Grab Builds Secure Agentic AI Workload Platform
📰 InfoQ AI/ML
Learn how Grab's Palana platform securely runs autonomous AI agents using Kubernetes-native infrastructure
Action Steps
- Build a Kubernetes-native platform using isolated namespaces to contain AI agent threats
- Configure out-of-process control planes to manage AI agent workflows
- Implement proxy-mediated, Vault-backed secrets to secure sensitive data
- Test Palana's secure execution platform with autonomous AI agents
- Deploy Palana to production using Kubernetes deployment tools
Who Needs to Know This
Security teams and AI engineers can benefit from Palana's secure execution platform to run autonomous AI agents safely and efficiently
Key Insight
💡 Palana's infrastructure-level security features mitigate unpredictable risks from model-driven AI agents
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🚀 Securely run autonomous AI agents with Palana, Grab's Kubernetes-native platform! 🚀
Key Takeaways
Learn how Grab's Palana platform securely runs autonomous AI agents using Kubernetes-native infrastructure
Full Article
Grab's security team built Palana, a Kubernetes-native secure execution platform, to run autonomous AI agents safely. Unlike deterministic software, model-driven agents exhibit unpredictable tool-use, code-writing, and prompt injection risks. Palana contains these threats at the infrastructure level using isolated namespaces, out-of-process control planes, and proxy-mediated, Vault-backed secrets. By Patrick Fa
DeepCamp AI