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
10.7 Authoring Best Practices
Orbnetes deployment and release orchestration documentation for operators and platform teams.
Keep pipelines readable
- prefer short jobs with focused responsibility.
- split long shell scripts into multiple named steps.
Use explicit names
- meaningful
job.nameandstep.nameimprove graph/log readability. - avoid generic names like
runorscript.
Model dependencies clearly
- use
needsfor intended order. - avoid hidden sequencing assumptions inside commands.
Scope configuration correctly
- do not hardcode credentials in YAML.
- use secrets/variables/environment scopes consistently.
Design for recovery
- include backup and verification stages in deploy blueprints.
- make failure points obvious in step naming/output.
Keep tag strategy simple
- align job tags with real agent capabilities.
- avoid tag sprawl that causes routing confusion.
Test incrementally
- first minimal run,
- then add inputs/conditions,
- then add artifacts and advanced controls.
Version blueprint changes
- review in PR,
- record notable behavior changes in changelog/release notes,
- avoid unreviewed direct edits for critical production blueprints.
Blueprint quality checklist
Before marking a blueprint production-ready:
- Syntax validates cleanly.
- Critical path jobs are strict (no accidental allow-failure).
- Tags match available project agents.
- Secrets are referenced, not hardcoded.
- Inputs are typed and required where needed.
- First non-prod run succeeded end-to-end.
- Failure behavior is understandable from graph + logs.