of the experiment in Chaos Engineering. How continuous verification is becoming a crucial part of the complex systems we build because there really is no end. Developing a software system isn’t just about writing it, it’s also every bit as much about running it. Unless there is some kind of evil catastrophic end-game planned from a volcano island hideout, most of us want to keep them running.

I’m big on experimental music. You probably know what I mean when I say that, but you might not because genres, in general, are horrible overgeneralizations. Similarly, after the composer John Cage had written his “silent piece” in 1952 (see also Living 4’33”), he seemed to have a struggle with the concept of calling the music composed by him and others he admired experimental.

In science, we often think of an experiment as a method to (dis)prove a hypothesis. We perform experiments to answer a question or assertion, often during the process of reaching an end goal. To Cage, this implied that calling something an “experiment” meant it was not complete, not finished. That there is a final state determined by products of the experimentation, and he thought that his (and others’) music was complete when performed. There was no “final state” that was decided as a result of an experiment either succeeding or failing, if it was itself called experimental.

Cage revised this view, however. He began embracing the term and actually ended up preferring it. The reason for this is the way he evolved to think about the context of sound. At the beginning of the decade, he experienced an anechoic chamber (an “echoless” room) and the non-presence of total silence, because he could hear both high and low sounds — explained to him by the engineer as his nervous system in operation and blood circulating, respectively. Whether or not that is physiologically probable, he had the now famous revelation that it is impossible to remove sound completely. 4’33” and an entire philosophy about the nature of sound and silence in music was not far behind.

To him then, the moniker experimental came to mean that which is undiscovered, because even if a piece of music requires certain sounds, environmental sounds are impossible to predict. This experimental music isn’t about the search for failure or success, but an experience of discovery, where questions become more interesting than answers. When applied to composition, each performance of a musical work is always new and different due to its context and sonic environment. Indeed, it is impossible to know ahead of time any structure of the interpenetrating sounds both intentional and not, themselves independent and unique (whether or not they are consonant). It is in fact in a total state of chaos, each and every time.

When complex systems run, they do so at the hand of indeterminacy and randomness. There certainly is a “steady state”, but it is continuously in need of verification. Just like Cage observing that no performance of a musical work is a repeat, the nature (structure and form) of distributed systems we operate cannot in truth be predicted with any kind of regularity.

So while it is useful to be very specific in defining and running our Chaos experiments, the nature of what we’re doing is more about asking questions and making discoveries, not testing for answers we already think we know or think we can guess. The “breaking things in production” mantra implies we are interested in failure when what we’re really interested in is what was determined and what questions arose, good or bad.

Appendix

Here are a couple of PDFs taken from Cage’s writing that highlight his viewpoint on the subject of “experimental music” as a title of what he did.

  • Experimental Music: Doctrine (1955) ::: This article, there titled Experimental Music, first appeared in The Score and I. M. A. Magazine, London, issue of June 1955. The inclusion of a dialogue between an uncompromising teacher and an unenlightened student, and the addition of the word ”doctrine” to the original title, are references to the Huang-Po Doctrine of Universal Mind.
  • Experimental Music (1957) ::: The following statement was given as an address to the convention of the Music Teachers National Association in Chicago in the winter of 1957. It was printed in the brochure accompanying George Avakian’s recording of my twenty-five-year retrospective concert at Town Hall, New York, in 1958.

The photo above is the album cover from a release by Craque called Meat Hacker.

Musical Intuition meet Technology and Chaos

Today I read through the InfoQ eMag on Chaos Engineering, and was struck by John Allspaw’s (@allspaw) contribution because it reminded me of something I jotted down on a sticky at my desk a few days ago:

Intuition is valid because it is learned like jazz changes.

I’m pretty stubborn and refuse to accept that music is merely a hobby of mine. When people ask me if electronic music or singing is my “hobby”, I am wincing inside. So a question often on my mind is: how does the intuition I have when performing and composing music connect with the work I do as a technologist?

Some musicological background might help. One concept in learning how to improvise (jazz or otherwise) is that you have developed an intuition built around internalizing the materials and form of the piece (or genre) – like scales, chord changes, or rhythm structures. This is different from the more lizard-brainy concept of instinct. Think about a blues progression, the foundation of music you hear every day, everywhere. You know intuitively the chord progression and timing is “right”, even so much that anomalies and departures come across as emotionally significant. The rest is pop history.

But you, homo sapiens, do not have this chord sequence pre-programed in your DNA, it isn’t something that is instinctual. By the same token, great technology leaders develop good intuition (expertise over hundreds of interviews) when hiring engineers but never rely on instinct (oh I just have a good “gut feeling”). The best DBAs have an intuitive understanding of their platform (you want to do X, but did you think of Y+Z?), but there’s nothing instinctual about it.

It is not a stretch, then, to recognize that intuition in improvised music can be directly compared to how Allspaw writes about the “mental map” that engineers develop. They each have their own subjective view on relevant (but overlapping) parts of the system and are challenged when relating each substrate to theirs. For instance, a phenomenon known as “fundamental common-ground breakdown” (Woods & Klein: Common Ground and Coordination in Joint Activity) happens when what I describe as intuitions (accumulated individual learnings about the system) are assumed knowledge among participants, good or bad. Part of the game is learning how to harmonize these separate threads of experience, avoiding costly coordination surprise and re-synchronization… and trust me, I have been in plenty of rehearsals and narrowly saved performances that fit this description!

The important point here is that a system becomes more complex as it grows dimensions, shrinking the capacity of any one person to comprehend the whole thing. Therefore we rely on shared and discovered knowledge to fully grok these fascinating systems. Take any ensemble of musicians: as it grows in membership, individuals gradually lose the ability to contain its myriad relationships in their mental map, so coordination and integration become a matter of listening and rehearsal experience (both modes of communication). Oh and it characterizes the music, too. Building intuition about how to play a part in an opera is much different than in a free improv vocal trio. Orchestrating ten thousand linux containers in a cloud provider doesn’t compare to managing two rows of server racks at the datacenter downtown.

Technologists grapple with the task of building and sharing intuitions about a system because understanding an entire system contributes to what we know about making it more resilient. Communication is key in either musical or engineering teams, collaboration on understanding the whole is no exception. Our mental maps should be adaptable to constant updates, and practices like Chaos Engineering that make discoveries in complex system behavior are supported by this kind of cross-pollination and proliferation of our combined understanding.

A quote from Allspaw’s article highlights it well:

Maybe the process of designing a chaos experiment is just as valuable as the actual performance of the experiment.

– John Allspaw, Recalibrating Mental Models through Design of Chaos Experiments

The use of the term “performance” is apt. We’re familiar with this concept: practice makes perfect. Taken further, the experience of practice is necessary such that the result is merely an extension of practice. It takes meticulous work to understand a piece of music to the level of having an intuition about how it operates, and the same goes for building experimentation that challenges what you think you know about complex software. The results of the “performance” can be enhanced by a focus on understanding the system’s design and steady state (i.e. nominal condition), what we would call the language of the musical work. It is as if the performance of the event naturally evolves from learnings gained preparing for it.

Imagine you are a jazz musician, you have gone through years of studying scales and changes and charts and recordings of a particular artist, and have built a capability for understanding how the language of their music works. One evening at a local club, your dreams are fulfilled, you’re in the audience and invited up for a set with them. You intuitively know how this person plays their music, as it has been a guide for your own. But when you’re jamming together, they do something indeterminately that informs your intuition in a way you would have never discovered yourself. Not only has the process of designing your inevitable collaboration been valuable to understand what you thought you needed to know to play like your biggest influence, but it also served as the basis for learning something new and unexpected.

Whether it is free improvisation or interpreting a through-composed piece of music (and everything in between), there is a certain amount of experience and training informing the performance. Eventually, when we’ve practiced enough, the music itself steps out of the way and intuition takes over. I think this is where my musical performance connection with technology starts: once you understand the fundamentals of the system, let the presentation of the system get out of the way, and you’re in a better place to evolve your mental map and gain further intuition through disciplines like Chaos Engineering.