Tag: Workload Identity

Compare 10 identity security vendors for AI agents, including where each fits and what buyers should examine before choosing.
AI agents are workloads, but traditional workload identity alone can miss the user, task, and runtime context needed to govern dynamic agent access.
As AI agents begin calling tools and APIs, OAuth moves from background plumbing to a core access-control question.
AI agents need identity controls, scoped access, and runtime enforcement before they are trusted with production systems.
AI agents need more than working credentials. They need verifiable identity, task-scoped access, and clear attribution.
Your Azure Databricks pipelines need access to cloud and SaaS services, but they should not have to carry permanent credentials to get it.
Eliminating static API keys is real progress – but securing one credential surface is not the same as governing workload access at scale.
A working prototype can mask the harder problem: keeping every workload, agent, credential, policy, and audit trail consistent across production environments.
An early IETF draft hints at how identity infrastructure may evolve once autonomous software starts acting inside enterprise environments.
See how Aembit injects database credentials at connection time without requiring application code changes or stored Oracle passwords.