This article was originally posted in 2020 on the OpenSignals website, which is now defunct.
Humanism: Progress and Agency
Humanism is a philosophical stance at the heart of what Humainary aims to bring to service management operations. It runs counter to the misguided trend of wanton and wasteful extensive data collection so heavily touted by those focused on selling a service rather than solving a problem.
Humanism’s core principles are progress and the value of the human agency, whereas current observability techniques and technologies are anything but this. While cloud infrastructure has scaled to meet ever-increasing levels of change and complexity, observability has stayed with cave wall painting – logging, and tracing.
Scaling the SLM Model
Bringing a human back to the table where s/he can add value and act intelligently requires rethinking current observability technologies, emphasizing simplicity and significance while offering new higher-order forms of sensing, selection, and sapience.
Over the last decade, with the arrival of the cloud, there has been an incredible scaling of computing resource capacities and communication networks, but not so much in the ability of humans to comprehend and reason about the state of a system or service or the significance of a situation.
When it comes to scaling human cognition, less is more. Scaling agency and attention to this new world of micronization and interconnectedness requires shrinking the surface area and shifting to sensibility and selectivity.
Synthesizing and Semantics
While there might never be a one size fits all kind of model for observability, a suitable model and representation of reality should be able to frame a system (space) or situation (temporal) at various levels of scaling (abstraction and compression) without too much in the way of communication overhead or cognitive effort. This is where Humainary shines compared to other observability technologies such as distributed tracing, metrics, or logging.
While the Humainary model is simple and small, it is astonishingly powerful in compressing complexity, synthesizing semantics, amplifying analysis, and detecting dynamics – the same intellectual qualities we look to each other in leading the progress of society and guiding decision-making.
A Small Suffice Sign(al) Language
Much of the conceptualism underlying Humainary is based on the early foundations of human (and animal) communication and control – behavioral signaling and state inference. Humainary’s Serventis brings a much-needed humane approach to how systems of services communicate, converse, and collectively coordinate cooperation.
Signals are the ultimate in the clear and concise communication of an operation or outcome. Signals and the traces of such signs left within an environment inform others of significance. They augment what is communicated over different channels, mediums, or within request or response payloads. Signals are used to influence the behavior of clients. There is no need to inspect or interpret a message – ambiguity is absent in signaling.
Steering Systems with Signals
Signals steer behavior in others who sense such signals and signs, starting with mapping a signal to a possible status value. In human society, signal mapping is generally universal. If another swiftly raises a clenched fist, most others within an environment will make a similar assessment of what is being signified and, over time with repeated signaling, accurately and similarly judge the state.
Optimally there is little need for contextualization of the signal – no additional data capture is required. Contextualization is conversational. In Humainary, the set of signals has been carefully chosen based on the most basic constructs, controls, and codes found in various existing service-to-service communication channels, contracts, and clients.
The Subjectivity of Service Quality
In human society, the inferred state of another is always subjective. The subjectivity encompasses the sensitivity of the signal receiver, the sequencing of signals received, and the scoring algorithm employed in assessing the state over time and within the scope of a contextual space or changing situation.
From the small and simple model of Humainary comes complexity, but of a kind that is highly vigorous and versatile in capturing the diverse degrees of resilience and fault tolerance mechanisms that invariably exist within an enterprise-scale system of services.
Humainary can be used with relatively little effort to extract actual state dynamics and, in turn, predict future state trajectories at both service and system levels.
This is the way. This is the future!