There’s a common misunderstanding that profiling is only useful for tiny savings that impact infra costs at scale - the so-called “milliseconds matter” approach. But by dogfooding our own profiling tools, we fixed a problem that saved tens of seconds off each user interaction with our AI agent (and for those of you who like math, that’s four orders of magnitude bigger than those milliseconds that matter).

One Ruby feature that embodies the principle of “optimizing for programmer happiness” is how the language uses garbage collection (GC) to automatically manage application memory. But as Ruby apps grow, GC itself can become a big consumer of system resources, and this can lead to high CPU usage and performance issues such as increased latency or reduced throughput.

A few months ago, we implemented support for exception profiling in PHP. One of the key justifications for building this functionality into Continuous Profiler was to show the hidden costs of exceptions in PHP, especially when they are used for flow control in hot code paths. Once this feature was built, we naturally wanted to know if it surfaced these kinds of flow control problems in customer production systems.

We are excited to share a significant update for Grafana Pyroscope users and the broader open source community: the launch of Explore Profiles, a new application that makes it easier and faster to surface meaningful insights from your profiling data. Explore Profiles is a Grafana app plugin designed to integrate seamlessly with Grafana Pyroscope, the open source continuous profiling backend, providing a smooth, queryless experience to browse and analyze your profiling data.

When you face issues like reduced throughput or latency spikes in your production applications, determining the cause isn’t always straightforward. These kinds of performance problems might not arise for simple reasons such as under-provisioned resources; often, the root of the problem lies deep within an application’s runtime execution.

The use of code profiling to troubleshoot application performance can appear daunting to the uninitiated, and many software engineers even assume that this domain is reserved for niche specialists. But here at Datadog, one of the key goals for our Continuous Profiler product has been to take this seemingly intimidating practice of code profiling and make it more accessible to engineers at all levels.

Each day, more than 70 million active users sign into Roblox to create, play, and interact with each other through virtual experiences. And regardless of what those experiences are, exactly — adopting a pet, completing an obstacle course, or fulfilling orders at a virtual pizza parlor — the Roblox observability team is dedicated to making them seamless.

When OpenTelemetry first came into the picture with the merger of OpenCensus and OpenTracing in 2019, it was pretty much all about classic telemetry data, namely- logs, metrics, and traces. Since then, OpenTelemetry has become an indispensable tool in the modern observability landscape. With frequent integrations and introduction to new capabilities every year or so, it has poised itself as an invaluable tool for cloud enterprises.