DAEDALUS

Dynamic Architecture & Engineering for Deployment Automation.
Multi-cloud architecture engineering, HLD/LLD generation, governance and identity-aware platform orchestration.

Architecture as Code HLD → LLD Governance by Design
Explore DAEDALUS View Repository 
      DAEDALUS
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 Declarative HLD Models
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 Inventory / CMDB / Requirements
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 Architecture Engine
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 Validated LLD Generation
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 Governance & Identity Checks
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 Deployment Artifacts
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 Platform Ready

What is DAEDALUS?

DAEDALUS is a multi-cloud architecture engineering and platform orchestration framework designed to transform declarative High-Level Design models, inventory data and technical requirements into validated Low-Level Designs, deployment artifacts, diagrams, documentation and operational templates.

Problem

  • Architecture designs are often inconsistent, manually maintained and difficult to validate.
  • HLD and LLD artifacts are frequently mixed, duplicated or disconnected from implementation.
  • Inventory, identity, security and governance constraints are often handled outside the design lifecycle.
  • Infrastructure automation usually starts too late, without a validated architecture model.

DAEDALUS Approach

  • Declarative HLD models as the source of architectural intent.
  • Automated HLD to LLD transformation.
  • Architecture validation before deployment or promotion.
  • Generation of deployment artifacts, documentation, diagrams and governance checks.

Architecture Overview

DAEDALUS separates architectural intent from technical implementation. The HLD defines what the platform should be. The LLD defines how that platform is implemented for a specific cloud, technology stack or infrastructure environment.

ARCHITECTURE ENGINEERING MODEL

HLD Model Inventory Requirements LLD Generation Governance Deployment Artifacts

Figure 1 — DAEDALUS Architecture Engineering Model

Architecture Layers

HLD Layer

Defines architectural intent, platform topology, high availability, multi-region or multi-AZ strategy, security segmentation, identity requirements and resiliency patterns.

Inventory & Requirements Layer

Consumes CMDB data, platform inventory, technical requirements, security constraints and non-functional requirements.

LLD Generation Layer

Generates platform-specific implementation models, configuration templates, infrastructure artifacts and operational views.

Governance & Validation Layer

Validates architecture consistency, compliance, Zero Trust constraints, identity integration and deployment readiness.

Core Capabilities

HLD/LLD Automation

Transforms declarative architecture models into validated Low-Level Designs for Azure, OpenStack, AWS, GCP and hybrid infrastructures.

Platform Orchestration

Generates deployment artifacts such as Terraform, Bicep, Ansible inventories, configuration templates, documentation and diagrams.

Governance as Code

Applies architecture validation, security baselines, compliance checks, identity-aware rules and promotion gates before deployment.

Roadmap

DAEDALUS evolves from architecture automation into a multi-cloud architecture engineering framework integrating infrastructure, identity, governance and operations.

v0.1 — Declarative HLD models

Initial architecture models for OpenStack, Azure, AWS, GCP and hybrid environments.

v0.2 — Automated HLD to LLD transformation

Generation of consistent Low-Level Designs from HLD models, inventory data and requirements.

v0.3 — Platform-specific factories

Autonomous platform factories for OpenStack, Azure, AWS and GCP with dedicated generators, pipelines, documentation and validation logic.

v0.4 — Governance and compliance validation

Policy-driven validation for security, architecture consistency, compliance and deployment readiness.

v0.5 — Identity-aware platform integration

Integration with identity governance ecosystems such as AEGIS Identity Fabric, including RBAC, federation, Zero Trust and privileged access validation.

v0.6 — Architecture-driven deployment pipelines

Separate HLD and LLD pipelines for validation, generation, planning, deployment, testing and publishing.

AEGIS Ecosystem

DAEDALUS is part of the AEGIS ecosystem, connecting platform architecture, identity governance, Zero Trust validation and autonomous operations.

DAEDALUS

Architecture engineering, HLD/LLD automation and platform orchestration.

AEGIS

Identity Fabric, Zero Trust governance and identity control plane for hybrid infrastructure.

ARGOS

Autonomous operations, observability-driven remediation and controlled operational response.

Repository

Source Code

DAEDALUS repository: github.com/bcollantes/DAEDALUS

Experimental multi-cloud architecture engineering framework focused on HLD/LLD automation, platform orchestration, governance validation and identity-aware infrastructure design.