20 minutes readKey takeaways Testing services individually misses the failures that appear when they call each other. Include service discovery, retries and timeouts in the test; they cause cascading failure. Trace across services or you will find the symptom rather than the source. Dispelling Myths: What Microservices Load Testing Really Requires Microservices Load Testing: Beyond Monolithic Assumptions… Read more »
18 minutes readKey takeaways OAuth2 makes load testing harder because tokens expire mid-test and refresh adds its own latency. Acquire tokens outside the measured path, then measure the API rather than the auth server. Model token lifetime deliberately. A test that never refreshes is not testing production. Clearing Up Misconceptions: What API Performance Testing Really Means Functional… Read more »
12 minutes readKey takeaways AI is moving performance testing from scripted runs to continuous analysis of production-like behaviour. The gain is in triage: finding which change caused a regression, not just that one exists. Tooling has converged enough that the differentiator is workflow fit rather than raw capability. AI Performance Testing in 2026: Why This Year Marks… Read more »
16 minutes readKey takeaways Most API performance problems are not the API: they are authentication, data setup and rate limits. Test with realistic payloads and realistic concurrency, or the numbers describe a system you do not run. Fix the challenge that blocks releases first. The exhaustive list is less useful than the ranked one. Filtering the Signal:… Read more »
17 minutes readKey takeaways The common mistakes are testing too late, testing an unrepresentative environment, and measuring averages. Unrealistic data is the quiet one: it makes everything look faster than production. Decide pass criteria before the run, or you will interpret the result to suit the deadline. Are You Falling for These Performance Testing Mistakes? Here’s How… Read more »
15 minutes readKey takeaways A benchmark is only useful against a stated target, not as an isolated number. Set targets from user expectation and competitor reality rather than current performance. Re-benchmark on a schedule, since dependencies drift even when your code does not. Why Most Web Applications Fall Short on Performance Benchmarks When web applications miss the… Read more »
9 minutes readKey takeaways Monitor from outside Azure as well as inside, or you miss what customers experience. Alert on latency percentiles and error rate, not on average response time. Watch platform limits alongside app metrics, since quotas throttle before the code fails. APIs are the backbone of many modern applications, enabling them to interact seamlessly with… Read more »
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