1.1 What Orbnetes Is 1.2 Who It Is For 1.3 What Problem It Solves 1.4 Core Platform Principles (control, traceability, speed)
1.5.1 Install Docker Image 1.5.2 Install Host App
2.1 First 30 Minutes Setup 2.2 Create Project 2.3 Register First Agent 2.4 Add Release Source / Storage 2.5 Create First Blueprint 2.6 Launch First Run and First Release 2.7 Quick Start Completion Checklist
3.1 Control Plane vs Agent Execution Plane 3.2 Project Scope Model 3.3 Data Flow: Source -> Release -> Pipeline -> Logs/Artifacts 3.4 Runtime Configuration Layers (global / project / environment) 3.5 Pipeline Execution Semantics 3.6 Release Governance Path 3.7 Rollback Architecture (Policy-driven) 3.8 Security and Trust Boundaries 3.9 State and Persistence Model 3.10 Scalability Model 3.11 Failure Modes and Recovery Patterns 3.12 Why This Architecture Works in Practice
5.1 Project Concept and Boundaries 5.2 Project Settings 5.3 Allowed Agents 5.4 Project Members 5.5 Project-level Notifications and Defaults
6.1 Agent Lifecycle (create, register, online/offline) 6.2 Install Instructions (Linux / macOS / Windows) 6.3 Tags and Job Routing 6.4 Agent Update Mechanism 6.5 Agent Archives and Binary Management 6.6 Agent Status, Metrics, and Troubleshooting
7.1 Global Configuration Overview 7.2 Notifications Settings 7.3 OAuth Login Settings (GitHub/GitLab) 7.4 SMTP/Email Notes 7.5 Operational Security Defaults
8.1 Project Secrets 8.2 Project Variables 8.3 Environment Secrets 8.4 Environment Variables 8.5 Global Secrets & Variables 8.6 Priority Resolution Rules 8.7 Best Practices for Sensitive Data
9.1 Release Sources (GitHub, GitLab, URL, Storage) 9.2 Tag and Asset Selection Model 9.3 Internal Release Storage 9.4 File Upload and Webhook Upload 9.5 Checksum / Integrity Considerations
10.1 Blueprint Fundamentals 10.2 YAML Structure 10.3 Jobs, Steps, Needs, If, Allow Failure 10.4 Inputs, Variables, Secrets 10.5 Templates, Actions, Functions 10.6 Syntax Validation 10.7 Authoring Best Practices
11.1 Standalone Runs vs Pipelines 11.2 Launch Flows 11.3 Pipeline Graph (DAG) 11.4 Live Job Pages 11.5 Rerun Strategies (all / failed) 11.6 Artifacts and Outputs
12.1 Release Creation Flow 12.2 Environments and Deployment Modes 12.3 Source + Blueprint Binding 12.4 Launch Inputs in Release Context 12.5 Release Status Lifecycle 12.6 Release Detail Page Anatomy
13.1 Approval Model 13.2 Approver Selection Rules 13.3 Pending Approval Behavior 13.4 Approve / Comment / Cancel 13.5 Notification Behavior in Approval Flow
14.1 Rollback Policy Overview 14.2 Check Target (all pipeline vs specific job) 14.3 Delay and Trigger Rules 14.4 Modes (last successful / selected release / selected version) 14.5 Rollback Traceability and Linked Releases 14.6 Anti-loop and Safety Recommendations
15.1 Live Console Features 15.2 Step Timeline and Search 15.3 Log Download Scopes (job / pipeline) 15.4 Status and Duration Interpretation 15.5 Common Failure Patterns
16.1 User Model and Profile 16.2 Project Permissions 16.3 Global Permissions 16.4 API Keys 16.5 Access Approval for New OAuth Users 16.6 2FA Enforcement
17.1 User-level Notification Preferences 17.2 Project-level Notification Policies 17.3 Event Types (release, run, approval, comments, cancel/rerun) 17.4 Delivery Channels and Operational Notes
18.1 API Authentication 18.2 Project-Scoped API Usage 18.3 Blueprints API 18.4 Releases API 18.5 Pipelines and Job Runs API 18.6 Integration Patterns (portal, bots, external orchestrators)
19.1 Audit Log Model 19.2 Action Types and Filters 19.3 Soft Delete Behavior 19.4 Operational Traceability Patterns
20.1 Standard App Deployment 20.2 Multi-Environment Rollout 20.3 Approval-Gated Production Release 20.4 Rollback Execution Playbook 20.5 Incident Triage with Graph + Live Logs
21.1 Agent Not Claiming Jobs 21.2 Release Source / Asset Not Loading 21.3 Secrets/Variables Not Applied 21.4 Approval Flow Not Starting Deploy 21.5 Pipeline Rerun Behavior 21.6 Common UI/Validation Issues
22.1 Terms and Definitions 22.2 Status Vocabulary (release, deployment, pipeline, job)
23.1 Example Blueprints 23.2 Example API Requests/Responses 23.3 Recommended Naming Conventions 23.4 Versioning and Changelog Guidance

4.5 Interpreting Status Widgets

Orbnetes deployment and release orchestration documentation for operators and platform teams.

Status widgets are designed for rapid triage. A good dashboard is only useful if operators interpret status consistently.

Recommended status interpretation model:

  • Waiting
    Includes pending approval and queued states.
    Meaning: not executing yet.
    Action: check approvals, runner availability, or tag routing.
  • Running
    Job/pipeline is active.
    Meaning: execution in progress.
    Action: monitor live graph/logs; validate progress and heartbeat freshness.
  • Succeeded
    Completed successfully.
    Meaning: expected outcome reached.
    Action: confirm environment/version state and proceed.
  • Failed
    Execution ended with error.
    Meaning: release risk exists.
    Action: inspect first failing step, validate blast radius, decide rerun/rollback.
  • Canceled
    Intentionally stopped or interrupted.
    Meaning: execution not completed by design.
    Action: verify reason (manual cancel, policy action, dependency path).

Widget reading best practices:

  • Always combine status with time context (ago + full timestamp).
  • Correlate release status and pipeline status; they may differ by phase.
  • Use dashboard as triage surface, then move to release/pipeline/job pages for root cause.

Recommended operator workflow from Dashboard

  1. Check Deployment Activity for failures or unusual spikes.
  2. Verify Current Versions by Environment for actual live impact.
  3. Confirm Agent Health for capacity/routing issues.
  4. Inspect Queue/Live Operations for execution bottlenecks.
  5. Drill down into graph + live logs for exact failure point.

This workflow keeps response fast, consistent, and auditable.