Deployment Intelligence: A Cognitive Architecture for Intelligent Deployment Decisions

Deployment Intelligence proposes a conceptual reference architecture for intelligent deployment decision support: a cognitive decision layer that complements CI/CD by bringing production context, operational memory, evidence-based reasoning, confidence estimation, explainable recommendations, human oversight, and continuous learning into deployment decisions. The paper introduces the SMART Framework (Sense → Model → Assess → Recommend → Tune), the Production Context Model, Operational Memory, Evidence-Based Reasoning, a Confidence Engine, and a layered Deployment Intelligence Reference Architecture. It also presents an implementation-oriented architecture, end-to-end deployment walkthrough, evaluation framework, failure modes, architectural tradeoffs, and future directions. Version 1.0 presents the conceptual architecture and does not claim a production implementation or empirical validation.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-17
DOI
https://doi.org/10.5281/zenodo.21976359
Primary Topic
AI-based Problem Solving and Planning
Type
article
Field-Weighted Citation Impact
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article

Deployment Intelligence: A Cognitive Architecture for Intelligent Deployment Decisions

Anirban Bhaduri
Zenodo (CERN European Organization for Nuclear Research)
AI-based Problem Solving and Planning
article

Deployment Intelligence: A Cognitive Architecture for Intelligent Deployment Decisions

Anirban Bhaduri
article en

Abstract

Deployment Intelligence proposes a conceptual reference architecture for intelligent deployment decision support: a cognitive decision layer that complements CI/CD by bringing production context, operational memory, evidence-based reasoning, confidence estimation, explainable recommendations, human oversight, and continuous learning into deployment decisions. The paper introduces the SMART Framework (Sense → Model → Assess → Recommend → Tune), the Production Context Model, Operational Memory, Evidence-Based Reasoning, a Confidence Engine, and a layered Deployment Intelligence Reference Architecture. It also presents an implementation-oriented architecture, end-to-end deployment walkthrough, evaluation framework, failure modes, architectural tradeoffs, and future directions. Version 1.0 presents the conceptual architecture and does not claim a production implementation or empirical validation.

Zenodo (CERN European Organization for Nuclear Research)
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AI-based Problem Solving and Planning
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