Inventory & discovery
Provider adapters, Kubernetes discovery, and on-prem agents feed one tenant-scoped inventory with ownership, region, tags, and operational state.
• One tenant-scoped platform: inventory, topology, provisioning, delivery, policy, audit, and AI.
• Live SDK adapters for AWS, Azure, GCP plus on-prem agents, one graph.
• Policy, approvals, and audit attached to every change before execution.
• Demo mode with zero credentials; connect real accounts when ready.
Devopsify unifies inventory, topology, provisioning, delivery, policy, audit, and AI-assisted operations in one tenant-scoped, policy-aware surface. Connect real accounts with live SDK adapters, or evaluate the complete workflow instantly with labeled demo data.
Devopsify is a tenant-scoped infrastructure control plane that unifies multi-cloud inventory, topology, governed provisioning, delivery operations, audit, and AI-assisted investigation under one declarative graph. The platform connects provider adapters, Kubernetes discovery, and on-prem agents into a single inventory graph where policy, approvals, and audit are enforced before any change executes, with guarded AI assisting investigation, never as the authorization boundary.
Provider adapters, Kubernetes discovery, and on-prem agents feed one inventory sync. Adapters support real SDK connections for cloud providers plus an on-prem agent protocol; demo surfaces stay labeled and need no credentials.
| Layer | What it does | Governance |
|---|---|---|
| Inventory | Tenant-scoped graph | Ownership + topology |
| Provisioning | Plan → policy → approve → apply | Policy + approvals |
| AI Operations | Investigate & propose | Human review |
Consoles are single-cloud and siloed. Devopsify is a tenant-scoped control plane that unifies inventory, topology, policy, approvals, and audit across all clouds and on-prem in one graph.
Yes. Labeled demo data lets you evaluate inventory, topology, and AI workflows without credentials.
No. AI proposes; humans approve. Execution is platform-only, policy-gated, and audited.
Four layers compose the control plane: observe, attach context, govern, and assist, each leaving a record an operator can replay.
Provider adapters, Kubernetes discovery, and on-prem agents feed one tenant-scoped inventory with ownership, region, tags, and operational state.
Infrastructure relationships are modeled so teams get a shared, dependency-aware view of services, boundaries, and the environments that surround a change.
OpenTofu plans, policy evaluation, required approvals, and deployment waves carry change from plan to apply with the decision trail retained.
AI-assisted investigation and recommendations stay within explicit action boundaries, subject to policy and human review, and never become the authorization boundary.
Adapters and agents collect infrastructure context into a tenant-scoped inventory.
Cost, drift, policy, deployment, and operational signals assemble around the requested change.
Required reviewers evaluate the plan while AI proposals stay within explicit action boundaries.
Execution, approvals, policy results, and actor identity are retained for review.
Start on labeled demo data with zero cloud credentials, then connect the environments your team actually operates.
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