Cross-Cloud Identity Federation: Patterns That Replaced Our Long-Lived Keys

About two years ago we had AWS access keys in twenty places: GitHub Actions secrets, GCP secret manager, a few engineer laptops, a couple of CI runners, one or two long-running EC2 instance profiles that should have been roles. Each one was a credential we'd have to find and rotate if anything leaked. Today we have zero long-lived cloud access keys outside of break-glass and one legacy integration we haven't migrated. This post is the federation patterns that got us there.

The shape of the problem #

Long-lived credentials are the bottom rung of cloud security. They:

Are valid for months or years until you rotate them
Get copy-pasted into CI secrets, env files, dev laptops
Don't expire when an employee leaves
Are hard to inventory — you don't know where each one ended up
Leak in surprisingly many ways (a misconfigured logging line, a public repo push, a screenshot)

The fix is to replace them with short-lived tokens issued at the moment of use. AWS, GCP, and Azure all support this via OIDC trust relationships: an external identity provider (GitHub Actions, GCP, another AWS account, etc.) presents a signed JWT; the target cloud verifies it; if the trust policy matches, it issues a credential good for ~1 hour.

No persistent secret on the calling side. The credential expires before you'd even notice it got logged.

The trust model in one paragraph #

Federation works because both sides know how to verify a JWT. The caller's identity provider signs the JWT with a key whose public part is published at a well-known URL (the JWKS endpoint). The target cloud fetches that public key, verifies the signature, and checks the claims in the JWT against a trust policy — rules like "this JWT must be issued by GitHub Actions, for the repo company/api, on a push to main." If all the claims match, the cloud hands back a short-lived access token (an AWS STS credential, a GCP service account token, etc.).

You configure the trust policy on the target side once. The caller side just needs to request its JWT (the CI platform or the cloud SDK does this for it) and exchange it.

GitHub Actions → AWS #

The most common path. Pattern:

Create an IAM role in AWS with a trust policy that accepts GitHub Actions' OIDC token under specific conditions:

json.json

{
  "Version": "2012-10-17",
  "Statement": [{
    "Effect": "Allow",
    "Principal": {"Federated": "arn:aws:iam::123456789012:oidc-provider/token.actions.githubusercontent.com"},
    "Action": "sts:AssumeRoleWithWebIdentity",
    "Condition": {
      "StringEquals": {
        "token.actions.githubusercontent.com:aud": "sts.amazonaws.com"
      },
      "StringLike": {
        "token.actions.githubusercontent.com:sub": "repo:company/api:ref:refs/heads/main"
      }
    }
  }]
}

The sub condition is the security boundary. It says "this role can only be assumed from the company/api repo on the main branch." A different repo or a feature branch can't assume it.

In the workflow:

yaml.yaml

permissions:
  id-token: write    # required for OIDC token issuance
  contents: read

steps:
  - uses: aws-actions/configure-aws-credentials@v4
    with:
      role-to-assume: arn:aws:iam::123456789012:role/github-deploy
      aws-region: us-east-1

After this step, the runner has temporary AWS credentials valid for the workflow run. No AWS_ACCESS_KEY_ID secret.

GitHub Actions → GCP #

Same shape, different ceremony:

Create a Workload Identity Pool + Provider in GCP that accepts GitHub's OIDC issuer.
Bind a service account so the pool's principal can impersonate it.
In the workflow:

yaml.yaml

- uses: google-github-actions/auth@v2
  with:
    workload_identity_provider: 'projects/123/locations/global/workloadIdentityPools/gh-pool/providers/gh-provider'
    service_account: 'deploy@my-project.iam.gserviceaccount.com'

The workflow gets a GCP access token for that service account. Same idea, different config surface.

AWS → GCP (workload-to-workload)#

Less common but useful when a workload running on AWS needs to write to a GCP bucket. Pattern:

AWS workload (Lambda, ECS task) has an IAM role.
GCP Workload Identity Pool trusts STS web-identity tokens from that IAM role's session.
AWS workload calls sts.GetCallerIdentity → gets a signed identity token → exchanges it at GCP for a service-account access token.

The bidirectional version exists too (GCP→AWS) with similar shape. We use this for analytics — Lambda functions on AWS that push data into BigQuery without storing GCP credentials.

The trust policy is your security boundary #

This is where most federation setups go wrong. The trust policy controls who can use this role. Get it wrong and you've replaced a leaked key risk with a "anyone can assume your role" risk.

What we enforce in every trust policy:

Specific repo + branch. repo:company/api:ref:refs/heads/main. Not repo:company/* (any repo). Not repo:company/api:* (any branch). Specific.

Audience claim. AWS requires aud = sts.amazonaws.com. Always set explicitly.

Environment claim (when using GitHub Actions environments). environment:production — restricts which environment can assume the role. Especially useful for prod-only roles.

StringEquals over StringLike where you can. Pattern matching is for cases that genuinely need it; exact match is safer.

We had one setup early on where StringLike was used with a * that was a typo and accidentally matched too much. Caught it in a security review; would have been bad in a breach. Specificity over flexibility.

What we federated, in order #

The migration took about a year, prioritized roughly by risk:

GitHub Actions → AWS (most credentials we had stored)
GitHub Actions → GCP (same pattern, fewer credentials)
EC2 instance roles — replaced any access-key-on-instance with proper IAM instance profiles
Cross-account AWS roles — internal accounts assuming roles in others via STS rather than embedded keys
AWS → GCP workload federation (analytics path)
Engineer-laptop SSO via AWS Identity Center for ad-hoc CLI work

After step 6, all that remained was one legacy integration with a partner service that doesn't support OIDC. That one stays on a long-lived key, rotated quarterly, scoped narrowly.

What we measure #

Long-lived credential count — target zero. We scan for AWS access keys via AWS Config rules + a custom audit.
Credential age distribution — for any remaining keys, the oldest. The legacy one is rotated quarterly.
Federation success rate — federation can fail (token verification timeout, IdP outage). Alert if failures spike.

Common mistakes #

Over-permissive trust policies. repo:company/* accepts any repo in the org. Use the specific repo.

Forgetting id-token: write. GitHub Actions workflows need this permission to request an OIDC token. Without it, the federation step fails with a confusing error.

Hard-coding the audience. GCP and AWS both have audience values; using the wrong one fails verification. Read the docs for the target.

Long session durations. AWS roles default to 1-hour sessions; you can raise to 12 hours. We keep them at 1 hour for CI roles. Longer sessions = more blast radius if a runner is compromised mid-run.

Same role for too many things. A "general deploy" role with all the permissions for everything. Defeats the security benefit. We have separate roles per service or per environment.

What to read next #

Cloud security best practices: securing AWS infrastructure — broader AWS security baseline that federation fits into
Zero trust architecture in multi-cloud — federation is one piece of the broader pattern
SSH tutorial — keys, config, and working remotely — the human-access side of credential management

Federation is one of those cleanup projects where the moment you finish it, you wonder how you ever lived without it. Long-lived access keys in CI secrets and env files just become a thing you stopped doing. The trust-policy discipline is the part that takes practice; the rest is mechanical.

#Identity

Cross-Cloud Identity Federation — Patterns That Replaced Our Long-Lived Keys