Jonas Weber·
Mapped my AWS-primary GCP-secondary setup and warned me the S3-to-GCS egress would be the killer
Designs a resilient multi-cloud or hybrid cloud architecture with workload distribution, data synchronization, and vendor-agnostic infrastructure patterns.
Multi-Cloud & Hybrid Architecture
Act as a Cloud Infrastructure Architect who has built multi-cloud systems across AWS, GCP, and Azure. Design a multi-cloud architecture.
**Workload Distribution Strategy**: {{workload_distribution_strategy}} (best-of-breed, failover, cost-optimization, regulatory)
**Primary Cloud**: {{primary_cloud}} (AWS/GCP/Azure and specific services heavily used)
**Secondary Cloud(s)**: {{secondary_clouds}} (which clouds for which purposes)
**Data Residency Requirements**: {{data_residency_requirements}} (regions, data classification, transfer restrictions)
**On-Premises Integration**: {{on_premises_integration}} (existing data centers, legacy systems, VPN/Direct Connect)
Provide:
1. **Architecture Diagram** - Visual topology showing workload placement per cloud with data flow arrows
2. **Service Mapping Matrix** - Equivalent services across AWS/GCP/Azure (e.g., S3=GCS=Blob Storage)
3. **Network Connectivity** - VPN, Direct Connect, Cloud Interconnect, ExpressRoute, private backbone design
4. **Identity Federation** - Cross-cloud IAM with SAML/OIDC, unified identity provider (Okta/Azure AD)
5. **Data Synchronization** - Real-time sync (CDC with Debezium), batch sync (Airflow/dbt), conflict resolution strategy
6. **Service Mesh** - Istio/Linkerd across clusters in different clouds, mTLS everywhere, traffic splitting
7. **Cost Optimization** - Spot instance arbitrage, data egress minimization, reserved commitment strategy per cloud
8. **Disaster Recovery** - Active-active vs active-passive, DNS failover (Route53 + Cloud DNS + Azure DNS)
9. **Vendor Lock-in Mitigation** - Kubernetes as abstraction layer, Terraform multi-provider, open-source over managed services
10. **Security Architecture** - Unified SIEM (Splunk/Datadog), cross-cloud security posture (Prisma Cloud), secrets sync
11. **Observability** - Single pane of glass (Grafana Cloud), unified logging, distributed tracing across clouds
12. **Migration Playbook** - Step-by-step migration of specific workloads from primary to secondary without downtime
Include a comparison table of equivalent services with pricing notes.
Ergebnisse
Multi-cloud design: **AWS primary** (compute, app data) + **GCP secondary** (BigQuery analytics, DR). Strategy is best-of-breed, not blind redundancy — you only pay the cross-cloud tax where it earns its keep.
**Service mapping**
| Concern | AWS | GCP | Notes |
|---------|-----|-----|-------|
| Object storage | S3 | GCS | egress is the cost killer — replicate, don't dual-read |
| Warehouse | Redshift | **BigQuery** | analytics lives here, on-demand pricing |
| Managed K8s | EKS | GKE | same Helm charts, Terraform multi-provider |
| Identity | — | — | Okta federates both via OIDC |
**Connectivity:** AWS Direct Connect + GCP Partner Interconnect into a shared transit hub; no traffic over the public internet between clouds. **Data sync:** Debezium CDC streams Postgres changes → Kafka → BigQuery loader (near-real-time analytics without touching the OLTP path). Conflict resolution is last-writer-wins keyed on a logical clock since GCP is read-mostly.
**Lock-in mitigation:** Kubernetes is the portability layer — workloads are plain containers, infra is Terraform with `aws` and `google` providers in one root module. **DR:** active-passive. Route53 health checks fail GCP-ward only on a full AWS-region outage; RTO ~20min. **Cost note:** the single biggest line item is S3→GCS egress — we minimize it by exporting only aggregated tables, not raw events.
Modell: Claude Opus 4
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