- Provided near-instant file access across continents
- Improved team productivity 10-20%
- Simplified operations with integrated archiving and robust data protection
My favorite part of this job is getting to talk to our customers, learn about their business, and learn how Hammerspace has helped them. NOV, a global energy technology company, has a great story with some really cool elements that apply broadly to the markets we serve.
Here’s the story…
The Challenge: Collaboration Across Cloud Regions Impacted by High Latency and Sync Issues
Within NOV, a centralized 3D animation and visualization team sits inside corporate marketing and supports a broad range of business units – creating high-resolution imagery and 3D renderings to support their sales efforts. The team operates out of two AWS regions in the US and EMEA.
The team initially used cloud gateway solutions, combined with manual data copying, and this resulted in latency issues – sometimes taking 10 seconds just to open a file – plus broken render workflows.
The Solution: A Global Namespace that Spans AWS Regions, with Policy-Based Data Orchestration
NOV’s cloud architect discovered Hammerspace through the AWS Marketplace, installed it independently, and moved into production as a global namespace spanning the AWS US and EMEA regions. The highlights of the Hammerspace solution include:
- Unified Global Namespace: Two Hammerspace clusters in two AWS cloud regions are deployed as a global file system, allowing artists worldwide to collaborate on the same file set.
- High-Performance Multi-Protocol Access: Seamless integration with Windows workstations via SMB and Linux-based render farms via NFS.
- Automated Data Tiering: Active project data resides on high-performance SSD storage, while inactive data is automatically offloaded to AWS S3 using policy-based automation without breaking file paths or workflows.
- Render Farm Consolidation: Hammerspace enabled NOV to consolidate from two regional render farms into one farm in the US, simplifying its entire infrastructure.
The Outcomes: Improved Productivity and Simplified Operations
- 10% to 20% Increase in Productivity: By removing the frustration of waiting for files to sync or folders to load, the team works significantly more efficiently.
- Seamless “Follow the Sun” Collaboration: Artists in Europe can finish their day, and US-based artists can immediately pick up the same files and continue working without data migration delays.
- Automated Lifecycle Management: NOV’s animation team no longer manually “cleans up” storage; Hammerspace automatically manages the transition from high-performance flash to low-cost S3, maintaining file links even for years-old projects.
- Reduced IT Overhead: With a “hands-off” approach to data management, a small team can manage a complex global pipeline without dedicated technical staff for data movement.
Why This Win Matters for All of the Markets and Customers We Serve
You may look at this story and say “this only applies to animation or rendering” – but the challenges that NOV addressed are challenges we are hearing from a lot of companies. Here are the common characteristics I see:
Requirement for High-Performance Computing: At NOV it was rendering, which is highly-parallel, data-intensive, and extremely sensitive to latency and throughput. But those same characteristics apply to many types of high-performance computing, including AI, across financial services, life sciences, product design and manufacturing, and many other industries. Hammerspace excels at these types of workloads, thanks to our standards-based parallel file system architecture.
Hybrid-Cloud and Multi-Cloud Workloads: NOV runs at AWS-based animation and render pipeline. But many organizations now want to run their computing workloads in the cloud – because they can rent the resources, because that’s where GPUs are available, and because the hyperscalers have available storage capacity. (See my last blog on the SSD Crisis.) With Hammerspace you can unity on-prem and cloud environments into a global namespace, then automate the flow of data between sites and cloud regions based on policy.
Multi-Site Collaboration: At NOV, they have teams of artists across the US and EMEA. But this applies to any organization with geographically distributed teams of data scientists, engineers, analysts, researchers – where those users have a need to work on a common set of data.
You can read the full case study here
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