observability intro

Author: santiviquez

observability/observability.md

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-OBSERVABILITY INTRO GOES HERE
+Use observability to monitor data quality at scale across all your datasets.
+Observability helps you catch unexpected issues without needing to define every rule up front.
 
-## What is Observability?
+Where data testing focuses on known expectations, observability helps you detect the unknown unknowns—like late-arriving records, schema changes, or sudden spikes in missing values. It offers broad, low-effort coverage and requires little configuration, making it easy to share data quality responsibilities across technical and non-technical teams.
+
+## What is data observability?
+
+**Data observability** is the practice of continuously monitoring your data for unexpected changes, anomalies, and structural issues. It involves collecting and analyzing metrics about your datasets to understand their health over time.
+
+Instead of writing checks manually for each dataset, observability uses profiling and metrics to automatically detect problems such as:
+- A spike in null values
+- A drop in row counts
+- Unusual value distributions
+
+**Data Observability helps you:**
+- Detect incidents faster
+- Scale coverage across more data
+- Reduce time spent on manual testing
+- Empower more team members to spot and act on issues
+
+
+## What is metrics monitoring?
+
+**Metrics monitoring** is the foundation of data observability in Soda. Soda collects metrics from datasets—such as row count, null values, min/max, and value distribution—and tracks how those metrics evolve over time.
+
+Soda then uses built-in anomaly detection to identify when metrics deviate from expected patterns. These deviations are surfaced in the **Metric Monitors** tab for each dataset.
+
+You can use metric monitoring to:
+- Spot problems without writing checks
+- Establish baselines for normal behavior
+- Alert data owners when something unusual happens
+- Provide insight to business users without requiring code
+
+## What's Next?
+To get started with Soda observability, follow one of these guides:
+
+- [Data observability quickstart]({% link observability/quickstart.md %}): Set up monitoring to detect anomalies in your datasets.
+- [Data observability guide]({% link observability/observability-guide.md %}): Learn how to get the most out of Soda’s data observability platform.