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The latest News and Information on Software Testing and related technologies.

How to Unit Test with Python

Confidence in the quality, robustness, and reliability of a product are among the most valuable qualities sought after by consumers as well as businesses. This confidence is built through the rigorous testing of a product. In software engineering, practices like extreme programming (XP) and test-driven development (TDD) champion the belief that automated testing should be used from the start of a project.

API Testing vs Monitoring: What's The Difference?

We’ve already outlined why API performance matters and what aspects of APIs to test, but what is the difference between API testing and monitoring? As with most things, context matters. The use cases for testing and monitoring are different because the objectives are different. The ultimate goal is to verify that your APIs are functioning properly, but staging environments vary significantly from production environments.

Build a Cypress tests infrastructure for serverless applications

When a startup is in its very early stages, rapid iteration and dynamism are at the top of its priorities. The ability to do so, while maintaining a stable and high-quality product, is a big challenge facing the R&D group. We want to release features as quickly as possible, but this rapid velocity cane cause conflicts when writing in-depth, comprehensive tests.

How We Run Successful Beta Tests with Error Reporting

We’ve recently completed a large beta test for our new product here at Testmo. We build a test management tool, so most of our users are professional software testers. As you can imagine, our customers are a rather critical group of users when it comes to software quality. We’ve learned some important lessons about running a large beta test and we want to share how we benefited from Sentry error reporting to identify, find, and fix issues quickly.

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Kubernetes Load Test Tutorial

In this blog post we use podtato-head to demonstrate how to load test kubernetes microservices and how Speedscale can help understand the relationships between them. No, that's not a typo, podtato-head is an example microservices app from the CNCF Technical Advisory Group for Application Delivery, along with instructions on how to deploy it in numerous different ways. There are more than 10 delivery examples, you will surely learn something by going through the project. We liked it so much we forked the repo to contribute our improvements.

API Testing: An Introduction

Digital businesses are making a radical change in the way they build and deliver software. Gone are the days of apps that rely solely on in-house tools. Rather, today’s apps are increasingly dependent on external APIs and third-party app providers (which, in turn, are reliant on other APIs and apps). While this type of modularity allows for product flexibility and rapid development, it can be difficult to address any issues that arise.

Postman Load Test Tutorial

In this load test tutorial, you’ll learn how to use Postman for small-scale API testing. You’ll also learn about some shortcomings and challenges of the framework that can be solved by using a tool like Speedscale. Because HTTP services don’t have a graphical user interface, you’re forced to test web APIs by simulating requests from a known client so that you can control the traffic data.

What is end-to-end testing?

End-to-end testing, also known as E2E testing, is a methodology used for ensuring that applications behave as expected and that the flow of data is maintained for all kinds of user tasks and processes. This type of testing approach starts from the end user’s perspective and simulates a real-world scenario. For example, on a sign-up form, you can expect a user to perform one or more of these actions: You can use end-to-end testing to verify that all these actions work as a user might expect.

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Who Can Benefit From Kafka Monitoring Services?

The benefits of Apache Kafka monitoring services are widely appreciated across the industry. Organizations that rely heavily on Apache Kafka for their data streaming needs can derive great benefit from the use of Kafka monitoring services. By keeping track of various different key performance indicators (KPIs) related to Kafka, such as message throughput and latency, organizations can ensure that their Kafka-based data pipelines are running as smoothly and efficiently as possible.