DatriseAI-first ETL

Instatus to Azure Data Lake Storage Integration

AI-first ETL from Instatus into Azure Data Lake Storage. Governed entities, incremental sync, typed landing tables.

How Datrise loads Instatus into Azure Data Lake Storage

Datrise syncs Instatus's incidents, components, incident updates, subscribers, status page views, and uptime history into Azure Data Lake Storage as partitioned Parquet in ADLS Gen2 per source entity. Flexible or custom fields land in nested struct/map fields in Parquet, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes new date partitions to the container and compacts on a schedule, so re-runs update only what changed. Hive-style partitioning by load date, readable by Synapse and Databricks. ADLS hierarchical namespace makes folder layout matter, so Datrise keeps a predictable entity/date path your Azure engines mount directly.

Ideal for Azure lakehouse storage shared across Synapse and Databricks.

Endpoints

Instatus: Fast status pages with incident timelines and subscribers.

Azure Data Lake Storage: ADLS Gen2 object storage for analytics workloads.

How Instatus entities map to Azure Data Lake Storage

Instatus entityAzure Data Lake Storage objectNotes
incidentsinstatus_incidentsid PK · custom fields → nested struct/map fields in Parquet
componentsinstatus_componentsid PK · linked to instatus_incidents
incident updatesinstatus_incident_updatesid PK · linked to instatus_incidents
subscribersinstatus_subscribersid PK · linked to instatus_incidents

FAQ

How does Datrise handle Instatus's custom fields in Azure Data Lake Storage?

Flexible values are stored as nested struct/map fields in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Azure Data Lake Storage types.

How does the Instatus to Azure Data Lake Storage sync stay up to date?

It runs incrementally — Datrise uses writes new date partitions to the container and compacts on a schedule.

Related pipelines

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