Operations | Monitoring | ITSM | DevOps | Cloud

Machine learning models must do more than make accurate predictions; they also need to adapt as the world around them changes. In real-world systems, data distributions shift due to seasonality, equipment wear, user behavior changes, or other external forces. If your models can’t keep up, the result is poor predictions. This can lead to outages, inefficiencies, or missed opportunities. That’s why forecasting systems need to be monitored and resilient, not just accurate.

Show a customized, crash-specific message when your game crashes. Locked in an intense battle, hanging on for dear life, on the verge of nigh-impossible victory and then… boom! Positively, absolutely, unquestionably, no one wants a crash to interrupt their favorite game. Crashes are a frustrating yet inevitable part of gaming, and the only thing worse than being on the receiving end of a crash is being on the receiving end of the same crash repeatedly.

We’re excited to share that Rollbar is now part of the ilert integration catalog! This new technical partnership allows software teams to detect application errors in real time with Rollbar and instantly respond using ilert’s powerful alerting and incident management features. What is Rollbar? Rollbar is a comprehensive, real-time error monitoring and debugging platform designed to help development teams detect, diagnose, and resolve issues faster—before they impact users.

We work in a digital landscape where IT teams are expected to move faster, scale smarter, and deliver flawless digital experiences, automation is no longer optional; it’s foundational. But while most organizations have started down the automation path, far fewer can answer the critical question: How do we measure success? The problem isn’t just a lack of metrics. It’s that the wrong metrics are still steering the ship.

In today’s dynamic business environment, mastering inventory management is more than a necessity—it’s a competitive advantage. Effective inventory management not only reduces inventory costs but also boosts profitability, enhances customer satisfaction, and ensures order fulfillment runs smoothly. For small businesses and large enterprises alike, the right inventory management strategy can transform operations and improve the bottom line.

The world is changing every day. From geopolitical shifts to legislation like GDPR which requires localized processing – these all create a complex and uncertain landscape where data storage, processing, and cloud services could potentially come to a sudden halt or suffer heavy disruption overnight. As a result, organizations are increasingly interested in potential routes for shifting cloud services to safer alternatives closer to their country of operation.

Both Grafana Tempo and Jaeger are distributed tracing tools designed for modern microservice architectures. Jaeger, released as an open-source project by Uber in 2015, has matured into a graduated CNCF project. Tempo, announced by Grafana Labs in October 2020, is a newer entrant focused on high-volume tracing with a unique storage architecture. Before comparing these tools in detail, let's quickly review what distributed tracing is and why it matters.

When something breaks in production, logs are usually where you start. They help you figure out what happened, where, and why. But with microservices architecture, logging isn't simple anymore. In a traditional monolithic application, logs live in one place. With microservices, they're scattered across multiple services, containers, and sometimes even data centers. What used to be a simple grep command now feels like solving a mystery without most of the clues.

No matter where or how you work, we all have the same goal when an incident occurs: to get it resolved effectively and efficiently—and as quickly as possible. However, the way we achieve that goal isn’t always the same. We understand that different organizations operate differently, so you need flexibility from your IRM tooling.

With the 3.0 release, Prometheus firmly established itself as the leading metrics database for OpenTelemetry. A lot of work has gone into integrating the two open source projects, including a major Prometheus enhancement we’re really excited about: resource attribute promotion.