Configuration reference

Important: This documentation is about an older version. It's relevant only to the release noted, many of the features and functions have been updated or replaced. Please view the current version.

Documentation

Grafana Pyroscope

Configure the client to send profiles

Grafana Alloy

Set up profiling with eBPF

Configuration reference

Open source

Grafana Alloy supports eBPF profiling. The configuration file is written in the River language and is composed of components that are used to collect, transform, and send data.

The pyroscope.ebpf component is used to collect application performance profiles via eBPF.

The pyroscope.ebpf runs on the host machine and collects stack traces associated with a process running on the current host.

Using the targets argument, you can specify which processes and containers to profile on the machine. The targets can be from discovery components such as discovery.process, discovery.kubernetes, discovery.docker, and discovery.dockerswarm.

You can use the discovery.relabel component to relabel discovered targets and set your own labels. For more information, refer to the Components documentation.

The forward_to parameter should point to a pyroscope.write component to send the collected profiles to your Pyroscope Server or Grafana Cloud.

Name	Type	Description	Default	Required
`targets`	`list(map(string))`	List of targets to group profiles by container id		yes
`forward_to`	`list(ProfilesReceiver)`	List of receivers to send collected profiles to.		yes
`collect_interval`	`duration`	How frequently to collect profiles	`15s`	no
`sample_rate`	`int`	How many times per second to collect profile samples	97	no
`pid_cache_size`	`int`	The size of the pid -> proc symbols table LRU cache	32	no
`build_id_cache_size`	`int`	The size of the elf file build id -> symbols table LRU cache	64	no
`same_file_cache_size`	`int`	The size of the elf file -> symbols table LRU cache	8	no
`container_id_cache_size`	`int`	The size of the pid -> container ID table LRU cache	1024	no
`collect_user_profile`	`bool`	A flag to enable/disable collection of userspace profiles	true	no
`collect_kernel_profile`	`bool`	A flag to enable/disable collection of kernelspace profiles	true	no
`demangle`	`string`	C++ demangle mode. Available options are: `none`, `simplified`, `templates`, `full`	`none`	no

Supported languages

The pyroscope.ebpf component supports the following languages:

Go
Rust
C/C++ with frame pointers enabled
Python

Send data Grafana Cloud Profiles

When sending to Grafana Cloud Profiles, you can use the following pyroscope.write component configuration which makes uses of environment variables:

pyroscope.write "endpoint" {
    endpoint {
        basic_auth {
            password = env("GC_PASSWORD")
            username = env("GC_USER")
        }
        url = env("GC_URL")
    }
}

Ensure that you have appropriately configured the GC_URL, GC_USER, and GC_PASSWORD environment variables.

Profile collecting behavior

The pyroscope.ebpf component collects stack traces associated with a process running on the current host. You can use the sample_rate argument to define the number of stack traces collected per second. The default is 97.

The following labels are automatically injected into the collected profiles if you have not defined them. These labels can help you pin down a profiling target.

Label	Description
`service_name`	Pyroscope service name. It’s automatically selected from discovery meta labels, if possible. Otherwise, it defaults to `unspecified`.
`__name__`	pyroscope metric name. Defaults to `process_cpu`.
`__container_id__`	The container ID derived from target.

Privileges

You are required to run the agent as root and inside host pid namespace in order to pyroscope.ebpf component to work.

Targets

One of the following special labels must be included in each target of targets and the label must correspond to the container or process that is profiled:

__container_id__: The container ID.
__meta_docker_container_id: The ID of the Docker container.
__meta_kubernetes_pod_container_id: The ID of the Kubernetes pod container.
__process_pid__ : The process ID.

Each process is then associated with a specified target from the targets list, determined by a container ID or process PID.

If a process’s container ID matches a target’s container ID label, the stack traces are aggregated per target based on the container ID. If a process’s PID matches a target’s process PID label, the stack traces are aggregated per target based on the process PID. Otherwise, the process is not profiled.

Service name

The special label service_name is required and must always be present. If it’s not specified, it is attempted to be inferred from multiple sources:

__meta_kubernetes_pod_annotation_pyroscope_io_service_name which is a pyroscope.io/service_name pod annotation.
__meta_kubernetes_namespace and __meta_kubernetes_pod_container_name
__meta_docker_container_name
__meta_dockerswarm_container_label_service_name and __meta_dockerswarm_service_name

If service_name is not specified and could not be inferred, it is set to unspecified.

Exposed Prometheus metrics

The pyroscope.ebpf component exposes the following Prometheus metrics:

pyroscope_fanout_latency (histogram): Write latency for sending to direct and indirect components.
pyroscope_ebpf_active_targets (gauge): Number of active targets the component tracks.
pyroscope_ebpf_profiling_sessions_total (counter): Number of profiling sessions completed.
pyroscope_ebpf_profiling_sessions_failing_total (counter): Number of profiling sessions failed.
pyroscope_ebpf_pprofs_total (counter): Number of pprof profiles collected by the ebpf component.