The testing pyramid advocates for a balanced approach with many fast unit tests at the base, fewer integration tests in the middle, and a minimal set of end-to-end tests at the top to ensure reliable and efficient bug detection.
#UnitTesting #IntegrationTesting #EndToEndTesting
https://dev.to/hongster85/unit-vs-integration-vs-e2e-testing-understand-in-3-minutes-4pin
Testing #APIs ≠ mocking a class. Integration bugs hide in configs, headers, and serialization quirks. Marián Varga shows how @WireMockOrg & REST Assured make #Java integration tests real.
Learn how: https://javapro.io/2025/08/06/java-has-been-connecting-systems-and-communities-for-30-years/
One of the things a good CMake-powered C++ library should do is to test its own integration - in other words, if others can plug it into their projects. One reason is obvious - nobody will use your library if they can't. The second one is pragmatic - the tests act as documentation for the users.
I've spent many hours refining my integration testing of CMake code, and I've compiled my learnings into the following article:
➤ https://medium.com/@nerudaj/cmake-integration-testing-4d71184525ea
I've also fallen into the inevitable rabbit hole of dependency management in CMake, so if you want to learn about that, the article has you covered as well! 😵💫
What do you think? Are there other aspects of integration that are worth testing? And would you be interested in an article on how to make findable prebuilt packages with CMake?
APIs testen ≠ eine Klasse mocken. Integrationsfehler stecken in Konfiguration, Headern & Serialisierung. Marián Varga zeigt, wie @WireMockOrg & REST Assured echte Integrationstests in #Java ermöglichen.
Lese: https://javapro.io/de/java-verbindet-seit-30-jahren-systeme-und-communities/
Why Mock Databases Kill QA Confidence
TL;DR: Mock databases are great for quick unit tests, but they fail to catch the real-world issues from production environments. For reliable database testing, you need database clones that mirror your production schema, data patterns, and performance semantics. With production-grade database clones for QA and staging, you ensure that bugs are caught early, performance is realistic, and QA confidence stays high.
We’ve been there. All of us. Including me. The build is tested and signed off. […]
https://www.simplyblock.io/blog/database-testing-without-mocks/
Microservices integration testing messy? Po Linn (Fo) Chia from @Classpass shares her solution at #InfoQDevSummit Boston: ephemeral containers via CI for reliable & cost-effective testing.
🔗 Learn more: https://bit.ly/4doATkX
#Microservices #IntegrationTesting #DevEx
Integration testing a microservice architecture is a pain – uplifting the entire universe on a local machine isn’t sustainable, but running an entire staging/QA environment can be costly, especially on managed cloud infrastructure.Anyone who works in a distributed system also knows the pain of trying to write and run these tests. When you have only one development environment, tests inevitably end up flaky due to deployments not matching production. Finding enough staffing and resources to address these challenges is a challenge unto itself.
and leverage fixtures for effective testing.
Let’s enhance our testing practices together! #Dapr #Testcontainers #Pytest #IntegrationTesting
For more information check: https://devblogs.microsoft.com/ise/external-data-handling-learnings/.
This blog post discusses setting up a Pytest integration test framework for a system using Dapr and Testcontainers. This framework was initially setup for a customer to suit their needs and it has been extracted into a sample project to provide a starting point.
Nicolas Fränkel 🇪🇺🇺🇦🇬🇪
Hongster
JAVAPRO
Jakub Neruda
simplyblock
Victor Nava
James 
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Microsoft DevBlogs