LLMOps
Role-based access control (RBAC) for LLM applications
Learn how Role-Based Access Control (RBAC) helps enterprises build AI applications, control access, ensure compliance, and scale securely.
LLMOps
LLM
What is AI interoperability, and why does it matter in the age of LLMs
Learn what AI interoperability means, why it's critical in the age of LLMs, and how to build a flexible, multi-model AI stack that avoids lock-in and scales with change.
LLMOps
How LLM tracing helps you debug and optimize GenAI apps
Learn how LLM tracing helps you debug and optimize AI workflows, and discover best practices to implement it effectively using tools like Portkey.
Cost reduction
LLM cost attribution: Tracking and optimizing spend for GenAI apps
Learn how to track and optimize LLM costs across teams and use cases. This blog covers challenges, best practices, and how LLMOps platforms like Portkey enable cost attribution at scale.
LLMOps
Scaling and managing LLM applications: The essential guide to LLMOps tools
Learn how to scale your AI applications with proven LLMOps strategies. This practical guide covers observability, cost management, prompt versioning, and infrastructure design—everything engineering teams need to build reliable LLM systems.
LLMOps
What a modern LLMOps stack looks like in 2025
Learn what a modern LLMOps stack looks like in 2025 the essential components for building scalable, safe, and cost-efficient AI applications.
LLMOps
Task-Based LLM Routing: Optimizing LLM Performance for the Right Job
Learn how task-based LLM routing improves performance, reduces costs, and scales your AI workloads
LLMOps
Canary Testing for LLM Apps
Learn how to safely deploy LLM updates using canary testing - a phased rollout approach that lets you monitor real-world performance with a small user group before full deployment.
LLMOps
LLM Grounding: How to Keep AI Outputs Accurate and Reliable
Learn how to build reliable AI systems through LLM grounding. This technical guide covers implementation methods, real-world challenges, and practical solutions
LLM
What is LLM Orchestration?
Learn how LLM orchestration manages model interactions, cuts costs, and boosts reliability in AI applications. A practical guide to managing language models with Portkey
LLMOps
How to improve LLM performance
Learn practical strategies to optimize your LLM performance - from smart prompting and fine-tuning to caching and load balancing. Get real-world tips to reduce costs and latency while maintaining output quality
ai gateway
How to scale AI apps - Lessons from building a billion-scale AI Gateway
Discover the journey of Portkey.ai in building a billion-scale AI Gateway. Learn key lessons on managing costs, optimizing performance, and ensuring accuracy while scaling generative AI applications.