6 Organizations have distributed data and AI workloads: on-premises, multiple clouds, and edge locations. Designing backup for this distribution requires rethinking backup infrastructure. Pure on-premises solutions leave cloud data dependent on cloud-native services. Pure cloud solutions create data gravity—expensive egress moving data between clouds. Hybrid backup combines on-premises and cloud infrastructure for both benefits. On-premises infrastructure serves on-premises with low latency. Cloud infrastructure serves cloud workloads flexibly. Data tiers between storage based on access and cost. The architecture reflects reality: data lives everywhere. This post covers architecting hybrid backup for AI workloads, managing data gravity and egress, and ensuring backup serves your infrastructure rather than constraining it. The Distributed Reality: Why Hybrid Backup Is Necessary Most organizations operate across multiple locations. Cloud services offer economical capabilities. Multi-region deployment improves availability. Different workloads have different requirements. This distributes data across locations and providers. For AI, distribution is pronounced: training data on-premises, training in cloud, feature stores in cloud, inference in multiple regions. Backups must protect data everywhere. Single-location strategies create problems. On-premises-only requires backing up all cloud data on-premises. This adds network overhead, increases latency, and tightly couples systems. Cloud-only strategies create lock-in and data gravity. If all backups are in one region, recovering on-premises requires transferring data over internet with significant egress costs. Multiple providers create complexity with different tools. Hybrid backup addresses this by distributing backup infrastructure across locations, optimized for each location. Tiering Backup Infrastructure: Locality and Performance Deploy backup targets at multiple locations, optimized for local workloads and data. On-premises backup infrastructure serves on-premises workloads. This might be object storage, traditional appliances, or both. Optimization focuses on speed—LAN throughput enables fast backups and recoveries. Size infrastructure based on local data and characteristics. Cloud backup infrastructure serves cloud workloads. AWS data gets AWS backup infrastructure. Azure data gets Azure infrastructure. On-premises Kubernetes gets hybrid tools. The principle: deploy backup close to protected data. The advantage is performance. Backups to local infrastructure are fast. Recovery from local infrastructure is quick. No internet round trips. No expensive egress. This locality simplifies operations. Each system manages discrete data and workloads. Regional cloud systems manage regional backups. On-premises systems manage on-premises backups. Teams specialize in their regions rather than managing multiple clouds. Data Tiering: Balancing Cost and Accessibility Beyond multiple locations, hybrid backup implements tiering moving data between storage tiers by age, frequency, and cost. A typical strategy: recent backups on fast storage (SSDs, high-performance object storage). Medium-age backups on standard storage. Old, rarely accessed backups on archive (AWS Glacier, Azure Archive). This balances quick recovery against cost. For hybrid, tiering considers location. Recent cloud database backups stay in cloud storage for quick recovery. Older backups archive to on-premises or cloud archive using cloud vs local storage strategies. Recovery eventually retrieves from archive, avoiding expensive long-term immediate-access storage. Tiering decisions should reflect actual recovery patterns. For critical databases requiring fast recovery, keep recent backups on fast local storage. For archive data rarely accessed, cheaper storage makes sense. Match tier decisions to requirements. Data Gravity and Egress Cost Management Data gravity is crucial: the cost and complexity of moving large data between locations. Cloud egress—moving data out of cloud regions—is expensive. Hybrid architectures inadvertently requiring terabytes out of cloud incur staggering costs. Effective hybrid backup manages data gravity explicitly. Keep data where recovery most likely occurs. If data is backed up in cloud because workloads run there, store backups in cloud. Don’t replicate to on-premises because it’s “primary”—replication incurs egress costs. This requires discipline understanding recovery patterns. For each data class, ask: where does it run? Where recover most likely? Where should primary backup be? Where secondary copies? For AI, training data backups co-locate with training infrastructure. AWS training means AWS backups. Feature stores backup where serving happens. Model checkpoints backup where training occurs. This doesn’t prevent cross-location copies for disaster recovery. It means primary, frequent-access backups co-locate with protected workloads. Secondary copies can be elsewhere for disaster recovery. Unified Management Across Distributed Backup Infrastructure The operational challenge is managing distributed backup infrastructure without unified management. Without it, you maintain separate tools for each location, defeating hybrid benefits. Unified management layers abstract distributed infrastructure. Rather than managing on-premises and cloud separately, manage a single system understanding entire infrastructure. Define policies once, apply consistently. Provide visibility across all. Orchestrate recovery across all. Unified management might use purpose-built orchestration platforms or cloud-native multi-cloud tools. The principle matters: backup operations should be unified, not fragmented. Unified management simplifies compliance and audit. Audit through single interface. Enforce retention consistently. Maintain encryption uniformly. Disaster Recovery in Hybrid Architectures Hybrid backup requires explicit disaster recovery planning. If primary location fails, how do you recover? Where are copies? Can you recover quickly? In hybrid, maintain secondary copies in alternate locations. On-premises databases have on-premises primaries and cloud secondaries. Cloud training has cloud primaries and on-premises secondaries. Use enterprise backup strategy accounting for RTO vs RPO. If primary is inaccessible, alternate locations have recoverable data. This requires network connectivity between locations and replication processes. Replication should be asynchronous and scheduled off-peak to avoid impacting workloads. The goal is disaster recovery without continuous overhead. Building Your Hybrid Backup Architecture Effective hybrid backup starts with mapping where data lives and where recovery happens. Deploy backup infrastructure close to data. Implement tiering balancing cost against requirements. Manage data gravity explicitly. Implement unified management for visibility and consistency. Organizations managing hybrid backup effectively treat it as strategic architecture, not necessity. They invest in unified tools, implement tiering thoughtfully, understand data gravity costs, and make deliberate placement decisions. They test disaster recovery regularly. As infrastructure becomes increasingly distributed, hybrid backup becomes necessary for managing protection. Build intentionally, measure continuously, and invest in tools providing unified management and visibility across infrastructure. Further Reading RTO vs RPO: Key Differences Explained DRaaS: Disaster Recovery as a Service Multi-Cloud Storage: Architecture, Benefits, and Strategy Tiered Storage for AI: Scalable Performance and Cost Control Hybrid Cloud Data Strategy for AI Workloads Scalable Backup Target Architecture
