Systems | Development | Analytics | API | Testing

Using Python MockServer for API Testing

Using a mock server is a popular method of working around these limitations and realities, allowing you to test web server assets against specific requests, ensuring that your response data matches the expected outcome. Today, we’re going to look at a powerful solution for Python clients in the form of MockServer. We’ll walk through the tool’s basics and learn how to use it for your own testing.

Measure Your App's Speed & Success with New Performance Targets

Knowing how well your application is performing is just as important as ensuring it doesn’t crash. But what defines “good performance?” How do you know if your app is hitting the mark or falling behind? With SmartBear Insight Hub, you can now use performance targets to set and track specific benchmarks for your application’s performance metrics.

Unlocking efficiency: 5 key use cases for Tricentis API simulation

In today’s interconnected digital world, software development and testing often hinge on APIs and dependent systems. These systems are the backbone of modern applications, but they can also create bottlenecks when they’re unavailable, costly, or challenging to work with. Tricentis API Simulation eliminates these barriers, enabling teams to accelerate development, reduce costs, and deliver high-quality software with confidence.

The $500B AI Gamble: Will APIs Unlock America's Next Tech Revolution?

The United States is investing $500 billion into AI infrastructure, aiming to lead the global AI race. This initiative, backed by OpenAI, SoftBank, and Oracle, focuses on building data centers, chips, and scalable systems. But here's the catch: APIs are the key to making this investment work. APIs are the backbone of this effort, and their success will determine whether this $500 billion gamble pays off.

How API Product Managers Can Leverage AI to drive better decisions

The responsibilities of an API product manager varies depending on the organization and industry they work for, among various other factors. However, the common set of tasks they carry out include managing the diverse user needs, ensuring reliability, and aligning API strategies with organizational goals. Performing these duties requires a delicate balance. In addition, API product managers face increasing challenges as APIs evolve into strategic business drivers.

Essential Guide to API Documentation: Best Practices and Strategies

Clear, effective API documentation is a crucial and rapidly expanding component of software development. Solid documentation provides all the necessary information a developer needs to integrate with an API so that they can avoid spending hours troubleshooting and context switching. It reduces the need for additional support from other teams, encourages more users to adopt the API, and creates a seamless developer experience for overall satisfaction.

Services, Multizone & Load Balancing: Combining it all Together in Kong Mesh

Services are the core component of service meshes. But what does it mean to send traffic from a workload to a service? What is the identity of a service? How does configuration apply to services? How do services interact when your cluster is multi-zone? Kong Mesh recently accomplished a major overhaul of its service to make them more intuitive and easier to manage that we want to share.

Comparing AI API Gateways

AI Gateways are rapidly becoming essential tools for businesses leveraging artificial intelligence and large language models (LLMs). Traditional API Gateways have evolved to meet the demands of modern AI workloads, offering features that cater to the unique requirements of AI/ML applications. These include advanced routing for models, latency management, and comprehensive analytics to optimize performance.

The Evolution of Enterprise AI: Navigating the Risks and Rewards of an Emerging Landscape

AI is moving at breakneck speed – can your enterprise keep up without breaking down? As businesses race to adopt AI, the push for innovation is relentless. But while AI promises to accelerate development and unlock new opportunities, it also opens the door to unforeseen risks. Malicious models, supply chain vulnerabilities, and unpredictable behavior can derail even the most well-intentioned AI initiatives.