k6 Cloud to MongoDB Integration

How Datrise loads k6 Cloud into MongoDB

Datrise syncs k6 Cloud's test runs, thresholds, checks, metrics, virtual users, and response times into MongoDB as a collection per source entity. Flexible or custom fields land in native nested documents, and timestamps such as created, updated, and status changes are typed as BSON Date.

Sync is incremental: Datrise uses upserts by stable id with updateOne(upsert) on the source primary key, so re-runs update only what changed. Optional sharding on the entity id for large collections. Mongo has no fixed schema, so Datrise keeps field types consistent across documents to avoid mixed-type query surprises.

Ideal for document-oriented apps that want CRM data in their existing Mongo store.

Endpoints

k6 Cloud: Load testing runs and performance thresholds.

MongoDB: Document database for flexible schemas.

How k6 Cloud entities map to MongoDB

k6 Cloud entity	MongoDB object	Notes
test runs	`k6_cloud_test_runs`	id PK · custom fields → native nested documents
thresholds	`k6_cloud_thresholds`	id PK · linked to k6_cloud_test_runs
checks	`k6_cloud_checks`	id PK · linked to k6_cloud_test_runs
metrics	`k6_cloud_metrics`	id PK · linked to k6_cloud_test_runs

FAQ

How does Datrise handle k6 Cloud's custom fields in MongoDB?

Flexible values are stored as native nested documents, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native MongoDB types.

How does the k6 Cloud to MongoDB sync stay up to date?

It runs incrementally — Datrise uses upserts by stable id with updateOne(upsert) on the source primary key.

Related pipelines

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