> ## Documentation Index
> Fetch the complete documentation index at: https://docs.corelayer.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Table Monitoring

> Monitor database tables for anomalies in data volume, column values, and schema changes.

## Prerequisites

* A connected database integration (e.g., AWS RDS, ClickHouse, PlanetScale)
* At least one table available in the connected database

## Setting Up Table Monitoring

### 1. Navigate to Anomalies

In your Corelayer dashboard, go to the **Anomalies** page from the sidebar.

### 2. Add a Rule

Click **Add Rule** and select a database table from the dropdown. Tables are grouped by provider, account, database, and schema. Use the search bar to filter by table name.

Tables that already have an anomaly configuration will not appear in the list.

### 3. Configure Data Settings

After selecting a table, you will be taken to the configuration page. Start by setting up your data configuration:

**Anomaly Type**:

* **Time Series** — Use when your data has a time column that orders records chronologically. Best for tables where records arrive over time (e.g., events, transactions, logs).
* **Categorical** — Use when you want to group data by categorical columns without a time dimension. Best for dimension tables or data grouped by region, product, or category.

**Time Column** (Time Series only):

* Select the column that tracks when records were created or updated.
* Defaults to `created_at` if available.

**Partition Columns**:

* Select columns that define how data should be grouped.
* Each unique combination of partition column values creates a separate partition with its own baseline.
* For example, partitioning by `region` and `product_type` creates a baseline for each region-product combination.

**Frequency**:

* Set how often data is expected to arrive (hourly, daily, weekly, monthly).

### 4. Enable Detection Rules

Toggle on the rules you want to use:

**Volume Rule**:

* Monitors the number of rows per partition over time.
* Detects unexpected spikes or drops in data volume.
* Uses a statistical baseline (mean and standard deviation) with a k-sigma threshold.

**Column Rules** (Time Series only):

* Select specific numerical columns to monitor (integer, float, decimal, double).
* Detects shifts in column value distributions.
* Each column gets its own baseline and threshold.

**Schema Rule**:

* Detects changes to your table schema.
* Flags added, removed, or modified columns.

### 5. Configure Triggers (Optional)

Optionally, link a notification resource (Slack, Teams) to receive alerts when anomalies are detected.

### 6. Save

Click **Save** to create the anomaly configuration. Corelayer will begin collecting data to build baselines.

## Understanding the Dashboard

### Anomalies List

The main **Anomalies** page shows all configured rules grouped under the **Tables** section. Each card displays:

* The table name and database path
* Which rules are enabled (Volume, Column, Schema)
* The partition type (Time Series or Categorical)
* Whether the baseline is ready

### Detail Page

Click on a table card to view the full configuration. From here you can:

* Edit data settings (anomaly type, partition columns, frequency)
* Toggle rules on or off
* View baseline progress for each rule
* Change the notification trigger

## Baseline Collection

When a rule is first created, it enters a **Collecting** phase. During this time:

* Corelayer gathers data to compute the statistical baseline (mean, standard deviation)
* No anomalies are reported until the baseline has enough data points
* The rule status changes to **Ready** once the baseline is complete

The time to reach baseline readiness depends on data frequency and the number of partitions.

## Managing Rules

### Editing

Navigate to the table detail page and modify any configuration setting. Click **Save** to apply changes.

### Deleting

From the **Anomalies** list, click the delete icon on a table card to remove the anomaly configuration. This deletes all associated rules and baselines.

## Troubleshooting

### Baseline Not Ready?

* Verify that the table is receiving new data at the expected frequency
* Check that the partition columns produce a reasonable number of partitions
* Ensure the database integration is still connected and healthy

### No Anomalies Detected?

* Confirm the baseline is in **Ready** status
* Check the time range on the detail page (7d, 30d, 90d)
* Volume and column rules require data to deviate significantly from the baseline to trigger a finding

Need help? [Contact support](mailto:support@corelayer.com) for assistance with table monitoring.