Systems | Development | Analytics | API | Testing

To incorporate the keywords like "HTTP 403," "HTTP error 503," "the service is unavailable," and "monitor Google Cloud API traffic" into the blog, I would recommend integrating them naturally into the content. Additionally, for internal linking from Keploy.io’s website blogs, here’s a possible update to your blog, integrating the mentioned keywords and linking.

Usage-based pricing has long been the default for APIs—straightforward to implement and easy for customers to understand. You charge based on consumption: API calls, compute time, or data volume. It is predictable, measurable, and scales well with usage. But as APIs become more intelligent—especially in AI-driven platforms—raw consumption no longer remains a reliable proxy for customer value. A user can rack up thousands of API calls and still achieve nothing meaningful.

NGINX with OpenResty offers unmatched performance for serving APIs (application programming interfaces) at scale, with the added benefits of the open-source ecosystem. It’s fast, flexible, and production-proven—an ideal choice for scalable web platforms and high-throughput APIs. But even the most reliable platform can leave teams blind to what matters: real-time API usage, user behavior, and production errors.

JSON Web Tokens (JWTs) secure communication between parties over the internet by authenticating users and transmitting information securely, without requiring a centralized storage system. In this article, we'll explain what JWTs are and give a high-level overview of how they work. We'll also implement a JWT-based authentication system by creating a to-do list API using Flask.

When I first started writing Go software a little over a decade ago, one of the features I found particularly intriguing was the ability to build statically-linked binaries for multiple operating systems and architectures without a lot of headache. This build toolchain feature is widely relied upon by nearly all Go developers, especially when needing to build multi-arch container images destined to be run in a Kubernetes cluster consisting of amd64 and/or arm64 nodes.

Automated testing with Cypress has revolutionized how developers ensure code quality, but writing comprehensive test suites remains time-consuming and often tedious. Artificial intelligence tools for Cypress testing are emerging as game-changers, dramatically reducing test creation time while maintaining quality. Let’s face it—writing tests can be a real drag. After you’ve spent days coding a beautiful feature, the last thing you want to do is spend another day writing tests for it.

API request logging is essential for secure and efficient APIs. It helps track performance, detect security threats, and meet compliance standards. Here's a quick breakdown of what you need to know: Why It Matters: Logging provides real-time insights, audit trails for investigations, and supports compliance.

Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to large language models (LLMs). It’s becoming a foundational layer in many AI-native workflows, especially when working with real-time or continuously updating data sources. We're excited to announce that Choreo now supports the deployment of MCP servers, empowering developers to integrate AI capabilities more efficiently into their applications.