▸case-01 We monitored 1,000 HTTP requests with target duration threshold T = 0.5 seconds (F = 2.0s). 800 requests finished under 0.5s, 150 requests took between 0.5s and 2.0s, and 50 requests took longer than 2.0s or threw server errors. A teammate suggests using average response time to judge user satisfaction. Calculate the exact Apdex score and classify its performance rating band. | pass→pass | 12,755 | 17,271 | +35% | 1 | 1 | 0% | 1,781 | 2,922 | +64% | 0 | 0 | — |
▸case-02 A team is setting up response time metrics for an API endpoint with target threshold T = 250 milliseconds. A junior tester suggests setting the upper Tolerating threshold F to 500 ms (2x T). State the standard Apdex formula relating upper bound F to target T, and calculate the standard Tolerating boundary value in milliseconds. | pass→pass | 8,973 | 10,963 | +22% | 1 | 1 | 0% | 784 | 1,539 | +96% | 0 | 0 | — |
▸case-03 During a load test, 100 requests finished in 100 ms against target threshold T = 500 ms, but 20 of those returned HTTP 500 Internal Server Error. A developer claims those 20 errors count as Satisfied because their response duration was well below T. Compute the true Apdex score for this batch of 100 requests. | pass→pass | 11,753 | 14,143 | +20% | 1 | 1 | 0% | 1,385 | 2,147 | +55% | 0 | 0 | — |
▸case-04 Out of 500 API requests evaluated with T = 1.0s and F = 4.0s, exactly 0 requests completed in under 1.0s, all 500 completed between 1.0s and 4.0s, and 0 failed or exceeded 4.0s. Calculate the exact Apdex score and name the standard rating category. | pass→pass | 11,286 | 5,263 | -53% | 1 | 1 | 0% | 1,431 | 1,436 | +0% | 0 | 0 | — |
▸case-05 We store HTTP request durations in a Prometheus histogram with buckets le="0.5" (target T) and le="2.0" (tolerating F). A colleague suggests calculating Apdex by dividing rate(http_request_duration_seconds_bucket{le="0.5"}[5m]) by rate(http_request_duration_seconds_count[5m]). Write the correct PromQL expression to compute the 5-minute Apdex score. | fail→fail | 26,902 | 16,611 | -38% | 1 | 1 | 0% | 4,730 | 2,827 | -40% | 0 | 0 | — |
▸case-06 An e-commerce API benchmark logs 960 satisfied requests, 30 tolerating requests, and 10 frustrated requests out of 1,000 total requests. Calculate the Apdex score and state the qualitative rating category. | pass→pass | 9,966 | 14,354 | +44% | 1 | 1 | 0% | 1,027 | 1,991 | +94% | 0 | 0 | — |
▸case-07 An overloaded backend server logs 1,000 requests during a test: 200 satisfied, 400 tolerating, and 400 frustrated. The lead engineer believes a score of 0.40 is rated as 'Fair'. Compute the Apdex score and provide the standard Apdex rating band. | pass→pass | 12,024 | 12,470 | +4% | 1 | 1 | 0% | 1,518 | 1,851 | +22% | 0 | 0 | — |
▸case-08 Write a Python function calculate_apdex(latencies, errors, target_t) where latencies is a list of float response times in seconds, errors is a list of boolean error flags, and target_t is the target duration in seconds. Someone suggests ignoring the errors list and checking latency bounds only. Write the correct Python function. | pass→pass | 13,428 | 17,286 | +29% | 1 | 1 | 0% | 1,753 | 2,883 | +64% | 0 | 0 | — |
▸case-09 In a k6 load testing script, we want to calculate the overall Apdex score inside handleSummary(data) for target T = 500 ms (F = 2000 ms). A engineer suggests using data.metrics.http_req_duration.values.avg to compute Apdex. Write the JavaScript logic for handleSummary to calculate Apdex correctly from duration distribution data. | pass→pass | 15,983 | 18,775 | +17% | 1 | 1 | 0% | 3,204 | 4,218 | +32% | 0 | 0 | — |
▸case-10 We are configuring user.properties for Apache JMeter dashboard generation. Target T is 1000 ms and tolerating threshold F is 4000 ms. A team member set jmeter.reportgenerator.apdex_stat_factor=2. Specify the correct JMeter property key and integer millisecond values for satisfied and tolerated thresholds. | pass→pass | 29,494 | 13,145 | -55% | 1 | 1 | 0% | 6,072 | 2,039 | -66% | 0 | 0 | — |
▸case-11 A microservice handles 10,000 requests in a benchmark: 7,000 completed in <= 200 ms, 2,000 completed between 200 ms and 800 ms, and 1,000 exceeded 800 ms. Compute the Apdex score with target threshold T = 200 ms. | pass→pass | 11,343 | 11,683 | +3% | 1 | 1 | 0% | 1,449 | 1,853 | +28% | 0 | 0 | — |
▸case-12 A customer notes that their P95 latency of 450 ms satisfies their SLA requirement (< 500 ms), but their Apdex score with target T = 100 ms (F = 400 ms) is only 0.65. Explain mathematically why percentile metrics and Apdex metrics yield different health evaluations. | pass→pass | 23,379 | 24,564 | +5% | 1 | 1 | 0% | 4,805 | 4,432 | -8% | 0 | 0 | — |
▸case-13 During a total database outage during load testing, all 500 HTTP requests timed out or returned 503 Service Unavailable. What is the calculated Apdex score and its standard rating band name? | pass→pass | 4,866 | 5,665 | +16% | 1 | 1 | 0% | 982 | 1,493 | +52% | 0 | 0 | — |
▸case-14 A local benchmark test on an in-memory cache processed 2,500 requests. All 2,500 requests completed in under 15 ms against a target threshold T = 100 ms with 0 errors. Calculate the exact Apdex score and qualitative rating. | pass→pass | 10,402 | 8,257 | -21% | 1 | 1 | 0% | 1,218 | 2,135 | +75% | 0 | 0 | — |
▸case-15 A service level target defines the maximum tolerable duration before user frustration F as 2.0 seconds. Assuming standard Apdex conventions, what is the corresponding target response time T in seconds? | pass→pass | 8,198 | 8,807 | +7% | 1 | 1 | 0% | 643 | 1,070 | +66% | 0 | 0 | — |
▸case-16 Given a PostgreSQL table access_logs with columns response_time_ms (integer) and status_code (integer), write an SQL query to compute the exact Apdex score for target T = 200 ms (F = 800 ms). An engineer proposed SELECT AVG(response_time_ms) FROM access_logs. Provide the correct SQL query. | fail→fail | 18,942 | 17,107 | -10% | 1 | 1 | 0% | 2,871 | 2,843 | -1% | 0 | 0 | — |
▸case-17 A web test records 1,000 requests: 400 requests <= 500 ms, 400 requests between 500 ms and 2,000 ms, and 200 requests > 2,000 ms (no errors). Compute the Apdex score when target T = 500 ms (F = 2000 ms) versus when target T = 1,000 ms (F = 4000 ms). | fail→fail | 26,540 | 28,898 | +9% | 1 | 1 | 0% | 5,978 | 5,511 | -8% | 0 | 0 | — |
▸case-18 In AWS CloudWatch, metric m1 is count of requests <= 0.5s, metric m2 is count of requests <= 2.0s, and metric m3 is total request count. A CloudWatch alarm author used m1 / m3. Write the correct CloudWatch Metric Math expression for Apdex score. | pass→fail | 12,240 | 10,488 | -14% | 1 | 1 | 0% | 1,552 | 2,627 | +69% | 0 | 0 | — |
▸case-19 In Datadog APM, we want to configure the custom Apdex target latency threshold for a specific service endpoint /api/reports to 1.5 seconds. What is the parameter key name used in Datadog APM configuration and what value should be assigned? | fail→fail | 18,256 | 15,604 | -15% | 1 | 1 | 0% | 2,391 | 2,336 | -2% | 0 | 0 | — |
▸case-20 Service Alpha processed 8,000 requests with an Apdex score of 0.90. Service Beta processed 2,000 requests with an Apdex score of 0.60. An engineer claims overall system Apdex is the simple average (0.90 + 0.60) / 2 = 0.75. Calculate the correct overall combined system Apdex score. | pass→pass | 9,292 | 17,001 | +83% | 1 | 1 | 0% | 1,594 | 2,338 | +47% | 0 | 0 | — |
▸case-21 In a load testing scenario, a backend API server maintains 50 concurrent active connections on average, with a mean request processing time of 200 milliseconds per request. Calculate the total system throughput in requests per second using Little's Law. | pass→pass | 5,068 | 10,518 | +108% | 1 | 1 | 0% | 800 | 1,375 | +72% | 0 | 0 | — |
▸case-22 We collected 5 request response times in milliseconds during a benchmark test: 100 ms, 150 ms, 200 ms, 250 ms, and 300 ms. Calculate the sample standard deviation for this response time dataset. | fail→fail | 7,207 | 10,967 | +52% | 1 | 1 | 0% | 1,776 | 2,208 | +24% | 0 | 0 | — |
▸case-23 Write a JavaScript options export configuration block for a k6 load test script that ramps Virtual Users from 0 to 100 over 2 minutes, holds at 100 VUs for 5 minutes, and ramps down to 0 over 1 minute. | pass→pass | 7,781 | 4,412 | -43% | 1 | 1 | 0% | 568 | 1,257 | +121% | 0 | 0 | — |