DEVOPS
Dropbox Artifact Storage Cost Audit to BigQuery
Weekly, inventories the Dropbox artifacts folder, writes per-folder size and age metrics to a BigQuery table for trend analysis, and flags the top storage offenders in Slack.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule fires
- ActionInventory Dropbox artifacts treeDropbox
- LogicAggregate size and age per subfolder
- ActionAppend snapshot rows to BigQueryBigQuery
- LogicSelect top storage offenders
- OutputPost offender ranking to SlackSlack
What it does
This workflow takes a weekly inventory of your Dropbox build-artifacts area, computes size and age stats per subfolder, and appends a dated snapshot row to a BigQuery table. Over time that table becomes a cost-trend dataset you can chart. It also surfaces the heaviest folders so owners know where storage is piling up.
When to use it
Use it when you want visibility into artifact storage growth before it becomes a bill problem. Unlike a sweeper, this one never deletes — it measures, records history, and reports, so you can set retention policy from real data.
How it works
- 1A weekly schedule starts the audit.
- 2List the Dropbox artifacts tree, capturing path, size, and modified date for every file.
- 3Aggregate the files into per-subfolder totals and average age.
- 4Append the dated snapshot rows to a BigQuery metrics table.
- 5A filter selects the top storage offenders above a size threshold.
- 6Post the offender ranking and week-over-week delta to Slack.
Set it up
What you configure once, before turning it on.
- 1Connect DropboxFiles and folders.
- 2Connect BigQueryDatasets, queries, schemas.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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