Welcome to the AI research bites. This series of short and informative talks showcases cutting-edge research work from ServiceNow AI Research team. The AI Research Bites are open to all, especially those interested in keeping up with the fast-paced AI research community.
Using a drag-and-drop interface, engineering teams can create apps that support troubleshooting, improve day-to-day operations, and offer self-service access without leaving Datadog. With the new conversational AI feature, teams can turn an idea into a working app in seconds. Watch the video to see how it works..
In this video, we introduce Fleet Management and how it helps teams control their telemetry estate as it scales. See how you can centrally manage collectors and agents, standardize configurations across environments, and roll out updates confidently, reducing operational effort and risk.
Testing with production traffic doesn't have to be a security risk. Engineers often avoid production data because of sensitive info like passwords, tokens, and PII. But legacy test data management is too static for modern, fast-changing payloads. Enter the Speedscale Streaming DLP Engine. It automatically detects and redacts sensitive data in real time as it's captured from your environment. You get the realism of production traffic without the risk of a data breach.
In 2025, DevOps teams faced a pivotal moment. The era of treating security as an afterthought was over. Practically overnight, airtight protection became a non-negotiable requirement across every layer of the technology stack, whether on prem, in the cloud, or at the network’s edge. For many teams, this wasn’t just a technical hurdle; it was a daily source of stress.
As our applications grow from simple side projects into complex distributed systems with many users, the “old way” of console.log debugging isn’t going to hold up. To build truly observable systems, we have to transition from simple text logs to structured, queryable, trace-connected events.
Technical debt refers to the future costs and limitations incurred when organizations opt for short-term solutions over robust, long-term scalable architectures. For the middle mile, technical debt often manifests as equipment or network designs that restrict long-term flexibility, scalability, or interoperability.
We are witnessing a fundamental transformation in how software is built. The industry has moved beyond the experimental phase of Machine Learning Operations and entered a complex new reality: the era of the AI Software Supply Chain. The adoption metrics confirm this shift is irreversible. Google reports that 90% of tech workers are now using AI as part of their daily work. Similarly, McKinsey data reveals that 88% of organizations use AI in at least one business function.
Note: this post was co-authored by Nicholas Borg, 3CX Product Manager. 3CX provides a robust, flexible IP PBX platform used by organizations of all sizes to power their contact centers. It offers detailed call activity, agent performance metrics, and operational insights — all of which become even more powerful when visualized.
Even with a powerful database or visualization layer, performance can suffer if queries aren’t optimized or system settings aren’t tuned. The new Mimir Query Engine in Grafana Cloud improves query efficiency, but there are still best practices you can follow to keep dashboards fast and responsive—whether your data source is hosted in Grafana Cloud or running on-premises.