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HASHICORP VAULT
Secrets management and encryption for ML infrastructure
BUSL-1.1
ABOUT
ML pipelines and model serving systems require access to numerous secrets — API keys for LLM providers, database credentials for feature stores, model registry tokens, and cloud storage keys — each posing a security risk if leaked in code, logs, or environment variables. Vault centralizes secrets management with dynamic credentials (short-lived tokens), automatic rotation, audit logging, and fine-grained access policies. ML teams use Vault to inject ephemeral credentials into training jobs, model serving containers, and CI/CD pipelines without hardcoding secrets in configuration files or worrying about credential expiry.
INTEGRATION GUIDE
1. Securely inject API keys for LLM providers (OpenAI, Anthropic) into training and inference pipelines
2. Manage short-lived database credentials for feature stores and model registries
3. Store and rotate TLS certificates for model serving endpoints and ML infrastructure
4. Audit all credential access across ML pipelines with detailed audit logs
TAGS
securitysecrets-managementencryptiondevopsinfrastructure