Monitor GitHub check suites in Databox
Keep check suite transitions visible so changes in repository validation are easier to spot.
Trigger
Check Suite Status / Conclusion Changed
Triggers when a GitHub check suite changes its status or conclusion for a given ref. Monitors all check suites associated with a git reference (branch, tag, or commit SHA) for changes to status (queued, in_progress, completed, etc.) and conclusion (success, failure, neutral, cancelled, skipped, timed_out, action_required, startup_failure, stale). Optionally filters by GitHub App ID.
Action
Push Data to Dataset (V1)
Tool to push data points to a Databox dataset using the v1 API. Use when you need to ingest data records into a specific dataset by providing the dataset ID and an array of records matching the dataset schema.
Why this helps
Check results are spread across refs and runs, which makes it harder to notice recurring validation issues.
- Capture check suite status and conclusion changes.
- Review validation outcomes for a monitored ref.
- Reduce repeated manual checks across GitHub.
Setup
Build it in a few focused steps.
- 1Connect GitHub and Databox once in the Notis portal.
- 2Create an automation and tell Notis to add each check suite's ref, status, conclusion, and available timestamps to a Databox dataset.
- 3Pick the Check Suite Status / Conclusion Changed trigger for the ref to monitor.
- 4Choose where run reports go, then test with one real check suite transition.
Questions about this workflow
What does this monitor?
It monitors check suites associated with a configured branch, tag, or commit SHA for status or conclusion changes.
Does it track a single check run?
No. The check suite event covers suites associated with a ref. A separate event monitors an individual check run.
Can Databox identify a failure trend?
It can summarize ingested statuses and conclusions if those values are stored and you define the reporting calculation.
When this happens · Trigger
Do this · Action
Supported Triggers and Actions
Notis builds workflows that link GitHub to Databox. A trigger fires from one place; an action lands in another.
GitHub triggers
Databox actions
Recurring trigger
Notis starts this workflow on a schedule, such as daily, weekly, or during business hours.
Create Dataset
Tool to create a new dataset in Databox data source. Use when you need to initialize a dataset with a title, data source ID, and primary keys for unique record identification.
Webhook trigger
Notis starts this workflow when an external tool or custom backend sends an HTTP request.
Create Data Source
Tool to create a new data source in Databox. Use when you need to create a logical container for datasets within a Databox account. Requires accountId, title, and timezone parameters.
New Workflow Artifact Created
Triggers when a new workflow artifact is created in a GitHub repository. Monitors for newly created GitHub Actions workflow artifacts. Optionally filters by artifact name to restrict monitoring to specific artifacts.
Delete Dataset
Tool to delete a dataset by ID in Databox. Use when you need to permanently remove a dataset. This operation is irreversible.
Branch Changed
Triggers when a GitHub branch changes. Monitors a specific branch for: - New commits pushed (head commit SHA changes) - Protection status toggled (branch becomes protected or unprotected) - Protection settings changed, including: required status checks and their enforcement level, admin enforcement, required pull request reviews (dismiss stale reviews, code owner reviews, approving review count, last push approval), required linear history, force push allowance, deletion allowance, conversation resolution, branch locking, and fork syncing.
Delete Data Source
Tool to delete a data source by ID in Databox. Use when you need to permanently remove a data source. This operation is irreversible and will delete all associated datasets.
New Branch Created
Triggers when a new branch is created in a GitHub repository. Detects newly created branches. Deleted branches do not fire events.
Get Dataset Ingestion Status
Tool to check the status of a specific data ingestion for a dataset. Use when you need to verify whether a data ingestion was successful by providing the dataset ID and ingestion ID returned from the initial POST request.
Check Run Status / Conclusion Changed
Triggers when a specific GitHub check run changes its status or conclusion. Monitors a single check run for changes to: status (queued, in_progress, completed, etc.), conclusion (success, failure, neutral, cancelled, skipped, timed_out, action_required), started_at, and completed_at.
List Accounts
Tool to retrieve all Databox accounts accessible to the authenticated user. Use to identify account IDs required for subsequent API operations like data source creation.
Check Suite Status / Conclusion Changed
Triggers when a GitHub check suite changes its status or conclusion for a given ref. Monitors all check suites associated with a git reference (branch, tag, or commit SHA) for changes to status (queued, in_progress, completed, etc.) and conclusion (success, failure, neutral, cancelled, skipped, timed_out, action_required, startup_failure, stale). Optionally filters by GitHub App ID.
Push Data to Dataset (V1)
Tool to push data points to a Databox dataset using the v1 API. Use when you need to ingest data records into a specific dataset by providing the dataset ID and an array of records matching the dataset schema.
New Code Scanning Alert Created
Triggers when a new code scanning alert is created in a repository. Fires an event for each newly created code scanning alert detected in the configured repository. Alerts can be filtered by Git reference, scanning tool, state, and severity. The payload includes the alert number, rule details, tool information, state, severity, and the location of the most recent instance.
Connect any two apps with Notis in the middle.
GitHub and Databox, or any other combination from 1,000+ integrations.
When this happens · Trigger
Do this · Action
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