Video production and analysis workflows generate enormous data volumes. A single project can involve terabytes of raw footage, transcoded intermediates, and final renders—each stored across multiple locations and accessed by multiple team members simultaneously. Traditional approaches centralize this data, but centralization introduces latency for distributed teams and single points of failure for mission-critical workflows.
The challenge. A client operating across multiple European offices needed to process and annotate video content in near real-time. The latency of downloading clips from a central server, annotating locally, and syncing back was slowing their editorial cycle to hours per iteration. Cloud storage alone did not solve the problem—random-access patterns for video editing are fundamentally different from the sequential reads that cloud object stores optimize for.
The solution: distributed virtual disk. We implemented a scalable VPN connecting cloud compute nodes to a distributed virtual disk layer backed by cloud object storage. The virtual disk presents a POSIX-compatible filesystem interface to applications, so existing video editing and analysis tools work without modification. Under the surface, it uses intelligent prefetching, local caching, and parallel segment loading to deliver near-local performance across WAN links.
The fault-tolerant design ensures that if a node or link fails, the system falls back to direct cloud object access rather than stalling. This resilience was a requirement for the client, whose operations fell under EU public-sector service continuity standards.
Broader applicability. This pattern—distributed caching over object storage with a standard filesystem interface—applies beyond video. Any workload that requires low-latency random access to large datasets stored in cloud object storage benefits from this approach. In government contexts, where data residency requirements (such as those specified in EU procurement tenders) mandate that data remain within specific jurisdictions, the distributed cache can be configured to keep all data within approved boundaries while still providing global access.
The result: editing latency dropped from hours to seconds, and the client's distributed teams could collaborate on the same footage simultaneously without sync conflicts. For organizations navigating cross-border data regulations—from TED procurement requirements to SAM.gov data handling provisions—this architecture provides the compliance guarantees of centralized storage with the performance of local access.