Get Production-Like Test Data

in Just One Click

Sixpack covers the full test data lifecycle: synthetic test data generation, cross-environment data delivery, dataset buffering for instant access, leasing to prevent collisions, refresh workflows, and cleanup or deletion when data expires.

Sixpack uses team-owned generators. Teams choose the safest and fastest method for each system, including database inserts, internal or public APIs, event triggers, and UI automation.

Sixpack provides SDKs in multiple languages, reusable helper libraries, and example generators for common patterns. Teams can start quickly and still keep full flexibility in their native language and tooling.

In distributed architectures, schemas and business rules change often. Generators keep domain logic with the owning teams, so test data stays accurate without central bottlenecks or fragile platform-specific insert rules.

Sixpack is framework-agnostic. If UI automation is the right way to create data, you can reuse your existing web or mobile automation stack. We also provide examples based on Pumpo5.

Sixpack orchestrates generators, pre-generates and buffers datasets, exposes self-service UI and API access, manages retries and delivery, and supports multi-generator scenarios that create consistent cross-system datasets.

No. Sixpack is designed for synthetic test data and does not require production data analysis or production copies. Any optional production-derived statistics are controlled by your team and are not a platform requirement.

When a generator is deployed, it registers its available data types in Sixpack. The platform then updates the UI and REST API automatically per environment, so teams can request newly available data immediately.

Sixpack pre-generates datasets in the background using generator declarations and historical demand trends. When users request data, they usually get a ready dataset immediately from the buffer.

Test data is delivered through the Sixpack UI, REST API, and optional notifications (for example email or chat). Sixpack mainly shares references and metadata, while the actual dataset content remains in your target systems.

If a requested dataset is not pre-generated, Sixpack sends an ad hoc generation request to the relevant generator chain and delivers the dataset as soon as generation is completed.

Sixpack retries failed generation jobs based on configuration, tracks failures, and can trigger alerts. Teams can monitor generator health and fix issues without losing request context.

Sixpack uses dataset leasing. Once a dataset is assigned, it is not reused by other users or test runs until released or expired, which prevents test collisions and shared-state flakiness.

Typically no direct inbound access is needed. Connections are initiated from your infrastructure, and Sixpack handles references and orchestration metadata, not full environment content. Synthetic data also reduces data privacy and compliance risk.

Yes. Self-hosted deployment is available for teams that need it. Sixpack can run in Kubernetes and requires a SQL database.

Sixpack offers Free, Professional, and Enterprise plans. Free includes core platform access with monthly usage limits, Professional scales by team size and usage, and Enterprise covers custom support, SLA, and deployment requirements.

Sixpack is built by PumpITup, an engineering team focused on test automation, CI/CD, and scalable test environments. The platform is based on hands-on delivery experience across enterprise testing programs.