Pyroscope コマンド

Grafana Pyroscopeはアプリケーションのパフォーマンスボトルネックを見つけるのに役立つ継続的プロファイリングプラットフォームです。複数の言語をサポートし、Grafanaとネイティブに統合され、プロファイル収集のためのプッシュモードとプルモードの両方を提供します。

インストール

Linux/Ubuntu

# Download Pyroscope binary
curl -fL https://github.com/grafana/pyroscope/releases/latest/download/pyroscope_Linux_x86_64.tar.gz | tar xz
sudo mv pyroscope /usr/local/bin/

# Verify
pyroscope --version

# Docker
docker run -d --name pyroscope \
  -p 4040:4040 \
  grafana/pyroscope:latest

Helm (Kubernetes)

helm repo add grafana https://grafana.github.io/helm-charts
helm repo update
helm install pyroscope grafana/pyroscope -n pyroscope --create-namespace

サーバー設定

# pyroscope-config.yaml
# Start with: pyroscope -config.file=pyroscope-config.yaml

storage:
  backend: filesystem
  filesystem:
    dir: /var/lib/pyroscope/data

server:
  http_listen_port: 4040

limits:
  max_query_lookback: 720h
  max_query_length: 6h

scrape_configs:
- job_name: "my-go-service"
  scrape_interval: "15s"
  static_configs:
  - targets: ["my-service:6060"]
  profiling_config:
    pprof_config:
      process_cpu:
        enabled: true
      memory:
        enabled: true

# Start Pyroscope server
pyroscope -config.file=pyroscope-config.yaml

# Start with default settings
pyroscope

# Access the web UI
# http://localhost:4040

プッシュモード — Go SDK

// Install: go get github.com/grafana/pyroscope-go

// Add to your Go application main():
// import "github.com/grafana/pyroscope-go"
//
// pyroscope.Start(pyroscope.Config{
//     ApplicationName: "my-go-service",
//     ServerAddress:   "http://pyroscope:4040",
//     ProfileTypes: []pyroscope.ProfileType{
//         pyroscope.ProfileCPU,
//         pyroscope.ProfileAllocObjects,
//         pyroscope.ProfileAllocSpace,
//         pyroscope.ProfileInuseObjects,
//         pyroscope.ProfileInuseSpace,
//         pyroscope.ProfileGoroutines,
//         pyroscope.ProfileMutexCount,
//         pyroscope.ProfileMutexDuration,
//         pyroscope.ProfileBlockCount,
//         pyroscope.ProfileBlockDuration,
//     },
// })

プッシュモード — Python SDK

# Install the Python SDK
pip install pyroscope-io

# Add to your Python application
import pyroscope

pyroscope.configure(
    application_name="my-python-service",
    server_address="http://pyroscope:4040",
    tags={
        "region": "us-east-1",
        "env": "production",
    },
)

# Use tags for dynamic labeling
with pyroscope.tag_wrapper({"endpoint": "/api/users"}):
    handle_users_request()

プッシュモード — Java SDK

# Add to JVM arguments
# Download the Java agent JAR from GitHub releases
java -javaagent:pyroscope.jar \
  -Dpyroscope.application.name=my-java-service \
  -Dpyroscope.server.address=http://pyroscope:4040 \
  -Dpyroscope.format=jfr \
  -jar my-app.jar

プッシュモード — Ruby SDK

# Install the Ruby gem
gem install pyroscope

# Add to your Ruby application
require 'pyroscope'

Pyroscope.configure do |config|
  config.application_name = "my-ruby-service"
  config.server_address = "http://pyroscope:4040"
  config.tags = {
    "region" => "us-east-1",
    "env" => "production",
  }
end

プッシュモード — Node.js SDK

# Install the Node.js package
npm install @pyroscope/nodejs

// Add to your Node.js application
const Pyroscope = require('@pyroscope/nodejs');

Pyroscope.init({
  serverAddress: 'http://pyroscope:4040',
  appName: 'my-node-service',
  tags: {
    region: 'us-east-1',
    env: 'production',
  },
});

Pyroscope.start();

プッシュモード — .NET SDK

# Install the NuGet package
dotnet add package Pyroscope

// Add to your .NET application Program.cs
// Pyroscope.Profiler.Instance.SetTag("region", "us-east-1");
// Use the PYROSCOPE_APPLICATION_NAME and PYROSCOPE_SERVER_ADDRESS
// environment variables to configure

プルモード — pprofエンドポイントのスクレイピング

# Configure Pyroscope to scrape pprof endpoints (in pyroscope-config.yaml)
scrape_configs:
- job_name: "go-services"
  scrape_interval: "15s"
  static_configs:
  - targets: ["app1:6060", "app2:6060"]
  profiling_config:
    pprof_config:
      process_cpu:
        enabled: true
        path: "/debug/pprof/profile"
        delta: true
      memory:
        enabled: true
        path: "/debug/pprof/heap"
        delta: true
      goroutine:
        enabled: true
        path: "/debug/pprof/goroutine"
      block:
        enabled: true
        path: "/debug/pprof/block"
        delta: true
      mutex:
        enabled: true
        path: "/debug/pprof/mutex"
        delta: true

- job_name: "kubernetes-pods"
  scrape_interval: "15s"
  kubernetes_sd_configs:
  - role: pod
  relabel_configs:
  - source_labels: [__meta_kubernetes_pod_annotation_pyroscope_io_scrape]
    action: keep
    regex: true
  - source_labels: [__meta_kubernetes_pod_annotation_pyroscope_io_port]
    action: replace
    target_label: __address__
    regex: (.+)
    replacement: ${1}

Grafana連携

# Add Pyroscope as a data source in Grafana
# 1. Navigate to Configuration > Data Sources > Add data source
# 2. Search for "Pyroscope" (or "Grafana Pyroscope")
# 3. Set URL to http://pyroscope:4040
# 4. Click "Save & Test"

# Grafana Explore:
# 1. Select the Pyroscope data source
# 2. Choose profile type (cpu, memory, goroutine, etc.)
# 3. Filter by labels (service_name, env, region)
# 4. View flame graph, table, or both

プロファイルのクエリ

# Query profiles via HTTP API
# List available label names
curl -s http://localhost:4040/pyroscope/api/v1/labels | python3 -m json.tool

# List label values
curl -s "http://localhost:4040/pyroscope/api/v1/label-values?label=service_name" | python3 -m json.tool

# Render a profile (returns pprof format)
curl -s "http://localhost:4040/pyroscope/api/v1/profiles/render?query=process_cpu:cpu:nanoseconds:cpu:nanoseconds{service_name=\"my-service\"}&from=now-1h&until=now" -o profile.pb.gz

# Analyze with go tool pprof
go tool pprof -http=:8080 profile.pb.gz

差分ビュー（プロファイル比較）

# In the Pyroscope web UI:
# 1. Select "Comparison" mode in the top toolbar
# 2. Set baseline time range on the left
# 3. Set comparison time range on the right
# 4. View differential flame graph
# Red = increased time, Green = decreased time

# Via API — compare two time ranges
curl -s "http://localhost:4040/pyroscope/api/v1/profiles/render-diff?leftQuery=process_cpu:cpu:nanoseconds{service_name=\"my-service\"}&leftFrom=now-2h&leftUntil=now-1h&rightQuery=process_cpu:cpu:nanoseconds{service_name=\"my-service\"}&rightFrom=now-1h&rightUntil=now"

プロファイルの種類

Profile Type	Description
`process_cpu`	CPU time consumed by the process
`memory`	Heap memory allocations
`goroutine`	Active goroutine count (Go)
`mutex`	Mutex contention (Go)
`block`	Blocking operations (Go)
`wall`	Wall-clock time
`alloc_objects`	Number of allocations
`alloc_space`	Bytes allocated
`inuse_objects`	Live objects in memory
`inuse_space`	Live bytes in memory

クイックリファレンス

Component	Default Port	Purpose
Pyroscope Server	4040	Storage, query, web UI
Grafana	3000	Visualization and dashboards
pprof endpoints	6060	Go application profiling

Feature	Description
Push mode	SDKs send profiles to Pyroscope
Pull mode	Pyroscope scrapes pprof endpoints
Flame graphs	Interactive CPU/memory visualization
Diff view	Compare profiles across time periods
Tag filtering	Filter by service, env, region, etc.
Grafana native	Built-in Pyroscope data source