Understanding Provenance in Clockspring

Provenance is Clockspring’s built-in record of what happened to your data as it moved through a flow. It tracks where a FlowFile came from, how it was changed, and where it went next. Provenance is essential for troubleshooting, auditing, and validating that a workflow is behaving as expected.

This article explains how provenance works, why it exists, and how to use it effectively without creating unnecessary overhead.

Why Provenance Exists

Every FlowFile has two parts:

• Attributes — metadata

• Content — the actual payload

As processors route, modify, or create FlowFiles, Clockspring records those actions as provenance events. This gives you a historical trail showing:

• When a FlowFile entered the system

• Which processors touched it

• What modifications were made

• Whether it was forked, merged, or cloned

• Where it ended up

This traceability helps you answer questions like:

• “Why didn’t this record reach the database?”

• “Which processor modified this field?”

• “Did we receive this file more than once?”

How Provenance Works Internally

Clockspring writes provenance events to a structured journal on disk. These events include:

• The action (receive, route, modify, fork, join, drop, etc.)

• The FlowFile identity at that moment

• A reference to the content if it changed

• A timestamp and processor name

Think of this as a minimal but accurate history: enough to understand what happened without logging full copies of every FlowFile at every step.

What creates a provenance event?

Most processors generate at least one event. Examples:

• Receive — data enters the system

• Fork/Clone — a FlowFile is duplicated

• Modify Attributes — metadata changed

• Modify Content — payload changed

• Send/Route — FlowFile is transferred

• Drop — FlowFile is intentionally ended

These map directly to how your flow behaves.

Provenance and Content Claims

Clockspring uses a content repository that stores FlowFile content in blocks. Provenance events point to these blocks rather than copying data repeatedly. This keeps storage usage low while still providing traceability.

When content changes:

• A new content claim is created

• Provenance records the relationship between old and new

This is why provenance is safe to use even on large files.

How Long Provenance Is Kept

Provenance data is kept until it hits the configured disk limit or retention window. Older events roll off automatically.

Production systems usually:

• Use shorter retention (to reduce disk usage)

• Keep enough history to troubleshoot failures

• Rely on external logs or metrics for long-term tracking

Development systems usually keep more history because visibility matters more than storage cost.

Performance Impact

Provenance is designed to be lightweight, but it is not free. Every event written to disk takes some I/O.

Key points:

• High-volume flows generate a lot of events

• Very small FlowFiles magnify provenance event count

• Debug processors create even more events

This doesn’t mean you should disable provenance. It means you should design flows with awareness of the event load.

Later KBs in this series will cover:

• Debug vs production configurations

• How to reduce unnecessary provenance noise

• How to tune write-ahead logs and repositories

When To Use Provenance

Use provenance when you need:

• Root-cause analysis

• Validation of new flows

• Tracking lineage

• Identifying duplicate or missing records

Don’t rely on provenance for:

• Real-time monitoring

• Operational metrics

• High-frequency debugging in production

• Long-term historical storage

Provenance is a forensic and traceability tool, not a metrics pipeline.

Practical Guidance

In Development

• Keep longer retention

• Use provenance to verify flow behavior

• Inspect events frequently to understand routing

In Production

• Reduce retention to something practical

• Avoid unnecessary debug processors

• Keep FlowFile counts reasonable

• Use logs and dashboards for monitoring instead of over-reading provenance

These patterns keep performance steady without losing the ability to troubleshoot when it matters.

Key Takeaways

• Provenance records how every FlowFile moves through the system

• It tracks attributes, content changes, and routing

• Stored efficiently using references to content claims

• Essential for troubleshooting and validation

• Should be tuned differently for dev and production

• High throughput flows benefit from controlled provenance retention