Systems | Development | Analytics | API | Testing

We expect software to work. Slow mobile apps and buggy website functionality are unacceptable, given that two-thirds of us do our banking from a mobile app and a quarter of the workforce logs in from their home office. Low-quality, poorly designed software can undermine operational efficiency, create security vulnerabilities, and contribute to customer attrition.

Why should you invest in software testing? And if you’ve already invested heavily in your testing program, why should you invest in modernizing your current practices and tools? If these are questions you’ve heard or asked yourself, take a cue from your peers, Gartner, and the World Quality Report. When you modernize your testing, you make it easier for IT staff and business stakeholders to collaborate in ways that lead to faster software delivery and better business outcomes.

Today it’s not unusual to see organizations having implemented mocking in their daily workflow, as mock APIs allow developers to speed up their development and not rely on external services. For those reasons and others, many engineers are looking to learn more about the mocked APIs and how they can best be implemented into their organization.

Automating your test suite helps get your code to production faster. In this tutorial, you'll learn how to write unit tests for Django and run them with GitHub Actions.

In an ideal world, you want to have precisely the capacity to manage the requests of your users, from peak periods to off-peak hours. If you need three servers to attend to all the requests at peak periods and just one server at off-peak hours, running three servers all the time is going to drive up expenses, and running just one server all the time is going to mean that during peak periods, your systems will be overwhelmed and some clients will be denied service.

One morning, you realize you have a great idea for an API. You discuss it with your team, then start building out the business case and technical requirements. Where do you go from there? You could write out the business requirements for the API and then code it. Or you could describe your API in a specification language, like OpenAPI, and use that definition to improve your team's understanding of the API and do some early testing. But are either of these the best solution?

With the introduction of new application platforms like Kubernetes, oftentimes the DevOps tooling around it needs to evolve. Cloud Native technology is powerful but complex. This 5 minute demo video shows how Speedscale provides production simulation capabilities so you can check for resiliency, quality and scalability in your Kubernetes clusters. You can record data and traffic in production and replay sanitized traffic on the fly against a new cluster.