This post introduces the reasoning, thinking, and concepts behind a technology we call Signals, which we believe has the potential to have a profound impact on the design and development of software, the performance engineering of systems, and the management of distributed interconnected applications and services.
Category: Signals
Observability – The Significant Parts
Most current observability technologies don’t fair well as a source of behavioral signals or inferred states. They are not designed to reconstruct behavior that would allow the level of inspection we would need to translate from measurement to signal and, in turn, the state effectively. They are designed with data collection and reporting in mind of the event, not the signal or state.
The Data Fog of Observability
The overemphasis on data instead of signals and states has created a great fog. This data fog leads to many organizations losing their way and overindulging in data exploration instead of exploiting acquired knowledge and understanding. This has come about with the community still somewhat unconcerned with a steering process such as monitoring or cybernetics.
Observability in Perspective
There are many perspectives one could take in considering the observability and monitoring of software services and systems of services, but here below are a few perspectives, stacked in layers, that would be included.
A Story of Observability
Once upon a time, there was a period in the world where humans watched over applications and services by proxy via dashboards housed on multiple screens hoisted in front of them – a typical mission control center. The interaction between humans and machines was relatively static and straightforward, like the environment and systems enclosed.
The Evolution of Substrates
With the latest update to the Substrates API, the metamorphosis to a general-purpose event-driven data flow library interface supporting the capture, collection, communication, conversion, and compression of perceptual data through a network of circuits and conduits has begun.
Simplicity and Significance in Observability
As computing and complexity scaled up, the models and methods should have reduced and simplified the communication and control surface area between man and machine. Instead, monitoring (passive) and management (reactive) solutions have lazily reflected the complexity's nature at a level devoid of simplicity and significance but instead polluted with noise.