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Many processes in our daily software development chain require data analysis in real-time. Ensuring the reliability of the data is vital, since multiple processes may rely on it. While taking into account the performance and fetching only the relevant data that is required for our specific use case.

Application Programming Interface, or API, is an important element to consider when you design an online product or platform. Well-designed API is equivalent to a well-designed user interface for enterprise customers. When you implement an intuitive and easy-to-use interface, your product can retain and attract more users.

In the previous article, we talked about Distributed Tracing with MuleSoft APIs using OpenTelemetry. In this post, we’ll go through the process of integrating Distributed Tracing with MuleSoft APIs using OpenTelemetry via a proxy server. The purpose of this article is to demonstrate how we can instrument a legacy mule app with open telemetry without making changes to the existing app. Here, we’re showing an example of getting data from a header as well as a query parameter.

To validate error handling often means to setup complex environments. This guide shows how you can avoid doing so.

Distributed tracing enhances observability by providing detailed insights into the performance, behavior, and dependencies of your distributed system. It empowers you to proactively identify and resolve issues, optimize performance, and deliver a reliable and high-performing application.

Today, we’re thrilled to announce the latest endpoints for the Raygun API – Deployments. This new release allows developers to efficiently manage deployments, with increased flexibility and control over their Raygun platform.