Calculate Application Performance Index (APDEX) scores with satisfaction thresholds. Part of the DevTools Surf developer suite. Browse more tools in the Developer Utilities collection.
Use Cases
Track user satisfaction across API endpoints after a performance regression
Set SLO targets in terms of Apdex score rather than raw latency percentiles
Compare performance of microservices using a single normalized metric
Report performance to non-technical stakeholders using a 0-1 score
Tips
Set T (the satisfied threshold) to your 95th percentile response time target, not the average — Apdex rewards fast performance, not just acceptable
Input raw response time samples; the tool bins them into satisfied (<T), tolerating (T-4T), and frustrated (>4T) buckets automatically
Compare Apdex scores before and after deployments to quantify user experience impact objectively
Fun Facts
APDEX (Application Performance Index) was defined by an industry consortium in 2007. The formula is (Satisfied + 0.5 * Tolerating) / Total — producing a score from 0 to 1.
An Apdex score of 0.94 is considered 'excellent'. Scores below 0.85 indicate users are noticeably experiencing degraded performance and churn risk increases.
Apdex was designed partly because raw latency averages are misleading: a system where 95% of requests take 100ms and 5% take 10 seconds has a good average but terrible user experience.
FAQ
What T value should I use?
T is application-specific. A common starting point is 500ms for web pages and 100ms for API calls. Set T based on user research or your SLA targets, not industry averages.
Is Apdex better than p95 latency?
They answer different questions. p95 tells you the worst-case experience for the 95th percentile user. Apdex summarizes the distribution of experiences across all users into a single satisfaction score. Use both.
What Apdex score is acceptable?
0.94+ is excellent; 0.85-0.93 is good; 0.70-0.84 is fair (users notice); below 0.70 is poor — at this level, performance is likely causing measurable abandonment.
