Monitor Bluesky Keyword Posts with Apify + n8n Data Table

Monitor Bluesky keyword posts automatically with Apify + n8n Data Table deduping

This n8n workflow runs an Apify Bluesky monitoring Taskupserts results into an n8n Data Table so reruns don’t create duplicates.

What this workflow does

• Runs manually or hourly using n8n triggers (Schedule Trigger supported).
• Starts an Apify Actor Task for Bluesky monitoring and waits for the run to finish.
• Fetches the dataset results: if the run returns a default dataset ID, it retrieves up to 100 dataset items (configured via the Task’s per-run cap).
• Normalizes each dataset row into a consistent Bluesky post schema.
• Creates diagnostic records for malformed rows missing required identifiers (so bad data doesn’t silently fail).
• Upserts into the n8n Data Table using a stable deliveryKey so existing rows update instead of inserting duplicates.
• Outputs a run summary and throws an error when the Apify run status is not SUCCEEDED.

Use cases

• Social listening for specific Bluesky keywords, with a persistent history of observed posts.
• SaaS operations dashboards that need incremental updates without duplicate records across workflow reruns.
• Data pipelines where downstream systems rely on normalized fields like sourceId, sourceUrl, and observedAt.

Technical details

• Requires the community node package @apify/n8n-nodes-apify (version 0.6.10+).
• Integrates with Apify via an Apify API credential and your saved Bluesky monitoring Task ID.
• Uses n8n nodes including Apify, if, code, and data table (plus supporting nodes like Manual Trigger / Sticky Note).
• Writes to an n8n Data Table named monitor-deliveries with columns: deliveryKey, product, sourceId, sourceUrl, title, observedAt, runId, runStatus, datasetId, payloadJson.