Peer Software, today announced PeerGFS v6.4, the latest version of its Global File Service platform.
The new release delivers significant advancements in performance, scalability and operational flexibility for organizations managing large-scale environments and globally distributed file infrastructure.
Today’s enterprises, particularly in the semiconductor, healthcare and life sciences, AI/ML and other data-intensive industries, are facing exponential growth in data driven events and increasingly complex application workloads.
As a result, organizations are distributing workloads across multiple locations, dynamically pursuing available compute resources, and leveraging cloud elasticity to scale capacity on demand.
PeerGFS v6.4 is purpose-built to meet this challenge, enabling seamless data orchestration and synchronization across on-premises and cloud infrastructure, so teams can move faster and operate at hyperscale without sacrificing cost efficiency or productivity.
“As organizations scale data-intensive workloads across data centers, edge locations and cloud environments, the ability to keep data synchronized, accessible and close to compute has become a critical operational imperative,” said Jimmy Tam, CEO of Peer Software. “PeerGFS helps customers eliminate the friction of distributed file management by improving performance, increasing resiliency and giving IT teams greater control over how data moves across their global infrastructure. The result is a more efficient foundation for supporting modern engineering, semiconductor, life sciences, and AI-driven workloads at scale.”
PeerGFS v6.4 delivers broad performance advancements for real-time file synchronization and scheduled replication for large data sets, including:
- Greatly improved performance for both scheduled scan and real-time replication for SMB and NFS workloads
- Enhanced resilience for large file transfer resumption on connectivity breaks across distributed sites
- Upgraded auditing of configuration and management activity
- Improved performance, reliability, and manageability of edge data management in distributed and bandwidth-constrained environments.
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