Imagine you are developing a streaming application that consumes data from a topic that has a defined schema. You are finally ready to test the application and realize you need a way to produce a sample schematized message. What do you do?

Here's a table comparing the two approaches for you to consider.

Local preview environments are transforming how developers test and validate code changes before merging them into the main codebase. Acting as temporary cloud environments, they provide a production-like setting where new features and bug fixes can be tested in isolation, catching issues early and streamlining the development code review process. These environments are crucial for enhancing development velocity, especially in CI/CD workflows used by DevOps engineers and QA teams.

In today's data-driven business landscape, the ability to predict trends, explain drivers, and act on insights is no longer a luxury—it's a necessity. Yet for many organizations, the path from data to predictive intelligence remains challenging. Data science resources are scarce, and traditional tools often require specialized expertise that most analytics teams lack. At Qlik, we believe that the power of predictive analytics should be accessible to all.

Without a doubt, Artificial Intelligence (AI) is revolutionizing businesses, with Australia’s AI spending expected to hit $6.4 billion by 2026. However, according to The State of Enterprise AI and Modern Data Architecture report, while 88% of enterprises adopt AI, many still lack the data infrastructure and team skilling to fully reap its benefits. In fact, over 25% of respondents stated they don’t have the data infrastructure required to effectively power AI.

Like most organizations today, you’re probably looking to optimize your business model through increased technology adoption. The more successful digital transformation projects look at changing business trends and seek to incorporate those trends within their own specific environment. Similarly, as API technology grows, promising new functionalities and integrations, enterprises should aim to embrace the utility of APIs within their wider technology strategy.

It sounds counterintuitive—using a technology that has trust issues to create more trustworthy data. But smart engineers can put generative AI to work to improve the quality of their data, allowing them to build more accurate and trustworthy AI-powered applications.

We are proud to share that Katalon has successfully completed its SOC 2 Type II audit, conducted by Sensiba LLC. We received a clean audit opinion, with no exceptions noted in the review of our controls over the specified period. This achievement confirms that our internal controls are functioning effectively, further strengthening the confidence our customers have in us and enabling them to operate securely.

This guide walks you through setting up a Free/Paid plan for your customers using a supported payment platform integrated with Moesif, focusing on tracking usage and managing upgrades to paid tiers. While the steps in this guide are specifically for Stripe, they can be adapted for other supported payment platforms.