|
|
|
@ -23,8 +23,8 @@ runtime profiling data on their metrics HTTP server (default `:8080`).
|
|
|
|
|
|
|
|
|
|
### Collecting a profile
|
|
|
|
|
|
|
|
|
|
To collect a profile, port-forward to the component's metrics endpoint and
|
|
|
|
|
collect the data from the [endpoint](#endpoints) of choice:
|
|
|
|
|
To collect a profile, port-forward to the component's metrics endpoint
|
|
|
|
|
and collect the data from the [endpoint](#endpoints) of choice:
|
|
|
|
|
|
|
|
|
|
```console
|
|
|
|
|
$ kubectl port-forward -n <namespace> deploy/<component> 8080
|
|
|
|
@ -33,3 +33,10 @@ $ curl -Sk -v http://localhost:8080/debug/pprof/heap > heap.out
|
|
|
|
|
|
|
|
|
|
The collected profile [can be analyzed using `go`](https://blog.golang.org/pprof),
|
|
|
|
|
or shared with one of the maintainers.
|
|
|
|
|
|
|
|
|
|
## Resource usage
|
|
|
|
|
|
|
|
|
|
As `kubectl top` gives a limited (and at times inaccurate) overview of
|
|
|
|
|
resource usage, it is often better to make use of the Grafana metrics
|
|
|
|
|
to gather insights. See [monitoring](../guides/monitoring.md) for a
|
|
|
|
|
guide on how to visualize this data with a Grafana dashboard.
|
|
|
|
|