Systems | Development | Analytics | API | Testing

At some point, your development team may be considering implementing load testing (also known as stress testing) as part of your software testing process. Load testing validates that your web app is able to withstand a large number of simultaneous users, decreasing the chance that any traffic spikes will bring down your services once deployed. These stress tests can be highly granular, giving you the opportunity to test run virtually unlimited strategies before they are set into the wild.

Transactions-per-Second (TPS) is a valuable metric for evaluating system performance and is particularly relevant for engineers overseeing Kubernetes environments.TPS, alongside average response time, provides critical insights into system performance during load testing. This post covers two approaches to calculating TPS; a manual approach applicable in all environments, and an automatic Kubernetes-specific solution using production traffic replication.

As developers, one of the most important things we can consider when designing and building applications is the ability to know if our application is running in an ideal operating condition, or said another way: the ability to know whether or not your application is healthy. This is particularly important when deploying your application to Kubernetes. Kubernetes has the concept of container probes that, when used, can help ensure the health and availability of your application.

With the rise in popularity of embedded integrations, and continued trial and error in this space, it’s best to review the core concepts of how embed frameworks operate. There are many ways platforms open their UI to third-parties, but one is considered original - the oldest, and likely still the most common method on the web - the old iframe model. In the olden days, the common way to enable third-party content in one’s interface was by iframing.

As businesses continue to digitize, the importance of load testing has surged, with the market witnessing a significant rise in the adoption of load testing tools. According to a recent report, the global load testing market is expected to grow at a CAGR of 12.5% from 2021 to 2026, reflecting the increasing demand for reliable and scalable applications.

What do good tests look like, and do you even need a Golang testing framework? It’s a loaded question with an open answer. Not only do tests help ensure that your code will work as intended, but good tests can also serve as documentation for your codebase, making it easier to update and maintain in the future, while accelerating and streamlining your software development process. In this article, we outline 6 Golang testing frameworks for every type of test.

Developing highly resilient Kubernetes deployments is crucial for ensuring that your hosted applications in Kubernetes can effectively manage and recover from disruptions. This capability is vital in order to maintain continuous availability for your customers. The importance of resilience in your distributed system also escalates depending on your customer base and the critical nature of your application. Even brief periods of downtime can have a significant negative impact on your business.

Today we're excited to introduce SCIM (System for Cross-domain Identity Management) support in Kong Insomnia to automatically provision and deprovision user accounts using a third-party IDP. This capability will enormously simplify the process of onboarding enterprise users into Insomnia, and it's available today for every Enterprise plan customer.

Service virtualization, which gained prominence in 2012, has significantly transformed the way software testing and development are approached. Originally designed to address limited access to dependent systems during development, service virtualization has evolved into a critical technology for enabling efficient and continuous testing. This blog explores its origins, key advancements over the past decade, ongoing challenges, and how API simulation is shaping the future of testing.

All but the simplest applications borrow code. You could write everything yourself from just core language features but who has time for that? Instead you take on dependencies, pieces of code written by others that usually give us 80% or more of what we need with 20% of the effort. Sometimes these dependencies are made to interact with a specific technology like a database, or perhaps it’s just a library providing some feature that would be onerous to write yourself.