Operations | Monitoring | ITSM | DevOps | Cloud

We’re excited to announce that ScienceLogic has been recognized in the 2025 AI Breakthrough Awards as the winner of “Predictive Analytics Platform of the Year.” This marks our second consecutive win in the program—and highlights our leadership in shaping the future of intelligent automation and observability. As organizations move from traditional monitoring toward autonomous operations, the need for real-time insight, automation, and predictive intelligence has never been greater.

Dynatrace gives you incredibly deep observability data. But all that depth can bury the insights needed. In this blog, we show how to turn Dynatrace's complex telemetry into visual dashboards that actually make sense. Dynatrace is a leading observability and application performance monitoring (APM) platform, known for its deep insight into complex, modern cloud environments. With capabilities spanning infrastructure monitoring, real user monitoring, and security, Dynatrace offers powerful telemetry.

Elastic now integrates with the NVIDIA Enterprise AI Factory validated design to provide users with a recommended vector database for their on-premises AI Factories. The validated design provides enterprises with a framework for building and deploying AI Factories on-premises.

In the era of AI, software development is at an inflection point, and observability has never been more critical. Teams are dealing with more code, more data, and more pressure than ever before. To navigate these new challenges, you need a partner with a strong vision for the future and a knack for looking around corners. Honeycomb is proud to be named a Visionary in the 2025 Gartner Magic Quadrant for Observability Platforms.

When your Go service hits 500ms latencies but CPU usage is flat, tracing gives you visibility into what the profiler misses. With 1–2% runtime overhead, Go’s built-in tracing tools help you: This makes it easier to debug performance regressions that don’t leave a clear footprint.

It’s 2 AM. An incident’s in progress. Error rates are climbing. You jump into the logs, filter by service, adjust the time window… and now you need a LogQL query. You write one. It errors out. You fix the syntax, try again, only to realize you need a different filter or a new aggregation. Back to rewriting. By the time you’ve got the query right, you’ve already lost 10–15 minutes. The system is still broken, and you still don’t know why.

When a customer taps a button, submits a form or waits for a page to load, they’re not thinking about your backend architecture, microservices, or CDN; they want it to work instantly. But when it doesn’t, the frustration is immediate. Maybe the app freezes. Maybe a checkout fails. Maybe the entire experience just feels laggy. And the worst part? They don't complain, they just leave the application.

Automate the removal of agents with Opslogix Lifecycle Management Pack Lifecycle Management is something that falls behind in many SCOM environments. It is common for organizations to reach out to us for help with manually removing agents when servers are no longer in use. To decrease the manual tasks and automate the removal of agents, we created the Opslogix Lifecycle Management Pack.