Progress Chef brings enterprise-grade secure configuration management and governance to fleets of desktop AI supercomputers at scale
BURLINGTON, Mass., June 30, 2026 (GLOBE NEWSWIRE) -- Progress Software (Nasdaq: PRGS), the trusted provider of AI-powered digital experience and infrastructure software, today announced that its Progress® Chef® platform now delivers enterprise lifecycle management and configuration capabilities for NVIDIA DGX Spark, enabling IT teams to securely provision, monitor and manage the desktop AI supercomputer at scale.
NVIDIA highlighted Progress Chef's role in enabling enterprise management for DGX Spark earlier this month in its developer blog.
"DGX Spark is bringing powerful AI computing out of the data center and into the hands of developers across the enterprise," said Sundar Subramanian, Executive Vice President and General Manager, Infrastructure Management at Progress Software. "As this new class of infrastructure scales, organizations must maintain confidence that every system remains secure, compliant and aligned with its intended state. Progress Chef provides the automation and governance needed to move quickly without losing operational control."
NVIDIA DGX Spark delivers petaflop-class AI performance in a compact desktop system, combining advanced hardware with the NVIDIA AI software stack. Designed to put AI supercomputing directly in the hands of developers, DGX Spark enables teams to build, fine-tune and run AI models locally. As these systems expand across offices, research facilities, edge locations and regulated environments, enterprises must manage them with the same rigor as other critical infrastructure. NVIDIA identified Progress Chef as an enterprise manageability partner supporting DGX Spark deployments.
Progress Chef enables IT and platform engineering teams to integrate DGX Spark into existing infrastructure operations and automate key lifecycle stages, including:
Consistent configuration: Establish and continuously maintain approved system configurations
Fleet-wide visibility: Monitor system health, software inventory and configuration posture
Controlled maintenance: Orchestrate updates and operational changes across staged cohorts
Continuous compliance: Detect configuration drift and validate adherence to security policies
Governed automation: Enforce role-based access, approvals and auditable workflows
Incident response: Automate diagnostics and evidence collection across distributed systems
Lifecycle management: Standardize processes from deployment through retirement