Synthetic test data: use cases
A complete project for every use of synthetic test data — pipeline testing, detection, load testing, database seeding — from an empty directory to working output.
Foundations, formats, realism, and delivery cover synthetic event and log data end to end — what it is, the shape it takes, how to make it realistic, and where it goes. A scenario puts them together into one complete project that solves a real job, from an empty directory to working output. This track covers the situations synthetic test data gets built for most often — proving a pipeline delivers data correctly, generating telemetry for SIEM and detection work, load-testing an API, seeding a database, tracking clickstream and IoT traffic, and firing scheduled alerts. Start with the end-to-end walkthrough below, then jump to whichever scenario matches your job.
Test data pipeline end to end
Generate a realistic event stream, deliver it the way production does, and confirm the backend actually received it.
SIEM test data: index Windows events in OpenSearch
Index Windows Security Event Log sessions into OpenSearch — for detection development, parser validation, and analyst training.
Test Sigma rules with synthetic attack telemetry
Generate benign and attack-shaped telemetry to test Sigma rules and ATT&CK-mapped detections.
Seed a database with realistic test data
Generate a shaped e-commerce dataset of purchases, refunds, and chargebacks as CSV, ready to load into a dev or staging database.
API load testing
Generate realistic load test data — a weighted mix of request payloads — and fire it at a REST API to benchmark throughput and find its breaking point.
Generate clickstream data for ClickHouse
Model user browsing sessions and bounces as clickstream data, and stream page views into ClickHouse for funnel analysis.
IoT test data
Generate simulated sensor readings with realistic drift and noise, streamed as NDJSON.
Alert simulation: scheduled Telegram alerts
Generate randomized-severity alerts on a cron schedule and deliver them to a Telegram chat through the Bot API, without waiting for a real incident.
Related
- The log and event formats field guide for the formats each scenario generates.
- Ready-made generators for common data sources in the Eventum Hub.
Output formatters: a shape per destination
Output formatters decide how the same event stream leaves each destination — one line per event, a single array, or a custom envelope — and which of the six to choose for a given target.
Test Data Pipeline End to End
Test data pipeline delivery end to end — generate a realistic event stream, deliver it the way production does, and confirm the backend actually received it.