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Functional unit and integration tests are a standard tool of any software development organization, helping not only to ensure correctness of newly implemented code, but also to identify regressions — bugs in existing functionality introduced by a code change. The situation looks different though when it comes to regressions related to non-functional requirements, in particular performance-related ones: How to detect increased response times in a web application?

Assuming you have correctly configured the user ids for MFA authentication in Salesforce, end-users should see the following screen when trying to login into the CRM application. The TOTP-based verification code is generated in third-party authenticator apps (Google or Microsoft) on your mobile device when you first scan the QR code or enter the key manually in the app. In this article, we’ll guide you through all the steps you need to set up our Salesforce MFA Web Sensor in your environment.

Why this combination you ask? Load testing is my passion, and I am partial to Kubernetes. I challenged myself to share a use case that many could relate to, focused on a business critical application. Websites came to mind and WordPress is the world’s most popular website management system. Of course, nginx is the most popular web server so let’s throw that into the mix. And Kubernetes? With more than 50% of corporations adopting Kubernetes in 2021, what better system to run in.

While Go provides a testing package and a go test command, the former only offers basic testing capabilities. The package also has some drawbacks, such as missing assertions and increasing repetition with large-scale tests. As a result, several Go testing frameworks have been created to augment it. Go testing frameworks consist of tools and resources for creating and designing tests. Some of these frameworks incorporate the testing package and go test command, while others take a different approach.

In my prior blog, Continuous Test Data Management for Microservices, Part 1, we offered an introduction to the key approaches for applying continuous test data management (TDM) to microservices. The continuous TDM process for microservices applications is similar to that for general continuous TDM (see figure below), but tailored to the nuances of the architecture. In this post, I’ll outline the key steps for applying TDM across the lifecycle.

In today’s blog post, I want to present something related to Icinga DB that you most likely will not come in touch with as a regular user: some of the test cases we built for Icinga DB and the tooling created to support them.