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

Menafsirkan Metrik k6

Pahami metrik terperinci k6, tag khusus, dan cara memvisualisasikannya untuk memperoleh wawasan.

Menafsirkan Metrik k6 adalah pelajaran Load Testing & Performance Benchmarking (JMeter & k6) gratis di CoddyKit. Ini adalah pelajaran 3 dari 4. Kamu bisa membaca pelajaran lengkapnya di bawah secara gratis — lalu praktikkan langsung di browser dengan editor kode bawaan dan tutor AI 24/7. Ini adalah bagian dari jalur belajar Load Testing & Performance Benchmarking (JMeter & k6), dan progresmu tersinkronisasi di web dan aplikasi CoddyKit. Kursus Load Testing & Performance Benchmarking (JMeter & k6) mencakup 4 pelajaran total.

Bagian dari pelajaran ini belum diterjemahkan dan ditampilkan dalam bahasa Inggris.

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!

Pertanyaan yang Sering Diajukan

Apakah pelajaran “Menafsirkan Metrik k6” gratis?

Ya — teks lengkap “Menafsirkan Metrik k6” gratis dibaca di sini di web. Untuk praktiknya secara interaktif (editor kode bawaan dan tutor AI 24/7) dan buka sisa kursus Load Testing & Performance Benchmarking (JMeter & k6), upgrade ke CoddyKit PRO. Kursus Load Testing & Performance Benchmarking (JMeter & k6) mencakup 4 pelajaran total.

Apa yang akan aku pelajari di “Menafsirkan Metrik k6”?

Pahami metrik terperinci k6, tag khusus, dan cara memvisualisasikannya untuk memperoleh wawasan. Kamu berlatih Load Testing & Performance Benchmarking (JMeter & k6) dengan kode praktik yang langsung kamu jalankan di browser, dan tutor AI 24/7 menjawab pertanyaanmu saat kamu mengerjakan pelajaran ini.

Apakah aku perlu pengalaman untuk memulai Load Testing & Performance Benchmarking (JMeter & k6)?

Tidak diperlukan pengalaman sebelumnya. Load Testing & Performance Benchmarking (JMeter & k6) di CoddyKit dirancang untuk pemula hingga pelajar tingkat lanjut, jadi kamu bisa memulai di sini atau dari awal dan belajar sesuai kecepatan kamu sendiri. Ini adalah pelajaran 3 dari 4.

Berapa lama pelajaran “Menafsirkan Metrik k6” memakan waktu?

Sebagian besar pelajaran CoddyKit memakan waktu sekitar 5–10 menit. Setiap pelajaran ringkas dan interaktif, jadi kamu membuat kemajuan stabil dan melanjutkan dari tempat kamu tinggalkan di web dan aplikasi.

Bisakah aku menulis dan menjalankan kode dalam pelajaran Load Testing & Performance Benchmarking (JMeter & k6) ini?

Ya. Setiap pelajaran Load Testing & Performance Benchmarking (JMeter & k6) menyertakan editor kode bawaan, jadi kamu menulis dan menjalankan kode nyata langsung di browser dan mendapatkan umpan balik AI instan — tidak diperlukan penyiapan lokal.

Semua pelajaran dalam kursus ini

  1. Alat Pemantauan Sisi Server
  2. Menganalisis Hasil JMeter
  3. Menafsirkan Metrik k6
  4. Mengorelasikan Metrik untuk Menemukan Akar Masalah
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