multi-cloud-architecture

Design a multi-cloud architecture by using a decision framework to map compute, storage, and database needs across AWS, Azure, and GCP, selecting compatible services to avoid vendor lock-in. The framework provides cloud-agnostic patterns and migration guidance for workloads.

The best way to avoid vendor lock-in is applying a cloud-agnostic decision framework that evaluates cross-provider services for compute, storage, and databases. This approach maximizes flexibility by selecting compatible, cost-effective services across AWS, Azure, and GCP.

Yes, the multi-cloud strategy includes cost-aware architecture design with best practices for inter-cloud connectivity. It integrates cost optimization and disaster recovery considerations into the decision framework for selecting cross-provider compute, storage, and database services.

Migrate workloads using the provided migration guidance and cloud-agnostic patterns. The framework supports workload migration by mapping service requirements across AWS, Azure, and GCP to ensure compatible compute, storage, and database integration during the transition.

You should reconsider a multi-cloud architecture when inter-cloud connectivity costs and operational complexity outweigh the benefits of avoiding vendor lock-in. If workloads rely heavily on provider-specific managed services, maintaining cloud-agnostic patterns becomes impractical.

Yes, Terraform and Kubernetes align with cloud-agnostic patterns to manage cross-provider architectures. The decision framework integrates these tools to standardize compute, storage, and database deployment across AWS, Azure, and GCP while avoiding vendor lock-in.