Operations | Monitoring | ITSM | DevOps | Cloud

According to McKinsey, 78% of organizations have implemented AI in at least one core function, with data analytics leading that transformation. AI no longer supports analytics from the sidelines; it now directs how data is queried, modeled, and delivered. It forecasts outcomes, detects anomalies, and reveals real-time insights, often before a dashboard loads. For SQL developers and DBAs, this marks a new phase in data work.

SQL Server AI marks the beginning of a new era for data-driven businesses. What was once thought of as a future prediction is now actively transforming database management. With outstanding features like natural language processing, predictive analytics, and automated error handling, managing data with artificial intelligence in SQL Server is faster, easier, and better. If you are a database developer, data analyst, or DBA, using SQL Server AI is no longer optional; it’s a productivity necessity.

Imagine telling your database to get the best five customers by order from six months ago, and you get a well-optimized query instantly. Zero coding. No Googling syntax. Just results. Welcome to the future of database management with MySQL AI. MySQL Artificial Intelligence is a strategic solution transforming the traditional method of managing databases.

If you manage an enterprise network, then you’ve definitely come across MPLS. Although many businesses rely on MPLS technology for large, high performing networks, they can suffer from network problems, like network congestion, that can impact user experience. Monitoring MPLS using a Network Monitoring tool is key to identifying and solving network issues that impact MPLS performance.

An enterprise client reports latency. Your dashboards say everything is fine. They blame you. You blame them. Nobody can prove it either way. This is where most monitoring efforts hit a wall. Too often, the conversation gets stuck on dashboards and tools instead of the one thing that really matters: truth. Observability isn’t about collecting metrics or building pretty dashboards.

LangChain apps are powerful, but they’re not easy to monitor. A single request might pass through an LLM, a vector store, external APIs, and a custom chain of tools. And when something slows down or silently fails, debugging is often guesswork. In one instance, a developer ended up with an unexpected $30,000 OpenAI bill, with no visibility into what triggered it. This blog shows how to avoid that using OpenTelemetry and LangSmith. With this setup, you’ll be able to.

We’re excited to announce a powerful new addition to your monitoring toolkit: DNS Monitoring is now available on UptimeRobot! DNS (Domain Name System) is a core component of internet functionality. When DNS records are misconfigured, hijacked, or simply expire, they can lead to serious outages, broken email services, or even security risks. That’s why we’ve introduced DNS Monitoring – to help you stay in control of your domain’s health at all times.

When you’re just starting out, you might picture yourself managing your IT infrastructure like Tom Cruise in Minority Report—key information projected in front of you, predicting events before they happen, controlling everything at the speed of thought with cinematic gestures on some kind of holographic computer.

As digital transformation continues to reshape the business landscape, IT teams are under more pressure than ever. Organizations demand faster service, always-on support, and seamless user experiences – all while IT budgets remain stagnant or even shrink. Organizations urgently need solutions that help them keep up without burning out their teams or inflating costs. This is where IT automation becomes essential.

In this tutorial, let’s walk through setting up a modern TIG stack in 10 minutes. TIG stands for three popular open source tools that complement each other: Telegraf, InfluxDB 3, and Grafana. They are often used to collect, store, and visualize time series data from servers, containers, APIs, or even IoT devices. We will be using a read-to-use GitHub repository that includes.