As engineering systems grow ever more complex, the engineering community's focus on simplistic measurement and reporting hinders achieving operational scalability by way of sensemaking and steering of such systems of systems.
Category: AIOps
Streamlining Observability Pipelines
The next generation of Observability technologies and tooling will most likely take two distinctly different trajectories from the ever-faltering middle ground that distributed tracing and event logging currently represent. The first trajectory, the high-value road, will introduce new techniques and models to address complex and coordinated system dynamics in a collective social context rebuilding a proper foundation geared to aiding both humans and 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 Double Cone Model
The Double Cone Model is a valuable conceptualization in thinking about more efficient and effective methods to handle data overload and generate far more actionable insight from a model much closer to how the human mind reasons about physical and social spaces.
AIOps – Visibility and Cognition
All points of experience within a topology offer some visibility, but the language (codes, syntax) and model (concepts) employed can differ greatly. This is problematic when the goal is to determine the intent and outcome of an interaction's operation(s).
AIOps – Why Service Cognition?
Today's data, such as logs, traces, and metrics, are too far removed to be the basis for a language and model that illuminates the dynamic nature of service interaction and system stability inference and state prediction formed across distributed agents.
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.
The Intelligence in AIOps
It could be argued that no one fully understands what AIOps pertains to now in its aspirational rise within the IT management industry and community. AIOps is a moving target and a term hijacked by Observability vendor marketing. It's hard to pin down.