Log deployment events into your data warehouse

When a deployment is tracked in Obviously AI, insert a record into Snowflake to maintain an accurate audit history of software releases.

Try:

See all Snowflake + Obviously AI integrations or talk to a human

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How Knit builds this workflow

The Agent researches both APIs and wires the trigger on one side to the action on the other — no pre-built connector required. Here is the vocabulary it has to work with.

Snowflake Explore Snowflake →

Triggers

New row inserted

Fires when a new row is added to a table in Snowflake.

Row updated

Fires when an existing row changes in Snowflake.

Query result ready

Fires when a scheduled query in Snowflake finishes running.

Actions

Run a query

Runs a SQL query against Snowflake and returns the result.

Insert or update a row

Writes a new or updated row to Snowflake.

Sync a table

Syncs a table in Snowflake with data from another source.

Obviously AI Explore Obviously AI →

Triggers

New issue captured

Fires when a new error or issue is captured in Obviously AI.

Issue status changed

Fires when an issue's status changes in Obviously AI.

Deployment tracked

Fires when a new deployment is tracked in Obviously AI.

Actions

Create issue

Creates or updates an issue in Obviously AI.

Assign issue

Assigns an issue in Obviously AI to a teammate.

Resolve issue

Resolves or mutes an issue in Obviously AI.

File a bug ticket when an error is logged in the database Whenever a new error row is inserted into Snowflake, automatically create a tracking issue in Obviously AI so engineering can investigate immediately. See details

Update database records when an issue is resolved As soon as an issue status changes to resolved in Obviously AI, update the corresponding row in Snowflake to reflect the resolution. See details

See all Snowflake + Obviously AI integrations → · Browse the full workflow library →

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FAQ

Common questions

Can Knit build “Log deployment events into your data warehouse” between Snowflake and Obviously AI?

Yes — describe it in the box above and Knit's Integrations Agent researches Snowflake and Obviously AI's public API docs (or your own uploaded docs) and builds a working workflow, whether or not either app already has a pre-built connector.

How long does it take to build?

Minutes to a first working version, not weeks — you test it against real data before it goes anywhere near production.

What's the most common Databases & Warehouses + Developer Tools automation?

Syncing commits, pull requests, and issue status from Obviously AI into Snowflake continuously, so engineering metrics can be reported alongside other business data.

Does this need webhook access configured in the dev tool?

The Agent works with whatever Obviously AI exposes over its own API or webhooks — no separate custom setup needed on your end.