Unfortunately, many of the solutions promoted in the Observability space, such as distributed tracing, metrics, and logging, have not offered a suitable mental model in any form whatsoever. The level of situation awareness is still sorely lacking in most teams, who appear to be permanently stalled at ground zero and overtly preoccupied with data and details.
Category: SRE
Observability – The Two Hemispheres
Two distinct hemispheres seem to form within the application monitoring and observability space - one dominated by measurement, data collection, and decomposition, the other by meaning, system dynamics, and (re)construction of the whole.
Scaling Observability for IT Ops
The underlying observability model is the primary reason for distributed tracing, metrics, and event logging failing to deliver much-needed capabilities and benefits to systems engineering teams. There is no natural or inherent way to transform and scale such observability data collection analysis to generate signals and inferring states.
Humanizing Observability and Controllability
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, now and in the future.
Observability – A Multitude of Memories
There are at least two distinct paths to the future of observability. One path that would continue increasing the volume of collected data in its attempt to reconstruct reality in high-definition on a single plane with little consideration for effectiveness or efficiencies. Another would focus on seeing the big picture in near-real-time from the perspective of human or artificial agents.
AIOps – A Postmodern Observability Model
We propose a model which can better serve site engineering reliability and service operations by being foundational to developing situational awareness capabilities and system resilience capacities, particularly adaptability and experimentation, as in dynamic configuration and chaos engineering.
AIOps – The Observer
Observability is purposefully seeing a system in terms of operations and outcomes. In control theory, this is sometimes simplified to monitoring inputs and outputs, with the comparative prediction of the output from input, possibly factoring in history.
Measurement and Control 2022
Since the very beginning of the hype of Observability, we have contended that the link with Controllability must be maintained for there ever to be a return on investment (ROI) that matches the extravagant claims from vendors pushing a message of more-is-better.