Software Diagnostics and Observability Institute

There are many spaces where we do our observations in software systems. The explosion of spaces began with the Abstract Space, where we depict running threads as braids.

When we talk about spaces, we also consider suitable space metrics (not to be mistaken with observability metrics below) by which we can compare the proximity of space objects.

In diagnostics, we have the so-called Diagnostic Spaces with their signals, symptoms, syndromes, and signs. Different analysis patterns can serve the role of space metrics in pattern-oriented software forensics, diagnostics, and prognostics.

Traces, logs, and metrics are pillars of observability that are all erected from Memory Space and, therefore, can be considered Adjoint Spaces. Memory spaces are also diverse: including manifold, orbifold, hyperphysical, physical, virtual, kernel, user, managed, and secondary, and have their own large-scale structures.

Traces and logs have their own individual Trace and Log Spaces (including Message Spaces, Interspaces, and Tensor Spaces. These also include network traces and logs from memory debuggers. (Observability) Metrics Spaces are a subtype of such spaces.

Traces and logs are also examples of the so-called software narratives with their own Software Narrative Spaces, including higher-level narratives, and space-like narratology. We can also consider software diagnostic spaces as general graphs of software narratives.

If we are concerned with the hardware-software interface, then we can consider Hardware Spaces via hardware narratology.

Presentation Spaces visualize other spaces, and visualization languages help with their meaning.
We analyze all these spaces to identify patterns with the help of analysis patterns, which are organized in their own Analysis Patterns Space (memory and traces).

Defect Mechanism Spaces help in root cause analysis.

When we delve into software workings, we are concerned with Software Internal Spaces.
Additionally, we have various Namespaces, Code Spaces (similar to Declarative Trace Spaces), State Spaces, and Data Spaces.

Artificial Chemistry Spaces based on the idea of spaces of chemistry enhance the artificial chemistry approach to trace and log analysis.

For many years, the ideas of various physical and mathematical spaces have inspired diverse memory and log analysis patterns, as well as some concepts in software diagnostics and software data analysis.
We would also like to mention that the book that introduces Information Space is featured on the cover of this article.

And finally, the new wave of AI suggests Token Spaces.