idp-adp-architect

Designs Internal Developer Platform and Agentic Developer Portal architectures across five planes.

Updated Jul 16, 2026
One-click install
npx skills add https://github.com/Cloud-Byte-Consulting/plugins --skill idp-adp-architect-cloud-byte-consulting
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: idp-adp-architect
Source: https://github.com/Cloud-Byte-Consulting/plugins/tree/main/platform-assessment/skills/idp-adp-architect
Command: npx skills add https://github.com/Cloud-Byte-Consulting/plugins --skill idp-adp-architect-cloud-byte-consulting

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Platform teams struggle to turn maturity assessment findings into a concrete, sequenced architecture for an Internal Developer Platform, and face new design questions when AI coding agents must safely consume the same platform capabilities as humans. ## Core Features & Use Cases - Five-plane reference architecture: Maps developer control, integration & delivery, resource, security, and observability planes to per-cloud tool slots (AWS, Azure, GCP) with portable invariants like Backstage, Score, Terraform/OpenTofu, and OPA. - ADP design for AI agents: Defines deterministic, probabilistic, and hybrid execution paths plus the seven agent infrastructure components (identity, context, capability, execution, evaluation, security, observability). - Specialized variants: Covers Kubernetes fleet lifecycle management, AI/ML sixth-plane extension with dual orchestrators, and sovereign/exit-by-design architectures for GDPR, NIS2, and DORA scope. - Use Case: After running a platform maturity discovery, produce an architecture brief with a filled tool-mapping table, capability register with reuse/buy/assemble/build decisions, golden paths, and a phased build sequence. ## Quick Start Use the idp-adp-architect skill to design our target platform architecture and agent readiness plan from the discovery evidence catalog.

Frequently Asked Questions about idp-adp-architect

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I design an Internal Developer Platform architecture?

Organize the platform around five planes: developer control, integration and delivery, resource, security, and observability. Map category slots to tools per cloud first, then pick vendors, keeping portable invariants like Backstage, Score, Terraform/OpenTofu, a graph-based orchestrator, and OPA.

What is an Agentic Developer Portal and when should I build one?

An Agentic Developer Portal is the interaction surface letting AI coding agents consume the same governed platform capabilities as humans, with identity, sandboxing, evaluation, and audit. Build it only after the underlying platform is mature, since agents amplify weaknesses in a shaky platform.

How do I choose between building and buying platform capabilities?

Make an explicit reuse, buy, assemble, or build decision per capability, defaulting to the least custom option that meets the requirement. Record the decision in a capability register with owner, interface, SLOs, unit cost, and an exit plan.

Can AI agents trigger infrastructure changes directly?

No. Any LLM- or agent-triggered infrastructure or environment change must route through a trusted CLI or the orchestrator API with RBAC and audit, never direct console or raw cloud API mutation. This keeps every agent action governed and logged as a Git pull request.

What changes for platform architecture under GDPR, NIS2, or DORA?

Treat jurisdiction as an architecture input: data residency does not equal data sovereignty. Self-host management stack components like Gitea, Keycloak, Vault, and Prometheus, use GitOps with OpenTofu as the exit mechanism, and test reconstruction on a different provider from Git alone.

When should a platform add a dedicated AI/ML plane?

Add the sixth Data and Model Management plane when workloads include training, serving, notebooks, or GPUs. It introduces a feature store, model registry with model cards, a dual-orchestrator pattern with an ML workflow orchestrator, model scanning gates, and drift observability.