Learn
A hands-on course on generating realistic synthetic event and log data — formats, realism techniques, delivery to your stack, and end-to-end scenarios.
Learn the formats your data uses, how to make it realistic, how to deliver it to your stack, and how to prove a pipeline works before touching production.
Foundations
Start here: what synthetic event and log data is, and why structure matters.
Synthetic data for event and log pipelines
What it is, how it differs from a flat Faker or Mockaroo dump, and where it fits.
Formats & schemas
Understand the shape of your data — Windows events, CEF, LEEF, syslog, NDJSON, OCSF, ECS, Apache/Nginx access logs, AWS CloudTrail, Suricata EVE JSON, Linux auditd — and generate a compliant sample of each.
Log & event formats
A field guide to the formats your pipeline speaks, and how to generate each.
Realism
Techniques that turn a flat stream into data that behaves like production.
Making synthetic data realistic
Timing, sessions, and value distributions that mimic production traffic.
Delivery
Stream synthetic data into the backend you actually use.
Stream to your stack
Deliver generated events to OpenSearch, Kafka, ClickHouse, HTTP, syslog collectors and more.
Scenarios
End-to-end projects that prove a use case from an empty directory to working output.
Synthetic test data: use cases
Complete projects — pipeline testing, detection, load testing, database seeding, clickstream — built end to end and runnable as shipped.