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April 23, 2026Open Access

Operational Memory Architecture for Kubernetes: Preserving Causal Context Across the Evidence Horizon

Key Points

The aim is to preserve the causal diagnostic context in Kubernetes clusters before it is lost due to event retention limits.
Developed the Operational Memory Architecture (OMA) as a collector and memory store.
Implemented three causal patterns for different error scenarios in configuration management.
Conducted validation tests on Minikube and AKS with concurrent stress evaluation.
Demonstrated effective preservation of causal context for up to 90 seconds after termination across scenarios.
Achieved successful operational memory storage, reducing information loss during troubleshooting.
Supported by a statistical analysis across 30 runs to validate the framework's performance.

Abstract

The Operational Memory Architecture (OMA) is an open-source framework for preserving causal diagnostic context in Kubernetes clusters before it is destroyed by the platform's native event retention mechanisms. OMA introduces the evidence horizon — a boundary (~90 seconds) after which LastTerminationState data is permanently overwritten — and addresses it through three causal patterns (P001: OOMKill chain, P002: ConfigMap env var misconfiguration, P003: ConfigMap volume mount propagation) implemented as a Go-based collector, SQLite operational memory store, and canonical query interface. Validated on Minikube and AKS 1.32.10 with 30-run statistical analysis and concurrent stress evaluation. Full implementation at https://github.com/opscart/k8s-causal-memory

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