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.

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.

Data Centralization emerges as a necessity in the cloud world now that data is omnipresent. Gone are the days when different teams had to rely on document sharing and wait till the data gets to them. With AIOps, data can be centralized and teams can have access to it in near real-time. This is a great opportunity for organizations to take advantage of the latest technology and leverage its power to solve their problems efficiently.

The popularity of open-source log management tools has been on a steady rise in recent years. As businesses become increasingly reliant on software applications and cloud-based services, logging has become an essential part of operations. Log management is a crucial process for organizations to collect, store, and analyze log data. Businesses can troubleshoot problems, identify security threats, and optimize system performance by effectively managing log data.

Centralized Observability may not be a buzzword but its practicality and importance can’t be denied. Let’s see why is that. As DevOps and IT teams recognize the importance of Observability, it becomes a critical component to monitor the stack and ensure data reliability. That being said, enterprises are rapidly embracing modern data stacks to harness the power of data. Therefore, a host of platforms require data observability as a tool for reliable and trustworthy data management.

Prometheus, developed by SoundCloud, is a powerful open-source system for service monitoring and time series data storage. It collects metrics from configured targets, evaluates rule expressions, presents results, and triggers alerts based on defined conditions. Thanos, on the other hand, is a collection of components designed to create a highly available metric system with limitless storage capacity.

In today’s data-driven world, the need for comprehensive observability has never been greater. Organizations rely on observability to gain insights into their systems’ and applications’ performance, availability, and behavior. However, the traditional approach to observability, which involves ingesting, processing, and storing massive amounts of data, is becoming increasingly challenging and expensive.

Log Management tools are crucial for the security and performance of your IT infrastructure. With the right log management system, you can quickly detect and respond to any anomaly or performance issue. Presently, there are numerous log management platforms. Each with its own unique set of features and benefits. While most of these platforms offer industry-standard capabilities, what sets them apart from each other are the stand-out features, pricing, and overall user experience.