Multi-Cloud Security: Scenario-Based Questions

Managing secrets like API keys, DB credentials, and tokens across AWS, Azure, and GCP requires unified governance, secure access control, and automated rotation. Each cloud provides native tools, but coordination is key.

🔐 Centralized Secret Management Approaches

• External Vaults: Use a centralized system like HashiCorp Vault or Doppler to abstract cloud differences.
• Cloud-Native: Combine AWS Secrets Manager, Azure Key Vault, and GCP Secret Manager with synced access policies.
• Environment-Specific Access: Use cloud IAM to control who can read/write which secrets per environment.

⚙️ Access & Rotation Strategies

• Use dynamic secrets or short-lived credentials wherever possible.
• Automate rotation using cloud-native workflows (e.g., Lambda, Azure Functions, Cloud Scheduler).
• Leverage identity federation (e.g., OIDC or workload identity) to reduce static credentials.
• Audit secret access logs across providers and alert on anomalies.

🧰 Tools & Services

• 🔑 Vault: Multi-cloud secret engine, dynamic DB credentials, integrated auth.
• 🧭 Chamber, Secrethub: Environment injection for 12-factor apps.
• 🧪 Checkov, tfsec: IaC scanning for exposed secrets in cloud configs.

✅ Best Practices

• Encrypt secrets at rest and in transit (TLS + KMS/CMK).
• Separate dev/staging/prod secrets — never reuse across environments.
• Scan repos for hardcoded credentials before every merge.
• Rotate keys automatically and document policies.

🚫 Common Pitfalls

• Embedding secrets in source code or Docker images.
• Managing secrets manually or through shared documents.
• Giving overly broad IAM permissions across all clouds.

📌 Real-World Insight

Multi-cloud organizations succeed by abstracting secret management behind APIs, enforcing audit logs, and automating rotation. A secure-by-default baseline prevents sprawl, leaks, and vendor lock-in.