You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
By default, vCluster creates logs in the control plane pod in console format, which is easy to read and preferred for manual log review. However, you can configure the logging in the control plane pod to JSON format. By enabling the JSON format, logs can be sent to external tools to aggregate logs across multiple virtual clusters to help monitor and troubleshoot these virtual clusters.
11
+
By default, vCluster generates logs in console format. Console format provides human-readable output that is well-suited for manual log review and troubleshooting. Alternatively, you can configure vCluster to output logs in JSON format. JSON format enables integration with external logging systems for centralized log aggregation and automated monitoring across multiple virtual clusters.
12
12
13
13
## Log encoding formats
14
14
15
15
vCluster supports two log encoding formats for the vCluster control plane pod.
16
16
17
-
- console (_Default_): Human-readable format. Ideal for development and manual log review.
18
-
- JSON: Structured format for log aggregation. Ideal for external monitoring and analysis tools.
17
+
-[console](#console-format) (_Default_): Human-readable format. Ideal for development and manual log review.
18
+
-[JSON](#json-format): Structured format for log aggregation. Ideal for external monitoring and analysis tools.
19
19
20
20
### Console format
21
21
22
-
The console format provides human-readable logs with timestamps, log levels, source locations, and contextual information. The console format is best suited for use cases where users will be troubleshooting a single virtual cluster. Choose this format in environments where human readability is more important than structured log parsing. Example use cases include:
22
+
The console format provides human-readable logs with timestamps, log levels, source locations, and contextual information. This format works well for use cases where users are troubleshooting a single virtual cluster. Choose this format in environments where human readability is more important than structured log parsing. Example use cases include:
23
23
24
-
* Local development and testing, where developers benefit from quick, readable output
25
-
* Single virtual cluster analysis, where users will manually review logs and debug in a terminal
24
+
- Local development and testing, where developers benefit from quick, readable output
25
+
- Single virtual cluster analysis, where users manually review logs and debug in a terminal
26
26
27
27
```text
28
28
2025-06-16 04:43:25 INFO license loader/inject.go:52 initializing license... {"component": "vcluster"}
@@ -32,10 +32,9 @@ The console format provides human-readable logs with timestamps, log levels, sou
32
32
```
33
33
34
34
### JSON format
35
+
The JSON format structures log data for programmatic processing and integration with log management systems. This format is best suited for use cases where external tools monitor and analyze logs for multiple virtual clusters. Log aggregation tools (for example, Elasticsearch or Splunk) can ingest these logs to support automated analysis, alerting, and integration with monitoring platforms (for example, Prometheus and Grafana). Example use cases include:
35
36
36
-
The JSON format structures log data for programmatic processing and integration with log management systems. The JSON format is best suited for use cases where external tools are used to monitor and analyze logs for multiple virtual clusters. Log aggregation tools (e.g. Elasticsearch or Splunk) can ingest these logs to support automated analysis, alerting, and integration with monitoring platforms (e.g. Prometheus and Grafana). Examples use cases include:
37
-
38
-
* Product environments where multiple virtual clusters are being monitored and logs from all of them need to be parsed and processed automatically.
37
+
- Production environments where you monitor multiple virtual clusters and require automatic parsing and processing of logs
0 commit comments