Log Events
The Log Events panel shows log entries that match specific filters. Use it to monitor error rates, trace issues, or watch for specific application or infrastructure events in real time.
Add a Log Events panel
-
Open the dashboard where you want the panel.
-
Click Add Panel.
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In Choose Visualization, select Log Events.
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Build your log query in Graph your data to define the log source and filters.
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Enter a descriptive Title.
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Click Save to add the panel.
Build queries (Graph your data)
Build queries (Graph your data)
The Graph your data section defines which metrics are displayed and how they are processed before visualization. These steps apply to most panel types in Kloudfuse.
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Click Add Query to create a new query. Repeat to add multiple queries.
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Click Select a metric to choose the metric name you want to query.
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Use From to select the metric source or namespace.
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Click Add Label to filter results by label values (for example:
pod=web
,env=prod
). -
Select an Aggregation (for example:
min
,max
,sum
,avg
) to reduce raw samples to one value per time interval. -
Use the Select dropdown (if available) to set the aggregation interval (for example:
1m
,5m
). -
Click Add Functions to apply transformations to your data.
Common examples: *
rate()
— Convert counters to rates. *derivative()
— Show the rate of change. *moving_avg()
— Smooth short-term fluctuations. *scale()
— Multiply values by a constant.
Query order determines formula identifiers: the first query = |
Add formulas
Use formulas to create new series from existing queries.
-
Click Add Formula in Graph your data.
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Reference queries by their letter (
a
,b
, …) or alias. -
Enter your expression and click Apply.
Example — double a series:
2*a
Example — percentage change between two queries:
((a - b) / b) * 100
|
Log Events–specific settings
Once your log source is selected:
-
Log source — Choose the dataset, index, or stream that stores your logs.
-
Time window — Define the time range for displayed logs (e.g.,
Last 5 minutes
,Last 24 hours
). -
Filters — Apply field-based filters (for example:
level=error
,service=api
, `pod=f*