Reference flow

Follow the data. Inspect the decisions.

Explore how Flower® handles a flow from Amazon S3 to Azure Blob: validate compressed CSV files, transform them into Parquet and apply recovery or quarantine policies. Select a scenario to see the decisions along the way.

Discuss your flow ↗

01Explore the recovery policy

Explore the recovery policyorders-001.csv.gz
  1. 01SourceAmazon S3CSV · gzip
  2. 02Validate, filter, aggregate and transformFlowerCSV → Parquet
  3. 03DestinationAzure BlobParquet
Delivered

The sample passes validation and is converted to Parquet. The illustration follows the data through processing, destination checks and completed delivery.

02What to verify in your environment

What to verify in your environment
ScenarioAcceptance check
Normal deliveryCheck that the Parquet output is readable and matches the agreed schema and expected records after transformation.
Temporary outageTemporarily disconnect the destination to explore policy-driven retries, backoff, recovery and actionable alerts.
Invalid fileSubmit a file with a record that violates a validation rule. Check that the whole source file is quarantined, with its failure reason, and that invalid data is not delivered downstream.
Recovered within the retry policyRestore the destination within the retry window and verify the completed output. Check source retention or cleanup against its separately configured policy.

03From illustration to a production flow

For the S3-to-Azure scenario, coordinate endpoint permissions, decompression, CSV schema, validation rules, Parquet mapping and quarantine. Combine destination checks with record counts, schema validation and business totals to document the quality and completion of the transformed delivery.

Discuss your data path

Turn the requirement into a reliable production flow.

Describe the source, destination, volume, constraints, or failure mode. You will speak directly with the team that builds Flower.

Talk to the Flower team