How do permission models differ across clouds?

AWS evaluates permissions by combining identity policies, resource policies, SCPs, permission boundaries, and session policies — an action must not be denied by any layer and must be explicitly allowed. Azure RBAC uses additive role assignments at scopes (management group, subscription, resource group, resource) with no explicit deny (NotActions are exclusions, not denies, though deny assignments exist in limited scenarios). GCP binds members to predefined or custom roles on resources, with organization policies providing guardrails. OCI uses a unique verb-based policy language (Allow group X to manage Y in compartment Z) applied at compartment scopes.

How do service accounts and machine identities compare?

AWS uses IAM instance profiles (for EC2) and execution roles (for Lambda, ECS) — there is no separate service account resource. Azure has Managed Identities (system-assigned tied to a resource, user-assigned as standalone resources). GCP has explicit Service Accounts that are both identities and resources, with key files or Workload Identity for authentication. OCI uses Instance Principals (similar to AWS instance profiles) and Dynamic Groups that match resources by compartment or tag. The key trend across all clouds is moving away from long-lived credentials toward identity federation and managed identities.

Multi-Cloud IAM Compare

IAM & SecurityMulti-Cloud

Compare IAM models, policies, and identity federation across AWS, Azure, GCP, and OCI.

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About This Tool

Identity and Access Management implementations differ significantly across AWS, Azure, GCP, and OCI in their fundamental models, policy languages, and federation capabilities. AWS uses policy documents with explicit Deny/Allow evaluated against principals, Azure uses role definitions with Actions/NotActions assigned at scopes, GCP uses IAM bindings that map members to roles on resources, and OCI uses compartment-based policies with a natural language syntax. This comparison tool helps you understand the mapping between IAM concepts across all four clouds, including roles, policies, identity federation, service accounts, and permission boundaries.

When to Use This Tool

•Mapping AWS IAM roles and policies to their Azure RBAC, GCP IAM, and OCI equivalents during multi-cloud architecture design
•Understanding how identity federation (SAML, OIDC) is configured differently across each cloud provider
•Comparing service account and machine identity models (IAM roles for EC2 vs managed identities vs service accounts vs instance principals)

Frequently Asked Questions

How do permission models differ across clouds?: AWS evaluates permissions by combining identity policies, resource policies, SCPs, permission boundaries, and session policies — an action must not be denied by any layer and must be explicitly allowed. Azure RBAC uses additive role assignments at scopes (management group, subscription, resource group, resource) with no explicit deny (NotActions are exclusions, not denies, though deny assignments exist in limited scenarios). GCP binds members to predefined or custom roles on resources, with organization policies providing guardrails. OCI uses a unique verb-based policy language (Allow group X to manage Y in compartment Z) applied at compartment scopes.
How do service accounts and machine identities compare?: AWS uses IAM instance profiles (for EC2) and execution roles (for Lambda, ECS) — there is no separate service account resource. Azure has Managed Identities (system-assigned tied to a resource, user-assigned as standalone resources). GCP has explicit Service Accounts that are both identities and resources, with key files or Workload Identity for authentication. OCI uses Instance Principals (similar to AWS instance profiles) and Dynamic Groups that match resources by compartment or tag. The key trend across all clouds is moving away from long-lived credentials toward identity federation and managed identities.

Related Learning Guides

Multi-Cloud IAM Rosetta Stone12 min read

Disclaimer: This tool runs entirely in your browser. No data is sent to our servers. Always verify outputs before using them in production. AWS, Azure, and GCP are trademarks of their respective owners.