With Explore, you can efficiently monitor, troubleshoot, and respond to incidents by analyzing your logs and identifying the root causes. It also helps you to correlate logs with other telemetry signals such as metrics, traces or profiles, by viewing them side-by-side.
When working with data sources that support a full range logs volume, Explore automatically displays a graph showing the log distribution for all submitted log queries. This feature is currently supported by the Elasticsearch and Loki data sources.
In Loki, generating the full range log volume via a metric query can be resource-intensive, depending on the time range queried. This is especially challenging for smaller Loki installations. To mitigate this, we recommend that you use a proxy like [nginx](https://www.nginx.com/) in front of Loki with a timeout like 10ss. Log volume histogram queries can be identified by looking for queries with the HTTP header `X-Query-Tags` with value `Source=logvolhist`; these headers are added by Grafana to all log volume histogram queries.
If the data source doesn't support loading the full range logs volume, the logs model calculates a time series by counting log rows and organizing them into buckets based on an automatically calculated time interval. The timestamp of the first log row is used to anchor the start of the logs volume in the results. The end of the time series is anchored to the time picker's **To** range. This way, you can still analyze and visualize log data efficiently even when the data source doesn't offer full range support.
Logs navigation, located at the right side of the log lines, can be used to easily request additional logs by clicking **Older logs** at the bottom of the navigation. This is especially useful when you reach the line limit and you want to see more logs. Each request run from the navigation displays in the navigation as separate page. Every page shows `from` and `to` timestamps of the incoming log lines. You can see previous results by clicking on each page. Explore caches the last five requests run from the logs navigation so you're not re-running the same queries when clicking on the pages, saving time and resources.
| **Time** | Shows or hides the time column. This is the timestamp associated with the log line as reported from the data source. |
| **Unique labels** | Shows or hides the unique labels column that includes only non-common labels. All common labels are displayed above. |
| **Wrap lines** | Set this to `true` if you want the display to use line wrapping. If set to `false`, it will result in horizontal scrolling. |
| **Prettify JSON** | Set this to `true` to pretty print all JSON logs. This setting does not affect logs in any format other than JSON. |
| **Deduplication** | Log data can be very repetitive. Explore hides duplicate log lines using a few different deduplication algorithms. **Exact** matches are done on the whole line except for date fields. **Numbers** matches are done on the line after stripping out numbers such as durations, IP addresses, and so on. **Signature** is the most aggressive deduplication as it strips all letters and numbers and matches on the remaining whitespace and punctuation. |
| **Display results order** | You can change the order of received logs from the default descending order (newest first) to ascending order (oldest first). |
Explore automatically detects some incorrectly escaped sequences in log lines, such as newlines (`\n`, `\r`) or tabs (`\t`). When it detects such sequences, Explore provides an **Escape newlines** option.
Explore replaces these sequences, changing the option from **Escape newlines** to **Remove escaping**. Assess the changes, as the parsing may not be accurate based on the input. To revert the replacements, click **Remove escaping**.
For logs where a `level` label is specified, the value of this label is used to determine the log level and update the color of each log line accordingly.
If the log doesn't have a specified level label, Grafana attempts to determine if its content matches any of the supported expressions.
Refer to the following table for more information. The log level is always determined by the first match. If Grafana isn't able to infer a log level field, it gets visualized as an unknown log level.
When using the Loki data source, if `level` is part of your log line, you can use parsers such as `json`, `logfmt`, or `regex` to extract the level information into a level label. This label is used to determine the level value, allowing the histogram to display the various log levels as separate bars.
When your query includes specific words or expressions for keyword search, Explore highlights them in log lines to enhance visibility. This highlighting feature facilitates easier identification and focus on the relevant content within your logs.
In Explore, each log line has an expandable section called **Log details** that you open by clicking on the log line. The Log details view provides additional information and exploration options in the form of **Fields** and **Links** attached to the log lines, enabling a more robust interaction and analysis.
Within the **Log details** view, you have the ability to filter the displayed fields in two ways: a positive filter, which focuses on an specific field and a negative filter, which excludes certain fields.
These filters modify the corresponding query that generated the log line, incorporating equality and inequality expressions accordingly.
If the data source supports it, as is the case with Loki and Elasticsearch, log details will verify whether the field is already included in the current query, indicating an active state for positive filters. This enables you to toggle it off from the query or convert the filter expression from positive to negative as necessary.
Click the **eye icon** to select a subset of fields to visualize in the logs list instead of the complete log line.
Each field has a **stats icon**, which displays ad-hoc statistics in relation to all displayed logs.
Grafana provides data links or correlations, allowing you to convert any part of a log message into an internal or external link. These links enable you to navigate to related data or external resources, offering a seamless and convenient way to explore additional information.
Log context is a feature that displays additional lines of context surrounding a log entry that matches a specific search query. This helps in understanding the context of the log entry and is similar to the `-C` parameter in the `grep` command.
Toggle **Wrap lines** if you encounter long lines of text that make it difficult to read and analyze the context around log entries. By enabling this toggle, Grafana automatically wraps long lines of text to fit within the visible width of the viewer, making the log entries easier to read and understand.
Click **Open in split view** to execute the context query for a log entry in a split screen in the Explore view. Clicking this button opens a new Explore pane with the context query displayed alongside the log entry, making it easier to analyze and understand the surrounding context.
Linking log lines in Grafana allows you to quickly navigate to specific log entries for detailed and precise analysis. Click **Copy shortlink** to generate and copy a [short URL](/docs/grafana/<GRAFANA_VERSION>/developers/http_api/short_url/) that provides direct access to the exact log entry within an absolute time range. When you open the link, Grafana automatically scrolls to the corresponding log line and highlights it in blue, making it easy to identify and focus on relevant information.
The **Live tailing feature** allows you to monitor the latest logs in real-time, making it easier to track events as they occur and promptly detect issues.
If the selected data source supports log samples and both log and metric queries, you will automatically see log line samples that contribute to the visualized metrics for metric queries. **This feature is currently only supported by the Loki data source.**
If you are transitioning from a metrics data source that implements `DataSourceWithQueryExportSupport` (such as Prometheus) to a logging data source that supports `DataSourceWithQueryImportSupport` (such as Loki), Explore retains the labels from your query that exist in the logs and use them to query the log streams.
For example, after switching to the Loki data source, the Prometheus query `grafana_alerting_active_alerts{job="grafana"}` changes to `{job="grafana"}`. This will retrieve a set of logs within the specified time range, which can be searched using grep or text search.
