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[release/v1.2] Add doc about profiling Alloy (#1840)
Co-authored-by: Clayton Cornell <[email protected]> Co-authored-by: Paulin Todev <[email protected]>
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--- | ||
canonical: https://grafana.com/docs/alloy/latest/troubleshoot/profile/ | ||
description: Learn how to profile resource consumption | ||
title: Profile Grafana Alloy resource consumption | ||
menuTitle: Profile resource consumption | ||
weight: 300 | ||
--- | ||
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# Profile {{% param "FULL_PRODUCT_NAME" %}} resource consumption | ||
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{{< param "PRODUCT_NAME" >}} is written in the Go programming language, which offers [built-in][pprof-pkg] support for profiling. | ||
Like other applications written in Go, you can profile {{< param "PRODUCT_NAME" >}} by sending an HTTP request, which returns a pprof Go profile. | ||
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Once you have the pprof file, visualize it as a [flame graph][flame-graph] in [Grafana Pyroscope][pyroscope-getstarted]. | ||
Alternatively, you could visualize it on [Grafana Play][pyroscope-adhoc] or locally by using Go's built-in [pprof tool][go-pprof]. | ||
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{{< admonition type="note" >}} | ||
A profile may contain sensitive information about your environment. | ||
You may not want to upload your profiles to a public location. | ||
{{< /admonition >}} | ||
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The port you use to send the HTTP request is controlled by the `--server.http.listen-addr` [command line argument][cmd-cli]. | ||
It is set to `127.0.0.1:12345` by default. | ||
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[pprof-pkg]: https://pkg.go.dev/net/http/pprof | ||
[pyroscope-adhoc]: https://play.grafana.org/a/grafana-pyroscope-app/ad-hoc | ||
[go-pprof]: https://go.dev/blog/pprof | ||
[pyroscope-getstarted]: https://grafana.com/docs/pyroscope/latest/get-started/ | ||
[flame-graph]: https://grafana.com/docs/pyroscope/latest/view-and-analyze-profile-data/flamegraphs/ | ||
[cmd-cli]: ../../reference/cli/run | ||
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## Obtaining a single profile | ||
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Different types of HTTP requests will retrieve different profiles. | ||
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### Memory consumption | ||
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Goroutine leaks often cause memory leaks. | ||
This is why obtaining a goroutine profile is usually necessary when investigating memory issues. | ||
For example: | ||
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```bash | ||
curl localhost:12345/debug/pprof/heap -o heap.pprof | ||
curl localhost:12345/debug/pprof/goroutine -o goroutine.pprof | ||
``` | ||
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It is often helpful to collect profiles both when memory usage is low and when it is high. | ||
You can compare the profiles, and it may be easier to identify what caused the memory consumption to increase. | ||
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### CPU consumption | ||
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If you are experiencing high CPU consumption, you can collect a CPU profile: | ||
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```bash | ||
curl http://localhost:12345/debug/pprof/profile?seconds=30 -o cpu.pprof | ||
``` | ||
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The `?seconds=30` part of the URL above means the profiling will continue for 30 seconds. | ||
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## Continuous profiling | ||
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You don't have to send manual `curl` commands each time you want to collect profiles. | ||
You can also profile continuously using the [pyroscope components][] in {{< param "PRODUCT_NAME" >}}. | ||
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If you have very few {{< param "PRODUCT_NAME" >}} instances, you can even configure them to profile themselves. | ||
However, if you have a large cluster of collectors, it is best to set up {{< param "PRODUCT_NAME" >}} instances whose sole job is to profile other {{< param "PRODUCT_NAME" >}} instances. | ||
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The following is an example of an {{< param "PRODUCT_NAME" >}} instance profiling itself: | ||
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```alloy | ||
pyroscope.scrape "default" { | ||
targets = [{"__address__" = "localhost:12345", "service_name"="alloy"}] | ||
forward_to = [pyroscope.write.default.receiver] | ||
} | ||
pyroscope.write "default" { | ||
endpoint { | ||
url = "https://profiles-prod-014.grafana.net" | ||
basic_auth { | ||
username = sys.env("PYROSCOPE_USERNAME") | ||
password = sys.env("PYROSCOPE_PASSWORD") | ||
} | ||
} | ||
} | ||
``` | ||
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[pyroscope components]: ../../reference/components/pyroscope | ||
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## Expected resource consumption | ||
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Refer to [Estimate resource usage][res-usage] for more information about the expected resource consumption in {{< param "PRODUCT_NAME" >}}. | ||
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[res-usage]: ../../introduction/estimate-resource-usage | ||
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## {{% param "PRODUCT_NAME" %}} consumes an abnormally large amount of resources | ||
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If {{< param "PRODUCT_NAME" >}} consumes an abnormally large amount of resources, you can open an issue in the [Alloy repository][alloy-repo]. | ||
Attach your pprof files and your {{< param "PRODUCT_NAME" >}} configuration file. | ||
Make sure you redact any secrets in the attachments. | ||
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[alloy-repo]: https://github.com/grafana/alloy/issues |