In the past, I have discussed sonification as a mean of representing monitoring data. Aside from some silly and toy examples, sonifications can be used for serious applications. In many monitoring cases, the presence of some phenomena is more important than the details about it. In such situations, simple sonification is a perfect way to alert users about the occurrence of such phenomena. For example, Geiger counter alerts users of the radioactive decay, without providing any further details.
Our recent work on Retroscope and RQL allows us to bring sonification to the same “phenomena-awareness” plane for distributed systems. With RQL we can search for interesting conditions happening globally in the system, and we can use sounds to alert the engineers when certain predicates occur in the global state. Of course, for such system to be useful, it needs to be real-time, as the recency of events is the most important attribute of this type of sonification. For instance, users of a Geiger counter are not interested in hearing ticks for decay events happening a minute ago, as it rather defeats the purpose of the counter. Similar requirements apply to the “phenomena-awareness” tools in the distributed systems domain, as engineers need to know what happens in the system instantaneously.
RQL can easily allow inspecting past states, however it lacks when it comes to the current state inspection. What we need is a streaming query that can continuously receive individual logs from Retroscope log-servers, and perform the search as soon as sufficient data become available to form a consistent cut. Of course, streaming queries will still be lagging behind the current time, however we can make this lag small enough to be virtually unobservable by a person.
With streaming queries we can not only receive the cuts meeting some search criteria in near real time, but we can also sonify the mere fact such cuts have been found. If we look at the previous example of ZooKeeper staleness, we can run sonified streaming queries to have the system alert us when the data staleness reaches some threshold, such as two or more versions stale. In the audio clip below, we have used MIDI to sonify the stream of staleness events occurring in a ZooKeeper cluster. Multiple queries were sonified to produce different sounds for different staleness of ZooKeeper data.
We can hear periods of silence when the staleness is below the threshold of 2 values, however we can also observe some variations in cluster performance. For instance, it is very easy to identify when the cluster was experiencing more problems than normal. It is also easy to hear it recovering from the spike in staleness soon after.