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Load Testing & Performance Benchmarking (JMeter & k6) · Aula

Interpretando as Métricas do k6

Entenda as métricas detalhadas do k6, as etiquetas personalizadas e como visualizá-las para obter insights.

Interpretando as Métricas do k6 é uma aula grátis de Load Testing & Performance Benchmarking (JMeter & k6) no CoddyKit. Esta é a aula 3 de 4. Você pode ler a aula completa abaixo gratuitamente — depois pratica ao vivo no navegador com um editor de código integrado e um tutor de IA 24/7. Faz parte do caminho de aprendizado de Load Testing & Performance Benchmarking (JMeter & k6), e seu progresso é sincronizado entre a web e o app CoddyKit. O curso de Load Testing & Performance Benchmarking (JMeter & k6) inclui 4 aulas no total.

Partes desta aula ainda não foram traduzidas e aparecem em inglês.

What are k6 Metrics?

When you run a k6 performance test, it generates various metrics. These are numerical values that describe your system's behavior under load.

Understanding these metrics is crucial for identifying performance bottlenecks, verifying service level agreements (SLAs), and ensuring your application can handle expected traffic.

Key Metric: Request Duration

One of the most important built-in k6 metrics is http_req_duration. This measures the total time it takes for an HTTP request to complete.

  • It starts when the request is sent.
  • It ends when the full response is received.
  • It directly reflects the response time users experience.

Key Metrics: VUs & Iterations

Other fundamental metrics help you understand the load:

  • vus (Virtual Users): Shows the number of virtual users currently active during the test.
  • iterations: Counts how many times your test script's default function has been executed.

These metrics help you see if your test is applying the intended load.

Key Metrics: Data Transfer

Understanding network usage is also vital. k6 provides metrics for data transfer:

  • data_sent: The total number of bytes sent by k6 during the test.
  • data_received: The total number of bytes received by k6.

These metrics help analyze bandwidth consumption and identify potentially large responses.

Understanding Metric Aggregations

k6 doesn't just give raw values; it aggregates them. Common aggregations include:

  • avg (average)
  • min (minimum)
  • max (maximum)
  • p(XX) (percentile, e.g., p(90), p(95))

Percentiles are especially important as they represent the experience of a certain percentage of your users, ignoring extreme outliers.

Beyond Built-in: Custom Metrics

While k6's built-in metrics are powerful, you might need to track specific application-level events or durations. This is where custom metrics come in.

You can create your own metrics to gain deeper insights into your system's unique behavior. Common types are Counter, Gauge, Rate, and Trend.

Adding a Custom Metric

Here's how to add a Trend custom metric to measure the duration of a specific operation within your script. This helps track performance beyond just HTTP requests.

import { Trend } from 'k6/metrics';
import http from 'k6/http';
import { sleep } from 'k6';

const myCustomTrend = new Trend('custom_operation_duration');

export default function () {
  const startTime = Date.now();
  http.get('https://test.k6.io/contacts.php');
  const endTime = Date.now();
  myCustomTrend.add(endTime - startTime); // Add duration in milliseconds

  sleep(1);
}

Categorizing with k6 Tags

Tags are key-value pairs that provide metadata for your metrics. They allow you to categorize and filter your results for more granular analysis.

k6 automatically adds tags like url and status. You can also add custom tags to differentiate metrics for different parts of your application or specific user flows.

Applying Custom Tags

Custom tags are very useful for breaking down metrics. For example, you can tag requests based on the page or API endpoint they hit, allowing you to analyze performance per feature.

import http from 'k6/http';
import { sleep } from 'k6';

export default function () {
  // Tagging requests to different pages
  http.get('https://test.k6.io/', {
    tags: { page_name: 'homepage' },
  });

  http.get('https://test.k6.io/news.php', {
    tags: { page_name: 'news_page' },
  });

  sleep(1);
}

Visualizing Your k6 Metrics

While k6's console output is useful, visualizing your metrics makes analysis much easier. Tools like Grafana (often paired with InfluxDB or Prometheus) are excellent for this.

k6 can export results directly to these systems, allowing you to create dashboards that show trends, spikes, and performance regressions over time.

Metric Interpretation Challenge

Consider the k6 output snippet below:

http_req_duration{status=200, scenario=default, my_tag=checkout}......: avg=350ms min=100ms med=300ms p(90)=550ms p(95)=600ms max=1200ms

What does p(95)=600ms primarily tell you about the checkout requests?

Recap: Interpreting k6 Metrics

You've learned how to interpret k6's powerful metrics!

  • Built-in metrics like http_req_duration, vus, and data_sent/received give foundational insights.
  • Aggregations, especially percentiles, provide a realistic view of user experience.
  • Custom metrics and tags allow for deep, granular analysis of specific application behaviors.
  • Visualization tools are essential for making sense of complex test results.

Mastering metric interpretation is key to successful performance testing!

Perguntas Frequentes

A aula “Interpretando as Métricas do k6” é grátis?

Sim — o texto completo de “Interpretando as Métricas do k6” é grátis para ler aqui na web. Para praticá-la interativamente (um editor de código integrado e um tutor de IA 24/7) e desbloquear o restante do curso de Load Testing & Performance Benchmarking (JMeter & k6), atualize para CoddyKit PRO. O curso de Load Testing & Performance Benchmarking (JMeter & k6) inclui 4 aulas no total.

O que vou aprender em “Interpretando as Métricas do k6”?

Entenda as métricas detalhadas do k6, as etiquetas personalizadas e como visualizá-las para obter insights. Você pratica Load Testing & Performance Benchmarking (JMeter & k6) com código prático que executa diretamente no navegador, e um tutor de IA 24/7 responde suas dúvidas enquanto trabalha na aula.

Preciso ter experiência prévia para começar Load Testing & Performance Benchmarking (JMeter & k6)?

Nenhuma experiência prévia é necessária. Load Testing & Performance Benchmarking (JMeter & k6) no CoddyKit é estruturado para alunos iniciantes até avançados, então você pode começar aqui ou desde o início e aprender no seu ritmo. Esta é a aula 3 de 4.

Quanto tempo leva a aula “Interpretando as Métricas do k6”?

A maioria das aulas CoddyKit leva cerca de 5–10 minutos. Cada uma é compacta e interativa, então você faz progresso constante e retoma exatamente de onde parou entre web e app.

Posso escrever e executar código nesta aula de Load Testing & Performance Benchmarking (JMeter & k6)?

Sim. Cada aula de Load Testing & Performance Benchmarking (JMeter & k6) inclui um editor de código integrado, então você escreve e executa código real direto no navegador e recebe feedback de IA instantaneamente — nenhuma configuração local necessária.

Todas as aulas deste curso

  1. Ferramentas de Monitoramento no Servidor
  2. Analisando Resultados do JMeter
  3. Interpretando as Métricas do k6
  4. Correlacionando métricas para encontrar causas-raiz
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