

[](https://docs.datakitchen.io/articles/#!open-source-data-observability/data-observability-overview)
[](https://data-observability.slack.com)
*<p style="text-align: center;">Data breaks. Servers break. Your toolchain breaks. Ensure your data team is the first to know and the first to solve with visibility across and down your data estate. Save time with simple, fast data quality test generation and execution. Trust your data, tools, and systems end to end.</p>*
DataKitchen Open Source Data Observability product suite (released April 2024).
* [**DataOps TestGen**](https://docs.datakitchen.io/articles/dataops-testgen-help/dataops-testgen-help) is a data quality verification tool that does five main tasks: (1) data profiling, (2) new dataset screening and hygiene review, (3) algorithmic generation of data quality validation tests, (4) ongoing production testing of new data refreshes and (5) continuous periodic monitoring of datasets for anomalies [(GitHub)](https://github.com/DataKitchen/dataops-testgen).
* [**DataOps Observability**](https://docs.datakitchen.io/articles/dataops-observability-help/dataops-observability-help) monitors every tool used in the journey of data from data source to customer value, from any team development environment into production, across every tool, team, data set, environment, and project so that problems are detected, localized, and understood immediately [(GitHub)](https://github.com/DataKitchen/dataops-observability).

For background on why we build this product check out the articles on ['why we open sourced'](https://datakitchen.io/why-we-open-sourced-our-data-observability-products/), [manifesto](https://datajourneymanifesto.org/), [free book](https://datakitchen.io/the-dataops-cookbook/), and [top data observability and DataOps articles](https://datakitchen.io/datakitchen-resource-guide-to-data-journeys-data-observability-dataops/).
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