Application programming interfaces (APIs) have quickly become vital to modern businesses. APIs work by allowing different systems to talk to each other and share data. The commercial use of APIs and web APIs has skyrocketed over the last decades in accordance with the rise in app development, mobile apps, and e-commerce. However, how do you estimate API development time? Well, API creation and the development time frame will always vary from project to project.

If you'd like to run load tests in a simple way, and possibly share them, while benefiting from a simplified configuration, with a focus on writing your test plan, and its test typology, this article is for you! Docker offers virtualization services that simplify the replication of working environments. Furthermore, each virtualized service is isolated from unrelated services on other containers or the host machine, ensuring portability across host machines and the network.

Let’s pose a hypothetical scenario. You're the API product owner at the Paris, Texas Regional Airport. You're in charge of two main APIs: Flights API and Scheduling API. Flights API is primarily used by local research institutions that are interested in read-only access to information about departures and arrivals. Scheduling API is primarily used by airline partners who are interested in updating information about their flights and gates.

The Ably service handles massive amounts of data throughput and concurrent connections for many customers while maintaining a highly reliable and available service, with a 5x9s uptime guarantee. Ably has no scale ceiling, and that’s challenging work (it’s one of the reasons I joined Ably). While the challenges we face in delivering our service are compelling, we sometimes face novel internet scale problems, such as breaching the limits of AWS services!

The java.lang.IndexOutOfBoundsException in Java is thrown when an index used in arrays, lists, or strings is not valid. A valid index must be a number from 0 up to one less than the total number of items. For example, in a list of 3 items, the valid indices are 0, 1, and 2. Here’s a quick example: The error message you’d get would look something like this: Here are some other common ways the IndexOutOfBoundsException might be thrown.

Not long ago, I was handed a problem that’s no stranger to the world of programming: making asynchronous threads communicate effectively within the same process. Given the widespread nature of this issue, I expected to find an existing solution to resolve it. My search led me to the concept of message queue, which seemed promising for streamlining this communication challenge.

An API (Application Programming Interface) is a set of rules and protocols that let software programs communicate with each other. It acts as an intermediary between different software or services. For example, when using a mobile app to book a hotel room, the API allows the app to communicate with the hotel’s booking system. While many REST API developers have their way of doing things, some factors in API development are generally considered essential.

In this blog post we are going to look at how we take a postman request or collection and translate these into JMeter tests. When web services are being build it is common for Postman to be used to test the endpoints. This is done by: the list goes on. What naturally happens during programmes where web services are part of the design is that postman requests and collections are built and grow to support all manner of requirements.

Data integrity refers to protecting data from anything that can harm or corrupt it, whereas data quality checks if the data is helpful for its intended purpose. Data quality is a subset of data integrity. One can have accurate, consistent, and error-free data, but it is only helpful once we have the supporting information for this data. Data integrity and quality are sometimes used interchangeably in data management, but they have different implications and distinct roles in enhancing data usability.

Is exploratory testing a solo practice? Is only the QA team responsible for quality? Are the great insights of an exploratory session shared with the team? We’ve been asking ourselves and our users these questions and we’re happy to launch version 3 of the Xray Exploratory App, designed to establish the foundations of collaboration in exploratory testing.