Operations | Monitoring | ITSM | DevOps | Cloud

Our SIGNL4 April Update is here - packed with powerful new features! In this video, we showcase how our AI-powered shift and duty scheduling works. The SIGNL AI identifies rotation patterns and proactively assigns future shifts based on historical scheduling data. Redesigned Signl-Center: Experience a sleek, modern interface with a bento-style layout, one-tap action buttons, streamlined status tabs, and modular detail views.

Our SIGNL4 April Update is here - packed with powerful new features! In this video, we introduce the redesigned Signl-Center featuring a sleek, modern interface with a bento-style layout, one-tap action buttons, streamlined status tabs, and modular detail views. Incident handling is now faster than ever, with enhanced notification tracking and easy CSV export.

In this video, we'll explore practical ways to utilize the AI Assistant in Splunk Observability Cloud. Through real-world scenarios, learn how the AI Assistant can help you interpret metrics, contextualize data, onboard new team members to your organization, and automate tasks via the Splunk Observability Cloud API. AI Assistant in Splunk Observability Cloud enhances observability by providing actionable insights and streamlining workflows.

Ever tried to build a metrics dashboard and thought, “Wait, what metrics am I actually sending?” We heard this from users again and again-so we built Metrics Explorer. For the first time, you get a real-time, interactive view of every metric coming into your system: Whether you’re onboarding a new integration, debugging an alert, or just exploring your data, Metrics Explorer makes it easy to understand and work with your metrics-no more guesswork, just clarity.

@hyperviewhq is enhancing its DCIM software with the addition of a powerful AI Assistant. One of its key features is the ability to quickly identify outdated firmware, ensuring your devices remain up-to-date and secure.

Learn how to determine if tf satisfies GitOps Principles.

On this episode of Interrupt Live, we'll meet Hayden Riddiford, the writer behind "Beyond Error Codes: Debugging III-Defined problems". Interrupt Live is a series where we sit down with Interrupters contributors to hear more about their origin stories, engineering journeys, and the unique challenges that inspired their contributions. If you’ve ever wanted to hear directly from the engineers behind your favorite Interrupt posts, now’s your chance.

How accurately can LLMs predict how bugs were fixed? To start exploring this field, we put Llama 4 and other leading models to the test using a GitHub Multiple Choice Benchmark. Each model was given a real bug ticket and had to identify the pull request that resolved it.

Is it the third-party API or my code? Your service suddenly slows down, or errors spike, and you’re stuck guessing if it’s your own logic or an external API you don’t control. We’ve seen this pain across teams: dashboards don’t tell you which vendor or endpoint is the culprit, and debugging turns into a maze of guesswork. Rate limiting, vendor errors, or integration issues often slip through until users complain.

We built deep Temporal observability in SigNoz.