With the release of Kreya v1.19.0 support for GraphQL was added. This guide will walk you through setting up your first GraphQL operation, from schema import to automated testing.

In my previous post we explored the full gRPC protocol stack, from the .proto contract down to the HTTP/2 frame on the wire. We ended with a cliffhanger: browsers cannot speak native gRPC. I promised to cover that gap. This is that post.

We will look at why browsers are fundamentally incompatible with the gRPC HTTP/2 protocol and how gRPC-Web works around those limitations at the byte level. Along the way, we will dig into the Fetch API's streaming internals and close with what is (hopefully) coming in the near future.

The API development lifecycle has changed. In 2026, the choice of API testing tools is no longer just about sending requests. It's about data ownership, seamless team collaboration, ensuring reliable deployments and deep protocol support.

For years, Postman has been the industry standard, but its shift toward a "cloud-mandatory" ecosystem has caused discontent for developers who value privacy and local workflows.

On the other side of the spectrum sits Kreya, a "privacy-first" desktop client designed to run where your code lives: in your file system and your version control.

Displaying a large amount of messages in a list can destroy the performance of an application. The naive approach to displaying these messages would be to render each message as a DOM element (in a webpage context). But this quickly degrades the performance, since the browser needs to spend all its time laying out these elements, repainting them during scrolling and holding the huge list of DOM nodes in memory.

Chat apps, log message visualizers and various other applications all face this problem. Today, we are going to take a look how we solved this in Kreya.

Kreya 1.19 is here, and in the meantime we have already released 1.19.1. Together they bring GraphQL, OAuth 2.0 Device Flow, and a set of polish improvements across the CLI and UI.

Securing your APIs with Auth0 is a smart move for production, but it often adds extra steps to the development and testing cycle. No one wants to spend their afternoon manually swapping expired tokens.

In this post, we'll show you how to use Kreya to automate the entire Auth0 handshake, allowing you to call secured endpoints effortlessly.

In our previous posts (part 1 and part 2), we demystified Protocol Buffers and learned how data is encoded into compact binary.

But Protobuf is just the payload. To send this data between microservices, we need a transport protocol. Enter gRPC.

While many developers use gRPC daily, few look under the hood to see how it actually works. In this post, we’ll go beyond the basics and explore the full gRPC protocol stack: from the high-level service architecture and streaming models down to the low-level HTTP/2 framing and byte-level wire format.

4.75 million invoked operations, over 5,000 monthly active users and 3 releases. These are some key facts about the past year.

Is transfering files with gRPC a good idea? Or should that be handled by a separate REST API endpoint? In this post, we will implement a file transfer service in both, use Kreya to test those APIs, and finally compare the performance to see which one is better.

API development is a high-wire act. You’re constantly balancing new feature delivery against the terrifying possibility of breaking existing functionality. Testing, for example manually writing assertions for every field you expect back, is your safety harness. But what happens when the response payload is 500 lines of complex nested JSON? Your harness becomes a tangled mess of brittle code that takes longer to maintain than the feature itself. This is where snapshot testing shines, but it also has drawbacks of its own. Let's take a look.