Master Portkey with our step-by-step tutorial, detailed feature walkthrough, and expert tips.
Create a free Developer account or deploy the open
source gateway locally. Connect provider API keys and configure virtual keys for application access. Point existing OpenAI
compatible model calls at Portkey's gateway endpoint. Add routing, fallback, retry, caching, and budget rules for production traffic. Use observability, prompt management, guardrails, and MCP Gateway controls as workflows mature.
💡 Quick Start: Follow these 3 steps in order to get up and running with Portkey quickly.
Explore the key features that make Portkey powerful for llm gateway & observability workflows.
Portkey is used as a control plane in front of LLM calls. Instead of each application integrating separately with OpenAI, Anthropic, Google, Mistral, AWS Bedrock, Azure OpenAI, Cohere, Together, Fireworks, Groq, and other providers, teams can send requests through Portkey's OpenAI-compatible API. From there, Portkey can apply routing, fallback, load balancing, rate limits, prompt management, observability, cost analytics, and guardrails in one place.
The available site content describes Portkey as working in front of 1,600+ models. It specifically references providers and model sources including OpenAI, Anthropic, Google, Mistral, AWS Bedrock, Azure OpenAI, Cohere, Together, Fireworks, and Groq. That breadth is the main reason Portkey is useful for teams that do not want their application code tightly coupled to one model vendor.
Portkey overlaps with observability tools because it includes per-request tracing and cost analytics. However, its broader role is a gateway and governance layer, not only a tracing dashboard. Based on our analysis of 870+ AI tools, Portkey is better suited when a team also needs routing, fallback, prompt management, guardrails, and MCP Gateway controls, while a lighter observability-only product may be enough for narrower logging and debugging needs.
Yes, Portkey's gateway approach is designed for provider fallback and load balancing. A team can route requests across multiple model providers and use fallback behavior when a provider fails or becomes unsuitable for a request. This is most valuable in production systems where one provider outage could break a customer-facing AI feature.
Portkey's pricing content lists Enterprise capabilities including role-based access control, SSO, granular budget and rate limits, private cloud deployment, VPC hosting, data isolation, SOC 2 Type 2, GDPR, HIPAA, custom BAAs, and data export to data lakes. Teams with strict compliance needs should still verify exact deployment model, data retention behavior, and contractual terms directly with Portkey before purchase.
Now that you know how to use Portkey, it's time to put this knowledge into practice.
Sign up and follow the tutorial steps
Check pros, cons, and user feedback
See how it stacks against alternatives
Follow our tutorial and master this powerful llm gateway & observability tool in minutes.
Tutorial updated March 2026