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Pyroscope Comandos

Grafana Pyroscope é uma plataforma de perfilamento contínuo que ajuda a encontrar gargalos de desempenho em suas aplicações. Suporta múltiplas linguagens, integra-se nativamente com Grafana e oferece modos push e pull para coleta de perfis.

Instalação

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

Configuração do Servidor

# 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

Modo Push — 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,
//     },
// })

Modo Push — 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()

Modo Push — 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

Modo Push — 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

Modo Push — 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();

Modo Push — .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

Modo Pull — Scraping pprof Endpoints

# 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}

Integração com Grafana

# 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

Consultando Perfis

# 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

Visualização de Diferenças (Comparando Perfis)

# 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"

Tipos de Perfil

Profile TypeDescrição
process_cpuCPU time consumed by the process
memoryHeap memory allocations
goroutineActive goroutine count (Go)
mutexMutex contention (Go)
blockBlocking operations (Go)
wallWall-clock time
alloc_objectsNumber of allocations
alloc_spaceBytes allocated
inuse_objectsLive objects in memory
inuse_spaceLive bytes in memory

Referência Rápida

ComponentDefault PortPurpose
Pyroscope Server4040Storage, query, web UI
Grafana3000Visualization and dashboards
pprof endpoints6060Go application profiling
FuncionalidadeDescrição
Push modeSDKs send profiles to Pyroscope
Pull modePyroscope scrapes pprof endpoints
Flame graphsInteractive CPU/memory visualization
Diff viewCompare profiles across time periods
Tag filteringFilter by service, env, region, etc.
Grafana nativeBuilt-in Pyroscope data source