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

# Events

> Manage events in Cognite Data Fusion (CDF).

<Badge color="orange">Legacy data modeling</Badge>

<Note>
  This resource is part of the **asset-centric** data model.

  * **New projects**: We recommend using the **[data modeling](/api-reference/concepts/20230101/data-modeling)** service for greater flexibility and performance.
  * **Existing projects**: This resource remains fully supported for maintaining legacy applications.
</Note>

**Events** store complex information that happens over **a period**. Events have a **start time** and an **end time** and can be related to **multiple assets**. For example, the Events API includes alarms, process data, and logs.

The `startTime` and `endTime` for the event's period are represented in Unix Epoch time in milliseconds. CDF doesn't support fractional milliseconds and doesn't count leap seconds. You can specify both the start and end times in the future, but the end timestamp must be greater than or equal to the start timestamp for the input to be valid.

To describe and classify events, you can add arbitrary string values for `description`, `metadata`, `type`, and `subtype`. All event information is stored in string format when you store it in metadata.

<Note>
  Use the Data Modeling service to store manually generated, schedulable activities with low volumes, such as maintenance schedules, work orders, or other appointment-type activities.
</Note>

<Info>
  **Events** and **time series** data are high-volume data types that can record data in microsecond resolutions. Avoid using events as a time series store, especially when the data flow is from a single instance of sensors (temperature, pressure, voltage), simulators, or state machines (on, off, disconnected). The [Time Series API](/api-reference/concepts/20230101/time-series) provides very low latency read and write performance and specialized filters and aggregations designed to analyze time series data.
</Info>

## What you can do

* **Create** events with metadata, time ranges, and asset links.
* **Search** for events by description, metadata, or time range.
* **Filter** events using advanced criteria.
* **Aggregate** event data for analytics and reporting.
* **Update** event properties and asset associations.
* **Delete** events that are no longer needed.

## Rate and concurrency limits

For Events rate and concurrency limits, see [API rate limits](/api-reference/concepts/20230101/rate-limits#events).