Operations | Monitoring | ITSM | DevOps | Cloud

Datadog is widely recognized for its comprehensive range of products and tools, making it quite a challenge to find a suitable alternative. When seeking an alternative to Datadog, it's essential to conduct a thorough comparison of features, performance, limitations, and other vital aspects. This task requires a deep dive into the details, and it might not be as straightforward as it seems at first glance.

Top tips is a weekly column where we highlight what’s trending in the tech world and share ways to stay ahead. This week, we’re taking a closer look at how smaller IT teams can keep their development costs under control—without sacrificing quality or long-term viability. When you're a large IT enterprise providing services to millions of users around the world, it's only natural to expect development costs to be sky high.

We’ve updated Logs Explore to integrate the real-time streaming capabilities of the old “LiveTail” into our new Explore environment. The result? A faster and more seamless experience. Customers can now benefit from.

A business website isn’t just an online presence; it’s the virtual front door to your business, brand, or service. If the door remains locked, opens slowly, or undergoes unexpected changes, you run the risk of losing visitors, customers, and revenue. That’s where comprehensive website monitoring becomes essential. Modern web monitoring goes far beyond simple uptime checks.

Three frameworks dominate Python backend development in 2026: Django, FastAPI, and Flask. This guide helps you choose between them (plus specialized alternatives like Falcon, Tornado, and Litestar) using a simple decision tree. Answer three questions about your project, understand each framework's strengths, and pick the right tool for your needs.

You know the situation: You're in a meeting and your alerts start to go off, but no one on the other side of the camera knows why you have to abruptly drop from the call. What if, instead, you had a robot in the background of your Zoom meeting that started to blink when those same alerts went off? You could just point to it, type in the chat "I have to drop," and off you'd go.

OAuth 2.0 client credentials flows are a core mechanism for machine-to-machine API authentication. They enable background jobs, microservices, and system integrations to securely access APIs without user interaction. However, while most teams spend time configuring these flows, far fewer ensure they are continuously monitored in production. This creates a critical blind spot: OAuth failures often surface only after dependent services begin failing.

High-cardinality metrics are one of those ideas that sound obviously right - until you try to use them in production. In theory, they promise precision. Instead of averages and rollups, you get specificity: per-request, per-userid, per-container, per-feature insights. The kind of detail we all immediately want when something is on fire. And then things start breaking. Not immediately. Not loudly.But quietly.