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Platform
Platform overviewThe operating model, end to end ArchitectureTopology, boundaries and blast radius Workflow orchestrationScripts, AI goals and approvals in one DAG GitOps configurationReviewable, promotable platform intent Governance and AAADefault-deny, caller-scoped decisions AI and MCPApproved models, tools, context and limits Knowledge and contextThe policies and guardrails you bind to a step Runtime and executionDocker and Kubernetes placement Evidence and monitoringDurable proof attached to the run
Use cases
All use casesTen workflows shown as governed runs Production incidentDiagnose and roll back behind an approval gate Release preparationScope, gates, notes and change request Hotfix to productionOne trail from complaint to emergency change Security scan triageFindings to scoped, tracked fixes
Why NopsAI
Integrations
Security
Resources
All resourcesDefinitions, comparisons and evaluation checklists AI agent governanceBoundaries that survive production MCP governanceFour decisions before a tool is available MCP securityControls when a server can reach production Self-hosted platformsThe evaluation checklist a security review uses
Pricing

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NopsAI wiki

Everything the platform does, grounded in the code that implements it.

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Task-based entry points into the product wiki.

I am new hereWhat the product is and how a run actually executes.I want to install itRun a local stack and finish first-install setup.I am writing a pipelineOne capability per page, on a manifest that grows as you read.Something is brokenSymptom to likely cause, with the page that explains the fix.

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Getting startedThe path from an empty machine to a green run: install the stack, finish setup, learn the topology, then build and trigger a first pipeline.12 pages - Product PipelinesEvery pipeline capability, introduced one page at a time on a single manifest that grows from one script step into a full release pipeline.14 pages - Automation platform AutomationHow runs start: manually, from a Git event, on a schedule, from an external system, or from a parent pipeline.6 pages - Automation platform PlatformInstalling, configuring, and owning the platform: deployment shapes, runners, networking, storage, GitOps authority, teams, access, and credentials.22 pages - Platform engineering OperationsRunning the platform day to day: runs, logs, metrics, evaluation, dashboards, notifications, updates, hardening, and triage.12 pages - Operations APIThe REST surface: what authenticates against it, how routes are organised, and the complete endpoint list.23 pages - Platform engineering ReferenceComplete indexes, interface contracts, vocabulary, and confirmed limits, for looking something up once you know the concept.7 pages - Product

7 sections - 96 pages - 279 documented fields - 88 examples - 203 implementation references