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Load Testing & Performance Benchmarking (JMeter & k6) · レッスン

JMeterの結果分析

JMeterの集計レポート、グラフ、ログを読み解き、パフォーマンス上の問題を特定します。

「JMeterの結果分析」はCoddyKit上の無料Load Testing & Performance Benchmarking (JMeter & k6)レッスンです。 これはレッスン2/4です。 下記で完全なレッスンを無料で読むことができます。その後、ブラウザ内の組み込みコードエディタと24時間対応のAIチューターでハンズオン演習できます。 これはLoad Testing & Performance Benchmarking (JMeter & k6)学習パスの一部であり、ウェブとCoddyKitアプリ全体で進捗が同期されます。 Load Testing & Performance Benchmarking (JMeter & k6)コースには全4レッスンが含まれています。

このレッスンの一部はまだ翻訳されておらず、英語で表示されています。

Why Analyze JMeter Results?

Running a performance test is just the first step! The real value comes from analyzing the results to understand your system's behavior under load.

Without proper analysis, you can't identify bottlenecks, validate performance goals, or make informed decisions about system improvements.

Key JMeter Listeners for Analysis

JMeter provides various Listeners to visualize and interpret test results. For effective analysis, you'll primarily use:

  • Aggregate Report: For summary statistics.
  • Graph Results: For visual trends over time.
  • View Results Tree: For detailed request/response data.

These listeners help you understand how your application performed during the test.

Understanding the Aggregate Report

The Aggregate Report is a powerful summary table, often the first place to look. It provides key metrics for each request (sampler) in your test plan.

To add it, right-click on your Thread Group > Add > Listener > Aggregate Report.

It presents data in a table, making it easy to compare performance across different transactions.

Aggregate Report: Response Time Metrics

Focus on these columns in the Aggregate Report:

  • Average: The mean response time for all samples.
  • Median: The middle response time (50% of samples are faster, 50% are slower).
  • 90% Line (or 90th Percentile): 90% of samples completed within this time. This is a common SLA metric.
  • 95% Line & 99% Line: Similar, but for 95% and 99% of samples. These highlight outliers.

High percentile values often indicate performance bottlenecks affecting a subset of users.

Aggregate Report: Throughput & Errors

Other critical metrics in the Aggregate Report include:

  • Throughput: The number of requests per second (or minute/hour) that the server handled. Higher is generally better, indicating system capacity.
  • Error %: The percentage of requests that failed. Any error rate above 0% usually warrants investigation.
  • Sent/Received KBytes/sec: Data transfer rates, useful for network performance analysis.

A sudden drop in Throughput or a spike in Error % under load are clear signs of trouble.

Visualizing with Graph Results

While reports give numbers, graphs show trends! The Graph Results listener visualizes metrics like response time over the duration of your test.

To add it, right-click on your Thread Group > Add > Listener > Graph Results.

This helps you spot performance degradation or improvements as the test progresses or as load increases.

Interpreting Response Time Graphs

When viewing a response time graph:

  • Rising trend: Indicates performance degrades with time or increasing load.
  • Spikes: Could be garbage collection, database locks, or other temporary issues.
  • Plateaus: Might suggest a resource ceiling (e.g., CPU, memory, database connections).
  • Fluctuations: Normal variations, but large swings need attention.

Look for correlation between user load and response time changes.

Detailed Inspection: View Results Tree

The View Results Tree listener lets you inspect individual requests and their responses in detail. It's invaluable for debugging failed requests.

For each sample, you can see:

  • Request details (headers, body)
  • Response data (headers, body)
  • Response time, latency, and status codes

Use this to understand why a request failed or returned an unexpected response.

Identifying Performance Bottlenecks

Combining insights from these listeners helps pinpoint bottlenecks:

  • High Response Times + Low Throughput: Server struggling to process requests.
  • High Error %: Server or application errors, often visible in View Results Tree.
  • Spikes in Graph Results: Correlate with server-side monitoring to find resource contention (CPU, memory, database).

Look for patterns and specific samplers that consistently underperform.

Checking JMeter Log Files

Don't forget the jmeter.log file! This file, usually found in JMeter's bin directory, records internal JMeter events and errors during test execution.

It's crucial for debugging issues with your test script itself, such as configuration problems, missing files, or syntax errors in functions.

Always check the log if your test isn't running as expected, even if the application under test seems fine.

Quick Check on Metrics

You've run a JMeter test and observe that the 90% Line for a critical transaction is significantly higher than the Average response time. What does this likely indicate?

Recap: Analyzing JMeter Results

In this lesson, we explored how to interpret JMeter test results using key listeners:

  • The Aggregate Report provides summary statistics like Average, Percentiles, Throughput, and Error %.
  • Graph Results visualize performance trends over time, helping spot degradation or spikes.
  • The View Results Tree allows for detailed inspection of individual requests and responses.
  • Don't forget jmeter.log for debugging the test itself!

Effective analysis is key to identifying bottlenecks and ensuring your application meets performance standards.

よくある質問

「JMeterの結果分析」レッスンは無料ですか?

はい。「JMeterの結果分析」の完全なテキストはこのウェブで無料で読めます。インタラクティブに演習し(組み込みコードエディタと24時間対応のAIチューター)、Load Testing & Performance Benchmarking (JMeter & k6)コースの残りをアンロックするには、CoddyKit PROにアップグレードしてください。 Load Testing & Performance Benchmarking (JMeter & k6)コースには全4レッスンが含まれています。

「JMeterの結果分析」で何を学びますか?

JMeterの集計レポート、グラフ、ログを読み解き、パフォーマンス上の問題を特定します。 ブラウザで直接実行するハンズオンコードでLoad Testing & Performance Benchmarking (JMeter & k6)を演習し、24時間対応のAIチューターがレッスンを進める中での質問に答えます。

Load Testing & Performance Benchmarking (JMeter & k6)を始めるのに経験は必要ですか?

事前経験は必要ありません。CoddyKitのLoad Testing & Performance Benchmarking (JMeter & k6)は初級者から上級者向けに構成されているため、ここから始めるか最初から始めて、自分のペースで進むことができます。 これはレッスン2/4です。

「JMeterの結果分析」レッスンにはどのくらい時間がかかりますか?

ほとんどのCoddyKitレッスンは約5~10分かかります。各レッスンはコンパクトでインタラクティブなので、着実に進歩し、ウェブとアプリ全体で正確に前回の場所から再開できます。

このLoad Testing & Performance Benchmarking (JMeter & k6)レッスンでコードを書いて実行できますか?

はい。すべてのLoad Testing & Performance Benchmarking (JMeter & k6)レッスンに組み込みコードエディタが含まれているため、ブラウザでリアルコードを書いて実行し、即座のAIフィードバックを取得できます。ローカル設定は不要です。

このコースのすべてのレッスン

  1. サーバーサイドの監視ツール
  2. JMeterの結果分析
  3. k6メトリクスの読み解き方
  4. メトリクスの相関分析による根本原因の特定
← Load Testing & Performance Benchmarking (JMeter & k6)に戻る