As cloud engineers, architects, or consultants, we often hop between cloud platforms—designing, deploying, and managing infrastructure. One thing remains central across these platforms: Identity and Access Management (IAM).
Control who can do what, where, and under what conditions.
But how each cloud enforces this principle is where the real difference lies.
The Similarities
Across AWS and GCP, IAM shares these key traits:
Access Control: Both platforms allow you to define who can access specific resources and what actions they can perform.
Least Privilege Principle: They enforce minimal access by default, encouraging the principle of least privilege.
Policy-Based Authorization: Both use a policy model (GCP uses role bindings; AWS uses policies attached to identities).
Resource-Level Granularity: You can define permissions at very specific resource levels in both platforms.
The Differences
Though the goal is shared, their approaches diverge significantly:
AWS IAM — Flat and Direct
Identity Types: AWS uses IAM users, groups, roles, and policies. Roles are often assumed via STS, especially in cross-account scenarios.
Flat Resource Structure: AWS does not enforce a strict hierarchy. Policies are scoped directly to identities or resources.
Policy Syntax: AWS policies are written in JSON using Action-Resource-Effect models ("Effect": "Allow", "Action": "s3:GetObject", "Resource": "...").
Service Control Policies (SCPs): Used in AWS Organizations for central governance, but not tied directly to standard IAM roles.
✅ In AWS, IAM is straightforward but requires careful policy management to avoid over-permissioning.
GCP IAM — Granular and Hierarchical
Hierarchical Resource Model: GCP resources live in a hierarchy—Organization → Folder → Project → Resources.
Inheritance: IAM roles and permissions cascade down from the organization level to the resources.
Predefined & Custom Roles: GCP uses role bindings to assign roles (which are sets of permissions) to members at a specific scope.
No User Management in IAM: GCP IAM doesn't manage users directly—it leverages Google identities (Google Workspace, Cloud Identity).
✅ GCP’s IAM is highly granular and encourages structured, scalable access control through scopes and inheritance.
Why This Matters
Understanding how IAM works in each cloud is critical for:
✅ Designing secure architectures
✅ Managing multi-cloud environments
✅ Preventing privilege escalation
✅ Complying with organizational governance
IAM is not an afterthought—it’s 50% of cloud work. The rest? Implementing services securely with IAM as the foundation.
Final Thoughts
Whether you're working in AWS, GCP, or both, mastering IAM is core to being a strong cloud engineer. The tools and terminology may differ, but the responsibility remains the same—grant the right access to the right resources at the right time.
If you're just diving into GCP or AWS, start with IAM. It will shape how you design everything else in the cloud.
Let me know in the comments how your IAM experience differs across cloud platforms!
Top comments (0)