”Isn’t Observability something for Ops to worry about?” I’ve heard this response more than once when talking about how developers should learn OpenTelemetry. I wanted to write this piece to show you how important and how easy it is to learn observability from day one as a coder.

Here at Raygun, we like to go fast. Really fast. That’s what we do! When we see something that isn’t zooming, we try to figure out how to make it go faster. So today, we’re answering a simple (and relevant) question; how do we make our public site, raygun.com, much, much faster? The answer, at first glance, is simple—we build it into a Content Delivery Network (CDN).

As organisations strive to deliver seamless user experiences, maximise operational efficiency, and maintain a competitive edge, the need for comprehensive Application Performance Monitoring (APM) tools becomes increasingly evident. APM tools offer invaluable insights into the performance and behaviour of applications in real-time. They go further than the conventional monitoring approach by providing a holistic view of the entire stack, encompassing servers, databases and user interactions.

Debugging errors in distributed systems can be a challenging task, as it involves tracing the flow of operations across numerous microservices. This complexity often leads to difficulties in pinpointing the root cause of performance issues or errors. OpenTelemetry provides instrumentation libraries in most programming languages for tracing.

Everyone talks about the need for observability, it even comes up in board meetings. But let’s talk about the reasons you shouldn’t add observability to production.

Application performance monitoring (APM) tools have become a fundamental part of many organisations that wish to track and observe the optimal functioning of their web-based applications. These tools serve to greatly simplify the process through automation and allow teams to effectively collaborate to maximize efficiency, enabling you to reach the root cause of an issue before it reaches your customers.

My favorite technical experience from grad school was all the cool ways we were trying to squeeze every last bit of performance out of the IBM JVM (now called Eclipse OMR). The majority of such optimizations required an intricate understanding of how CPUs and memories look under the hood. But why is there such an impressive performance gain in padding objects with blank space to the closest multiple of 64 bytes and ensuring they always start at addresses that are exactly divisible with 64?

As connected as the world is today, it can feel quite disconnected, especially in IT. Individual teams use various tools, each with specialized interfaces and dedicated dashboards, to present or interpret data each the specific functional team needs.

Loki is a open source log aggregation tool developed by Grafana labs. It is inspired by Prometheus and is designed to be cost-effective and easy to operate. But Loki also has some limitations, and you might want to explore some Loki alternatives for your log analytics. In this article, we will look at 11 log management tools you can use as a Loki alternative. Loki is designed to keep indexing low. It does this by making use of labels.