new doc: use at your own risk

Author: DebashisBorgohainO2

docs/user-guide/.pages

@@ -16,4 +16,5 @@ nav:
     - Identity and Access Management (IAM): identity-and-access-management
     - Management: management
     - Profile: profile
+    - Best Practices: best-practices
 

docs/user-guide/best-practices/.pages

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+nav:
+    - Use At Your Own Risk: use-at-your-own-risk.md

docs/user-guide/best-practices/use-at-your-own-risk.md

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+OpenObserve does not restrict the number of records returned or the length of the time range in a query. You can query a few minutes or several months of data. 
+However, queries that return a large number of results, especially those with small time intervals, breakdown fields, or large text fields, can overload the browser. 
+This may cause the UI to become unresponsive or crash, particularly on the **Logs** page or in **dashboard panels**.
+
+Two scenarios where this risk is significant:
+
+## 1. Long Duration Queries with Small Intervals 
+
+> **Where this issue can occur**: Logs Search and Dashboards
+<br>
+
+When you use histogram queries such as `histogram("timestamp", interval)`, the `interval` defines how the data is grouped over time. For example, an `interval` of `5m` groups logs into 5-minute buckets. The longer the time range and the smaller the interval, the more buckets the query will return.
+
+Each bucket becomes a row in the query result. If the query returns a large number of rows, the browser must load and render all of them. This can slow down the UI or cause it to crash.
+
+Example: 
+
+```sql linenums="1"
+
+SELECT histogram(_timestamp, '5m') AS log_time_interval,
+       COUNT(*) AS total_logs
+FROM "default"
+GROUP BY log_time_interval
+ORDER BY log_time_interval ASC
+```
+
+The above query returns the number of logs collected every 5 minutes. When run over a 7-day period, it generates more than 2,000 time buckets, each representing a row that the browser must load and render. This volume of data can cause the UI to become unresponsive or crash.
+
+> **Note:** <br>
+>**In Dashboard Panels- Breakdown Fields Multiply the Problem**<br>
+>In dashboard panels, if you add a breakdown to the query (e.g., by `log.level`), it multiplies the number of rows. <br> For example,
+>
+>- You already have 2,000 time buckets  
+>- `log.level` has 5 unique values: `INFO`, `ERROR`, `DEBUG`, `WARN`, `TRACE`
+>
+>The result becomes: 2,000 time buckets × 5 breakdown values = 10,000 rows
+>
+>That is 5X more data than without the breakdown. 
+>
+>All of it must be fetched, loaded, and rendered in your browser. It ends up crashing the UI. 
+
+## 2. Tables that Include Large Text Fields 
+
+> **Where this issue can occur**: Dashboards
+
+
+When you display logs in a table on a dashboard, avoid including large text fields such as `log.body`. 
+
+Over longer time ranges, such as several days, these fields can significantly increase the size of the response. This results in a larger payload, which can cause the UI to become unresponsive or crash.
+
+## Best Practices to Avoid UI Crashes
+
+To keep the user interface responsive and avoid crashes, follow these recommendations when working with large datasets:
+
+**For long-duration queries with small intervals**
+
+- Increase the interval when querying longer time ranges. Example: Use `8h` or `12h` instead of `5m` if you are querying several days of logs.  
+- Limit the time range to reduce the number of records returned by the query.   
+- Avoid or limit breakdown fields on large datasets. Breakdown fields multiply the number of results significantly. 
+
+**For tables that include large text fields**
+
+- Avoid including large fields such as `log.body` in dashboard tables unless absolutely necessary.  
+- Preview the field before including it in a large table.  
+- Use shorter time ranges when you need to view logs with large messages.

docs/user-guide/dashboards/.pages

@@ -6,4 +6,5 @@ nav:
     - Variable Dependencies in Dashboards: variable-dependencies.md
     - Comparison Against in Dashboards: comparison-against-in-dashboards.md
     - Custom Charts: custom-charts
+