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Sync History

Sync History shows what happened when DFS read from a connector. Use it to confirm that data arrived, diagnose partial runs, and collect evidence before downstream workflows use the data.

Open:

Data Integration > Sync History

Connector Detail may also show recent sync logs and throughput.

What to check first

For a new connector, confirm:

  1. a sync run exists;
  2. status is OK or the problem is understood;
  3. read count is greater than zero;
  4. written count matches expected accepted rows or points;
  5. failed count is reviewed;
  6. the run time matches the expected schedule;
  7. data quality is acceptable for the use case.

Sync fields

FieldUse
TimeWhen the sync started or completed.
ConnectorWhich source produced the run.
StatusOK, partial, or failed.
ReadRecords or points read from the source.
WrittenRecords or points accepted by DFS.
FailedRecords or points rejected or failed during processing.
StatisticsAdditional run details when available.

Status interpretation

StatusMeaningNext action
OKThe run completed successfully.Check written count and data quality.
PartialSome data was accepted and some failed.Review failed rows, mappings, and validation rules.
FailedThe run did not complete.Check connector status, source access, and error details.

Read, written, and failed counts

Use count patterns to diagnose issues.

PatternLikely meaning
Read is zeroSource query returned no data, topic was empty, file was empty, or source path is wrong.
Read is high, written is zeroMapping, validation, target identity, or table write failed.
Read is high, failed is highSource data shape or quality is not acceptable.
Written drops suddenlySource changed, mapping changed, quota changed, or upstream system is stale.
Failed count grows over timeSource schema or value format may be drifting.

Investigate a partial or failed run

  1. Open the connector detail page.
  2. Check recent errors.
  3. Check whether the connector is connected, warning, error, disabled, or syncing.
  4. Review mappings changed since the last good run.
  5. Check data quality trend.
  6. Open the Review Queue if rejected rows are being collected there.
  7. Ask the source owner whether source schema, units, file format, topic payload, or credentials changed.

Evidence to keep

When a sync issue affects a downstream workflow, record:

  • connector name;
  • sync time;
  • status;
  • read, written, and failed counts;
  • source owner;
  • suspected cause;
  • action taken;
  • whether the next run recovered.

Next step

Use Data Quality to decide whether the connector output is ready for downstream use.