Avoiding vendor lock-in through the use of open data formats and open, cross-platform, software-only architectures.Moving file-based data rapidly and reliably over any distance and network, at any scale.Enabling multi-cloud and hybrid cloud architectures for customer-specific initiatives using cloud services from providers like Amazon AWS, Microsoft Azure, Google GCP, Oracle, Wasabi, among others.Minimizing cost and complexity by utilizing in-place IT infrastructure (networks, servers, storage, and other devices) to optimize utilization wherever possible.Ensuring that mission critical applications and workflows depending on file data continue operating nonstop, irrespective of location or network quality (no matter how remote or unreliable the network).Having the flexibility and built-in security to support a wide range of enterprise-wide IT initiatives such as remote work, virtual desktop infrastructure (VDI), real-time synchronization, large-scale file distribution, consolidation (ingest), among others.Minimizing downtime and improving high availability and disaster recovery to meet SLAs for recovery times and recovery point objectives and ensuring data protection.Should be easy, right? Well, let’s also consider that IT infrastructure teams may also need solutions for: While storage solutions for unstructured data and cloud file storage have improved over the years, a huge challenge remains:Ĭ oherently managing large and growing data sets (including large files and many smaller files) across storage silos and other devices–spanning any number of locations and endpoints. In our previous blog we covered some history: consolidating on premises file servers to NAS (network-attached storage) to scale-out and cloud NAS. Which path will get you and your file data up the metaphorical mountain the fastest, with enough energy and resources to enjoy the view and get your data back down the hill in a coherent state? ![]() A friend of mine once said: “There are many paths to the top of the mountain.”Īnd so is the case moving and managing massive (and not so massive) unstructured data on a global scale.
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