How to scale agentic applications without creating AI sprawl
Databricks on scaling agents without chaos: governance, observability, and cost control before you hit 50 concurrent workflows.
Why it matters
As agentic applications move from pilot to production, enterprises face sprawl risks—multiple agent frameworks, hidden costs, governance gaps. Databricks positions its platform layer (agent observability, cost tracking, policy enforcement) as the control plane. Practitioner value: operational patterns for agent deployments at scale, not just capability.
The key facts
5 to knowVendor: Databricks blog post on agentic application scaling
Focus: governance, observability, cost control for multi-agent deployments
No GA announcements, pricing changes, or measured deployment outcomes disclosed
Positioned as patterns/guidance rather than product feature launch
Article date: September 30, 2026
Go to the source
Databricksdatabricks.com
Publisher excerpt: Building an agent is getting easier. More capable models and coding agents are making...