Hi Obi,
How do you keep AI systems reliable when they move from experiments into always-on production workloads?
AI adoption is changing the pressure on modern infrastructure. The challenge is no longer just building models, but running them reliably at scale. Data systems, cloud platforms, and production databases are now supporting machine-driven workloads that are constant, unpredictable, and often far heavier than the systems were originally designed for.
Join us on June 23rd, 2026, at 10 AM EDT for an InfoQ Live Roundtable where practitioners will delve into:
- Production AI Infrastructure: How AI workloads are changing the design and operation of cloud platforms, data systems, and production databases.
- Scaling Under Machine-Driven Load: What happens when AI systems create continuous pressure on infrastructure, and how teams are adapting.
- Identifying Failure Points Earlier: How teams are finding where systems are likely to break before outages happen.
- Architectural Decisions for Reliable AI: The patterns that help organizations scale AI systems gracefully, and the choices that create risk later.
This 60-minute live discussion will feature practical insights for engineering teams working through the infrastructure challenges behind production AI, including what is working, what is breaking, and what needs to change as AI becomes a permanent part of modern software systems.
We've arranged a complimentary ticket for you to attend. Use code “AIPRODJUN26” when registering for the InfoQ Live Roundtable.
