Systems | Development | Analytics | API | Testing

In this blog, we will demonstrate how to get the code coverage data for each incoming request on a python web server built using any web framework.

Whether you’re building a web application, a mobile app, or any other software product, integrating with third-party APIs is almost inevitable. But what happens when you need to test your application’s behavior without relying on these external services? That’s where the magic of simulation comes in handy. In this blog, we’ll explore how you can simulate responses effectively, even if the actual service isn’t available.

Artificial intelligence (AI) is something that, by its very nature, can be surrounded by a sea of skepticism but also excitement and optimism when it comes to harnessing its power. With the arrival of the latest AI-powered technologies like large language models (LLMs) and generative AI (GenAI), there’s a vast amount of opportunities for innovation, growth, and improved business outcomes right around the corner. All of that technology, though, depends on data to be successful.

Regulations often get a bad rap. You may have heard the old idiom “cut the red tape” which means to circumvent obstacles like regulations or bureaucracy. But in many – if not most )– cases the underlying need for regulations outweighs the burden of compliance.

At Qlik, we're witnessing a thrilling shift in the landscape of data analysis, customer engagement, and decision-making processes, all thanks to the advent of generative AI, especially Large Language Models (LLMs). The potential for transformation across all sectors is enormous, but the journey toward integration can be daunting for many businesses with many leaders wondering where to start in integrating the exciting capabilities of AI into their daily workflows.

Legacy security information and event management (SIEM) solutions, like Splunk, are powerful tools for managing and analyzing machine-generated data. They have become indispensable for organizations worldwide, particularly for security teams. But as much as security operation center (SOC) analysts have come to rely on solutions like Splunk, there is one complaint that comes up for some: Costs can quickly add up.

Test automation is an essential component in today's software development landscape, where speed and quality are critical. It ensures the timely delivery of high-quality software by automating repetitive and time-consuming testing tasks. However, the journey to effective test automation comes with challenges such as selecting the right tools, managing complex test cases, and enabling seamless integration of testing into the software development lifecycle.

Confluent has published official Docker containers for many years. They are the basis for deploying a cluster in Kubernetes using Confluent for Kubernetes (CFK), and one of the underpinning technologies behind Confluent Cloud. For testing, containers are convenient for quickly spinning up a local cluster with all the components required, such as Confluent Schema Registry or Confluent Control Center.

Data forms the foundation of the modern insurance industry, where every operation relies on digitized systems, including risk assessment, policy underwriting, customer service, and regulatory compliance. Given this reliance, insurance companies must process and manage data effectively to gain valuable insight, mitigate risks, and streamline operations.

Why forward-thinking organizations are turning to a data mesh architecture.