For years, “visibility” was the holy grail. Teams instrumented everything (logs, traces, metrics), following the seemingly reasonable principle that if they collected and saw more, they’d definitely gain visibility and thus, control. Somewhere along the way, companies started moving the goalpost further and further, hoping that the next iteration
Now that we’ve covered the principles of Metrics without Limits (MwL), let’s explore how you can easily leverage Dataiker to take advantage of this feature. First, navigate to Dataiker > usage > metrics . You’ll immediately see the potential savings from applying MwL to your top 10 metrics!
So, you just got access to Datadog. You log in, and… wow, there’s a lot going on. Dashboards, metrics, traces, logs — it can feel overwhelming if you don’t know where to start. The good news? You don’t need to learn everything at once. With just a few
I’ve worked with teams running Datadog Logs across some of the largest enterprises in the world. One thing I’ve noticed: most logging mistakes aren’t about Datadog itself — they’re about habits carried over from older log platforms. The problem? What worked when you had a single ELK
HTTP checks are a simple way to monitor the availability and response times of your services. This guide walks you through installing the Datadog Agent and configuring it to perform HTTP checks. 1. Install the Datadog Agent First, install the Datadog Agent on a host that will run the HTTP
If you’re a DevOps engineer at a mid-size SaaS company, chances are you don’t have a Site Reliability Engineering (SRE) team backing you up. * If you’ve worked at a larger company before, you already know what that means: you’re carrying your own job plus the invisible
![[Youtube] Mastering Synthetic Monitoring with Datadog: A Practical Guide](https://images.unsplash.com/photo-1460925895917-afdab827c52f?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3wxMTc3M3wwfDF8c2VhcmNofDJ8fHdlYnxlbnwwfHx8fDE3NTM4MjMzMjh8MA&ixlib=rb-4.1.0&q=80&w=600)
Want to catch issues before your users do? Synthetic monitoring lets you proactively test your applications—before, during, and after deployments. In this guide, we’ll show you how to set up and run synthetic API and browser tests in Datadog, the key features to take advantage of, and cost-effective
Welcome to the Datadog Log Management Mastery series—a deep dive into the tools, strategies, and best practices that turn noisy log lines into actionable insights. Whether you’re just starting out or optimizing large-scale log pipelines, these tutorials and guides are designed to help you stay in control, reduce
Before completing your migration, review the following checklist to ensure a smooth transition. 💡Checkout our complete article if something is unclear. ✅ Plan & Preparation: * Define the migration timeline and key milestones. * Identify all assets (dashboards, monitors, users, logs, integrations) that need migration. * Determine whether the migration is to a new
Log parsing in Datadog is both an art and a science. Whether you’re just getting started or refining pipelines at scale, crafting robust parsing rules is critical to ensure logs are structured, searchable, and actionable. This cheatsheet provides a practical, battle-tested guide for building parsing logic—from foundational principles
Observability, like any other discipline, varies in implementation quality and maturity. This guide outlines key success criteria at each stage of the journey—from Pro to Legend to Icon. As a bonus, a scoring app link is provided at the end to assess your current maturity level. 📈 What Does It
Using Vercel and looking for a powerful solution to monitor your app’s performance and reliability? This guide walks you through advanced observability using Datadog, going beyond the default integration to ensure your app stays optimized and running smoothly. Basic Setup To begin, set up the log drain to send