Local by Design: The dawn of the Distributed Storage Era.
The conventional wisdom has been simple: pick a major cloud provider, move your workloads there, and sleep soundly.
For years, this approach worked well enough. But as organizations scale operations, deploy AI/ML workloads, serve increasingly global customer bases, and navigate complex data sovereignty requirements, putting all your eggs in one basket starts to look less like best practice and more like concentrated risk.
Recent events prove the point. AWS suffered a significant outage in its US-EAST-1 region that cascaded globally, taking down countless websites and applications. The culprit was a DNS resolution issue in the EC2 internal network that impacted the DynamoDB API endpoint. Services went offline for hours. Millions of users were affected. And businesses everywhere got a sharp reminder that scale doesn’t equal invulnerability.
This isn’t about singling out AWS. They’re good at what they do. But the incident highlights exactly why smart data strategies now embrace distributed storage architectures that combine cloud infrastructure with private, on-premises, and sovereign capabilities.
The strategic advantages
Eliminating single points of failure
Concentrating all your data in one region, vendor, or availability zone creates obvious exposure. Configuration errors happen. Outages cascade. Regulatory environments shift. Geopolitical tensions flare. When AWS’s US-EAST-1 region stumbled, dependent services had nowhere to fail over. Building alternate storage locations across private cloud, on-premises systems, and sovereign infrastructure gives you genuine redundancy, not just the illusion of it.
Performance where it counts
Data locality matters more as use cases evolve. AI inference workloads, IoT analytics, edge computing, and latency-sensitive applications all benefit from storage that sits physically closer to where processing happens. A storage tier in your target region or jurisdiction delivers measurably faster responses and better user experiences. For organizations running ultra-low latency workloads, this isn’t optional.
Meeting sovereignty and compliance requirements
Regulated industries face mounting pressure to prove where data lives, who controls it, and which laws govern its use. Financial services firms, government agencies, and critical infrastructure operators increasingly need data to remain within specific jurisdictions, under explicit local control. A sovereign storage component in your architecture makes these conversations with regulators, auditors, and boards dramatically simpler.
Controlling costs and maintaining flexibility
Major cloud providers offer impressive scale, but that scale comes with pricing structures, geographic limitations, and egress charges that can constrain your options. A hybrid, distributed approach lets you optimize workload placement based on cost, compliance, and performance requirements. Less critical workloads can shift to lower-cost local storage. Frequently accessed data stays close to users. You retain the ability to adjust as conditions change.
Building competitive advantage
Organizations that control data placement and maintain flexible architectures extract more value from emerging technologies. Localized AI models, real-time analytics, federated learning frameworks, all perform better when storage infrastructure adapts to their needs. Treating storage as a static utility leaves you flat-footed. Building adaptable infrastructure that spans cloud, local, and sovereign options positions you ahead of competitors still locked into monolithic approaches
Five Critical Design Considerations
1. Classify data by criticality and recovery requirements
Start with an honest assessment. Which datasets need recovery within minutes? What can tolerate hours or days of downtime? Which workloads demand ultra-low latency access? Use these classifications to map data placement. Mission-critical systems might span global cloud and sovereign backup. Archive data might live entirely on-premises. Performance-sensitive AI workloads might require local storage tiers. One size fits nothing.
2. Build in geographic and vendor diversity
Avoid architectural lock-in from day one. Design systems that can distribute storage and backups across multiple providers and locations. Consider patterns like primary data in global cloud, mirrored backups in sovereign facilities, and tertiary archives on-premises. This way, provider-specific failures or regional issues don’t cascade into total outages.
3. Match storage topology to access patterns
If your workloads involve AI/ML inference near data sources, IoT edge computing, or serving users in specific regions, physical and logical proximity matters enormously. Both latency and data movement costs add up quickly. Local storage tiers reduce both while improving performance for the applications that need it most.
4. Integrate sovereignty requirements from the start
Boards, regulators, and customers increasingly ask pointed questions. Where does our data reside? Who controls access? Which jurisdiction’s laws apply? How are backups managed? Incorporating sovereign storage nodes that answer these questions clearly makes compliance demonstrably simpler. Retrofitting sovereignty into existing architectures costs far more than building it in from the beginning.
5. Implement operational rigor
Distributed storage means nothing without operational discipline. Regular backup validation, failover testing, versioning practices, data integrity verification, and clear governance processes all matter. You need proven ability to fail over between cloud, local, and private infrastructure. You need visibility into dependencies. You need understanding of cost, latency, and regulato
Why this matters now
Geopolitical uncertainty, supply chain disruptions, evolving regulations, and operational complexity are pushing executives to confront uncomfortable questions about data control. The AWS outage crystallized what many already suspected. Dependency on any single provider, regardless of their scale or reputation, introduces risk that boards and regulators won’t tolerate indefinitely.
This transforms data management from an IT implementation detail into a strategic consideration. Data location, distribution patterns, backup resilience, latency characteristics, and sovereignty guarantees now appear in board presentations. Organizations with well-architected distributed data strategies gain competitive advantage, not just defensive protection.
The Exaba LocalScale approach
Exaba’s LocalScale solution addresses these requirements directly. By providing sovereign, locally-anchored storage and backup infrastructure that integrates with both global cloud platforms and private systems, LocalScale enables genuinely distributed architectures.
When major cloud providers experience issues, your data assets remain accessible locally, under your governance, ready for use. Latency-sensitive workloads like AI inference and edge computing run closer to data sources. Your board gets clear answers about data jurisdiction, backup procedures, and regulatory compliance.
The point isn’t choosing between cloud and local infrastructure. It’s building layered strategies that leverage cloud scale while maintaining private control and local sovereignty where it matters. The AWS incident serves as a useful reminder. Even the largest players face outages. Your architecture should assume this reality, not hope against it.
Storage and backup deserve strategic thinking, not default decisions. Get the architecture right, and data management becomes an enabler rather than a constraint.
Exaba™ – Built for here. Built for you.