Aembit Server Workload Cookbooks Series | Edition 1: Secure Access to LLMs

Connecting workloads to powerful large language models (LLMs) like OpenAI, Claude, and Gemini presents a unique set of challenges to builders and security teams alike. Traditional methods like static API keys – stored in plaintext, passed through environment variables, or shared across teams – are error-prone, hard to manage at scale, and prone to compromise.

That’s why we created the Aembit Server Workload Cookbooks – a series of practical, step-by-step guides for securely connecting workloads to critical services.

This first edition focuses on AI language models, but the series will expand to include other essential infrastructure like widely deployed databases, SaaS applications, financial services, and cloud platforms – each with clear guidance and reusable patterns for secure integration.

Why Download the Cookbooks?

• Production-Ready Configuration – Step-by-step guides for securely connecting to LLMs like OpenAI, Claude, and Gemini, including endpoint structures, supported authentication schemes, and security best practices.
• Real-World Caveats – Understand how popular SDKs and APIs handle credentials at runtime, including known quirks and potential pitfalls.
• Scalable Security Principles – Shift from static API keys to dynamic, identity-driven, policy-based access controls, reducing your attack surface and operational overhead.
• No Vendor Lock-In – Use these guides with any access management setup – Aembit, cloud-native IAM, or custom scripts – without vendor restrictions.
• Future-Ready Design – Prepare for the next wave of machine identity management with guidance on least privilege, just-in-time credential injection, and real-time conditional access checks.

Download the cookbook (no registration required!) and make scaling your AI infrastructure simpler and more secure.