As ML workloads become revenue-critical, "good enough" latency doesn't cut it anymore. Platform teams are being squeezed between the need for massive contextual data and the reality of brittle, high-maintenance infra.
In this live session, we will explore why real-time context has become the core data primitive for modern AI.
Join our live session to discover:
The New Data Primitive: Why real-time context at scale is now a hard requirement for modern intelligent systems.
Predictability Under Pressure: Why context must not only be fast but stay stable even under the heaviest loads.
Scaling Without Complexity: How to serve increasingly large contextual datasets without exponential cost or operational overhead.
Modern Architecture: Why legacy systems struggle with context-rich AI/ML and how modern architecture fills the gap.
Can’t join us live? Register anyway, and we’ll send you the recording.
Building a self-service developer platform the thoughtful way As more organizations repatriate, modernize, and build new workloads on-premises, the demand for a "public cloud-like" experience inside the data center has never been higher. Join us live to learn how to automate full-stack Kubernetes deployments with a single git commit.
AI-powered Kubernetes observability best practices in 2026 Join TNS host Chris Pirillo and Dynatrace experts Paul Brugan and Jacob Hanley for a live session on practical, AI-powered strategies to help you run Kubernetes with greater confidence and efficiency in 2026.
Building production-ready agentic AI — why a control plane matters Join us on March 24 to learn what it takes to run agentic AI in production. We'll explore how end-to-end observability, deterministic real-time context, and a centralized control plane enable reliable autonomy.
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