Operations | Monitoring | ITSM | DevOps | Cloud

Datadog has long supported the monitoring of instrumented Go applications through our Go tracer v1. As the Go ecosystem has continued to mature, we’ve been hard at work collecting feedback and improving upon the tracer’s capabilities and usability features. We are now thrilled to announce the release of our Go tracer v2.0.0. This major update includes better security and stability, and a new and simplified API.

We’ve noticed a lot of our customers spend countless hours building and configuring processors. Either parsing JSON, standardizing log formats, normalizing timestamps, masking PII, de-duplicating logs, the list never ends. Most work revolves around recreating the same processor bundles in multiple processor nodes. Bindplane’s new Blueprints solves that boring, repetitive work by providing pre-built processor bundles you can drop into any pipeline with a single click.

When you run critical IT or Security systems, you are still on the hook if an alert is missed or a pipeline drops data. That is why Cribl Copilot never tries to replace you. Instead, it works as a partner you can question, guide, and overrule.

I’m genuinely excited about what we're rolling out with Copilot Editor, an update to our AI that’s truly packed with new capabilities designed to help you automate pipeline development. You can read about these capabilities here. I wanted to take a moment to share our thinking on a core principle that guides how we build, especially regarding the impactful, and sometimes daunting, world of generative AI.

Prometheus can be lightweight to start with, but once it’s in production, storage usage tends to grow faster than expected. Managing how long data is kept becomes critical, especially when you're working with limited disk space or tight budgets. This guide outlines the key concepts behind Prometheus data retention, how to configure it effectively, and what to watch out for.

Picture this: a crime scene where the evidence is scattered across five different rooms. There’s a footprint in one, a shattered window in another, a stray shoe on the stairs, and a witness across the street, who only saw part of what happened. Each clue matters in solving the case, but none of them tells the full story on their own.

First of all, by frontend memory usage I mean the amount of memory that a user’s browser needs when using your website or webapp. Secondly, do you have any idea how much browser memory your website or webapp requires? Or do you know if or how much the memory footprint of your website/webapp has changed over the last few months? Or after the recent changes or releases you made? I’m guessing you don’t. Yet, this is important to monitor to avoid a bad user experience.

A recent LinkedIn poll by Peter Zaitsev asked: “What is the most common preventable cause of downtime in your environment?” Guess what most respondents said it was? Surprise, surprise – the top answer is Deploying Broken Code, with 57% of respondents selecting it. This reinforces how critical it is to catch issues before they hit production.

We recently had the privilege of hosting several industry experts and technology executives across platform strategy, SRE, and engineering enablement for breakfast at our Observability Day in London. We noted that they’re all facing the same fundamental tension: deliver faster, scale smarter, stay resilient, and somehow get ahead of what’s coming next. But how do you move fast without breaking things? And how do you prove the value of the things you don’t break?