Artifact Lifecycle
This document defines the artifact lifecycle within the Oryvin ecosystem.
Artifacts are one of the key handoff mechanisms between workflow execution and operational consumption. They allow automation outputs to be packaged, described, delivered, stored, retrieved, and used in a traceable way.
The artifact lifecycle connects Orchestrator, DropBoxMini, and target systems through a predictable sequence of states and actions.
Purpose
The artifact lifecycle exists to support several goals:
- standardize how operational outputs move through the platform
- provide traceable state changes for artifacts
- separate artifact production from delivery and consumption
- support reliable retrieval and reuse
- contribute to operational evidence and auditability
This lifecycle turns artifacts into governed operational objects rather than ad hoc files.
What an artifact is
An artifact is a packaged output produced by a workflow or related process.
Typical artifact types include:
- patches
- builds
- documentation bundles
- configuration payloads
An artifact is not only the payload. It also includes metadata, usually through a manifest, that explains what the payload is and how it should be interpreted.
Lifecycle overview
A typical artifact lifecycle is:
build or generate
↓
package
↓
describe with manifest
↓
publish
↓
ingest
↓
store
↓
retrieve
↓
consume
↓
retain as evidence
This sequence provides a consistent path from automation output to operational use.
Lifecycle stages
1. Generate
An artifact begins when a workflow or process produces an output.
Examples include:
- Orchestrator produces a patch bundle
- a build pipeline produces a deployable package
- a documentation workflow produces a publication bundle
This stage creates the raw payload that will later become an artifact.
2. Package
The produced output is packaged into a transportable structure.
Typical packaging includes:
- payload files
- manifest metadata
- optional supporting metadata
This stage prepares the output for transfer.
3. Describe
The artifact is described with a canonical manifest.
The manifest identifies:
- artifact identifier
- owning system
- artifact type
- version
- producer
- timestamp
- included files
This stage makes artifact meaning explicit and machine-readable.
4. Publish
The producer publishes the artifact to the delivery boundary.
In the current Oryvin model, this is typically:
Orchestrator
↓
DropBoxMini
Publication is an authenticated action and should return an explicit success or failure result.
5. Ingest
DropBoxMini receives the artifact and validates it.
Typical ingest activities include:
- authentication check
- manifest validation
- payload presence validation
- artifact type validation
- version conflict checks
- storage determination
An artifact is not considered stored until it passes ingest.
6. Store
After successful ingest, DropBoxMini stores the artifact in a predictable path structure.
Example:
dropbox/weic/patches/0358/
Storage is a distinct lifecycle stage because it marks the point where the artifact becomes a managed platform object rather than a transient upload.
7. Retrieve
A target system or operator retrieves the artifact by explicit path or logical selector.
Examples include:
- specific version retrieval
- latest artifact retrieval
- system-and-type-based retrieval
Retrieval is the point where stored artifacts become available for operational use.
8. Consume
The retrieved artifact is consumed by a target system or workflow.
Examples include:
- applying a patch
- deploying a build
- importing a document bundle
- applying a configuration package
Consumption is not performed by DropBoxMini. It is performed by the downstream system that uses the artifact.
9. Retain
Artifacts and their metadata remain as part of the operational record.
Retention supports:
- traceability
- troubleshooting
- rollback support
- compliance and evidence use
Retention is important because artifact history is part of the broader Oryvin evidence chain.
Lifecycle states
The initial lifecycle can be represented as explicit states.
| State | Meaning |
|---|---|
| generated | payload exists but is not yet packaged |
| packaged | payload has been bundled for transfer |
| described | manifest has been created |
| published | producer has attempted delivery |
| ingested | DropBoxMini has accepted the artifact |
| stored | artifact is persisted and retrievable |
| retrieved | artifact has been requested by a consumer |
| consumed | artifact has been used by a downstream system |
| retained | artifact remains part of the operational record |
Not every system must store these states explicitly at first, but the conceptual model should remain clear.
Failure conditions
Artifacts may fail at several points in the lifecycle.
Typical failure conditions include:
- generation failure
- packaging failure
- invalid manifest
- authentication failure during publish
- storage conflict
- retrieval failure
- downstream consumption failure
These failures should be recorded explicitly rather than treated as ambiguous file-transfer problems.
Artifact identifiers and versions
An artifact requires both stable identification and version context.
Typical examples include:
artifact_idsystemtypeversion
These values help determine:
- storage location
- retrieval behavior
- lifecycle tracking
- evidence relationships
Version identity should remain explicit throughout the lifecycle.
Evidence implications
Artifact lifecycle events are part of the operational evidence chain.
Evidence may include:
- manifest files
- upload responses
- storage paths
- retrieval logs
- downstream consumption records
This allows the platform to show not only that a file existed, but how it moved through the system and what happened to it.
Relationship to producers and consumers
The artifact lifecycle separates the roles of participating systems.
Producers
Typical producers include:
- Orchestrator
- build automation
- documentation workflows
Producers generate, package, describe, and publish artifacts.
Delivery boundary
DropBoxMini ingests, stores, and exposes artifacts.
Consumers
Typical consumers include:
- infrastructure deployment targets
- operational systems
- administrators or operators
- future automated downstream workflows
Consumers retrieve and use artifacts.
This separation keeps system boundaries clean.
Design principles
The artifact lifecycle follows several principles.
Explicit states
Artifact handling should be understandable as a sequence of governed states.
Metadata matters
Artifacts should carry enough metadata to be understood without guesswork.
Separation of concerns
Production, delivery, storage, and consumption are distinct responsibilities.
Traceability
Artifact movement should contribute to the operational evidence chain.
Predictable retrieval
Stored artifacts should be discoverable through stable paths and selectors.
Relationship to the Oryvin plan
Artifacts are one of the key operational handoff mechanisms in Oryvin.
workflow output
↓
artifact packaging and description
↓
DropBoxMini delivery and storage
↓
target retrieval and use
↓
evidence and operational record
This lifecycle is one of the mechanisms that turns documentation-driven automation into real operational change.