How do I configure IT infrastructure for hybrid cloud data sharing?

Configuring IT infrastructure for hybrid cloud data sharing means integrating on-premises and cloud environments so data moves securely, performs well, and scales. Here are the steps and considerations.

1. Define Business Requirements

Data Types: Identify what you’re sharing — structured, unstructured, sensitive, regulated.
Use Cases: Analytics, disaster recovery, collaboration, burst compute — each drives different architecture.
Compliance: Map requirements (GDPR, HIPAA, PCI-DSS) to data residency and encryption controls.

2. Assess Existing Infrastructure

On-Premises: Inventory servers, storage arrays, network gear, and current utilization.
Cloud Provider: Pick based on workload fit, egress costs, and existing skill sets (AWS, Azure, GCP).
Connectivity: Measure baseline bandwidth, latency, and jitter between sites.

3. Build a Hybrid Cloud Architecture

Management Plane: Platforms like VMware Cloud Foundation, Azure Arc, or Google Anthos give consistent control.
Networking:
- Establish secure connectivity — IPsec VPN, AWS Direct Connect, Azure ExpressRoute, or Google Cloud Interconnect.
- Configure routing (BGP preferred) between datacenter and cloud VPC/VNet.
Storage: Deploy hybrid storage gateways (AWS Storage Gateway, Azure File Sync, NetApp Cloud Volumes ONTAP) for tiering and caching.

4. Implement Data Synchronization

Data Movement: Use Azure Data Factory, AWS DataSync, or Google Cloud Storage Transfer Service for scheduled or event-driven transfers.
File Sharing: NFS/SMB via Amazon FSx for NetApp ONTAP, Azure Files, or Filestore for cloud-native access.
Database Replication: Configure native replication — SQL Server Always On AGs, Oracle Data Guard, PostgreSQL streaming replication — across environments.

5. Configure Backup and Disaster Recovery

Backup: Hybrid-capable platforms (Veeam, Rubrik, Commvault) that write to on-prem targets and cloud object storage.
Disaster Recovery: Azure Site Recovery, AWS Elastic Disaster Recovery, or Zerto for orchestrated failover to cloud.

6. Optimize Security

Encryption:
- At rest: AES-256 on local arrays and cloud buckets (SSE-S3, SSE-KMS, customer-managed keys).
- In transit: TLS 1.2+ everywhere — VPN, Direct Connect MACsec, application-layer mTLS.
Identity and Access:
- Centralize with Entra ID (Azure AD), AWS IAM Identity Center, or Okta.
- Enforce RBAC and conditional access (device trust, location, risk).
Monitoring and Auditing:
- Enable CloudTrail, Azure Monitor logs, or Google Cloud Audit Logs.
- Forward to SIEM (Splunk, Sentinel, Chronicle) for correlation.

7. Integrate Kubernetes for Cloud-Native Applications

Cluster Setup:
- On-prem: OpenShift, VMware Tanzu, or Rancher-managed RKE2.
- Cloud: EKS, AKS, GKE — prefer managed control planes.
Storage: Use CSI drivers (AWS EBS, Azure Disk, NetApp Trident) for PersistentVolumes that span environments.
Service Mesh: Istio or Linkerd for mTLS, traffic splitting, and observability across clusters.

8. Test and Validate

Connectivity: End-to-end iperf3, ping, and application-level health checks.
Performance: Load test with realistic payloads — measure latency percentiles, throughput, and error rates.
Security: Verify encryption in flight (Wireshark), at rest (KMS key policies), and RBAC denial paths.

9. Monitor and Optimize

Observability: Prometheus/Grafana stack or cloud-native (CloudWatch, Azure Monitor, Cloud Operations) with unified dashboards.
Cost: Tag resources, set budgets/alerts in AWS Cost Explorer, Azure Cost Management, or FinOps tools (Cloudability, Kubecost).
Scaling: Cluster autoscaler + HPA/VPA for compute; storage auto-tiering for data.