![]() ![]() Load testing is simply a technique for understanding your system better, causing it to exhibit issues in misconfiguration, architectural assumptions, and resource constraints. One of those is load testing distributed systems before (and after) deployment. Unless you want to continuously deliver disappointing software that causes more trouble than it’s worth in production, consider that there are many tools/techniques that the past 70 years of software engineering have already produced to prevent this unfortunate future. What does load testing have to do with continuous delivery? The feedback is vital, but the cost of gathering it used to be too high to fit into high-velocity software delivery. Testing is just a tactic, and the more critical focus needs be on where/when/which feedback loops should be in place (within the context of automated pipelines at least).Ĭonsider load testing, a mechanism to verify the scalability and performance of distributed software systems, which used to require time, expertise, and often always-on infrastructure. “How do you test all the things all the time” is a classic (albeit early) question people ask. Part 3: Accelerating performance analysis with trends and open API dataĪs organizations become more automated in their approach to software delivery, many teams struggle to fit traditional feedback loops into their continuous delivery lifecycles. Part 2: 3 Killer anti-patterns in continuous performance testing Part 1: Continuous Load Testing using Jenkins Pipelines and Kubernetes ![]() This article is the first in a multi-part series on how to enable performance testing to fit into continuous and automated pipelines seamlessly. ![]()
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