Pricing APIs correctly is a key part of your API monetization strategy. That means understanding how you should charge for usage, whether it’s better to set your pricing by month or quarter, whether data tiers or a Pay As You Go API pricing model would work best and a whole host of other elements. In this post we’ll cover all you need to know when pricing APIs.
A key part of business is the drive for continual improvement, to always do better. “Better” can mean different things to different organizations. It could be about offering better products, better services, or the same product or service for a better price or any number of things. Fundamentally, to be “better” requires ongoing analysis of the current state and comparison to the previous or next one. It sounds straightforward: you just need data and the means to analyze it.
When I first started my role as an analytics engineer, I was tasked with rewriting a bunch of data models that were written in the past by contractors. These models were taking over 24 hours to run and often failed to run at all. They were poorly thought out and contained a bunch of “quick fix” code rather than being designed with the entire flow of the model in mind.
In the growing digital landscape, it’s a significant challenge to meet and cope with customer expectations, changing trends, use of technology, and expand the user base for digital applications. Many applications today fail to realize their full potential because they do not consider the complete end-user requirements during the design and development phase. It requires an exceptional effort to create and develop new technology accessible to all users.
In a world where technological advances are made on a daily basis, software products are often affected by routine updates. While updating software is necessary for all businesses, it can introduce a slew of bugs into applications and websites. If these software bugs are not thoroughly tested, validated, and fixed, they could end up costing the company a lot of money in production. User interface (UI) and visual bugs in software products are often disregarded due to the focus on functional testing.
Have you developed a vision for modernizing your testing? Now it’s time to make that vision a reality. When you set out to transform your testing practice, don’t just aim to improve a few processes—instead, strive to make sweeping changes in the culture and activities of your testing organization. By definition, a transformation should entail major changes. It’s your chance to implement an entirely new vision for testing.
When deploying any application that holds customer or user data, both data compliance and data privacy are important areas to consider. Yet these two areas of data management are sometimes misunderstood. This blog post will shed some light on the differences between data compliance and data privacy.
In this Postman load testing tutorial, you'll learn how to run a large scale load test in Kubernetes using your existing Postman collections. Because HTTP services don't have a graphical user interface, it's common to build collections of requests using Postman during the development process. These collections are useful for running quick functionality tests as you develop each endpoint. However, as the service grows you eventually need to test it in a more realistic way with larger volume. This is called a load or stress test. Speedscale is a Production Data Simulation Platform that includes this stress/load testing capability out of the box.
We’re back with another Job of the Week – but this time, we’re taking a step back to cover a concept we’ve skipped over in previous segments: OAuth2 authentication. Richard’s demonstrations often show simpler shortcuts to accessing data – but these shortcuts may not always be practical in real-world examples. Never fear! We’ll arm you with the know-how you need to make your data hacks just as impressive in real life.
