Best AI Gateways for AWS Bedrock in 2026

[This guide compares the top AI gateways for routing and managing AWS Bedrock workloads. For teams running mission-critical AI applications, Bifrost offers the most comprehensive feature set for performance, governance, and enterprise-grade reliability.]

Enterprises using AWS Bedrock to access foundation models from providers like Anthropic, Cohere, and Amazon itself often require a control plane to manage API traffic. An AI gateway provides a unified entry point for routing requests, enforcing security policies, managing costs, and ensuring reliability. While AWS offers native tools, a dedicated gateway can provide multi-cloud flexibility, advanced routing, and a consistent governance layer across all AI providers, not just Bedrock.

This article evaluates the best AI gateways for AWS Bedrock, focusing on features that matter for production workloads: performance, multi-provider routing, failover, governance, and observability. The top solutions include Bifrost, an open-source AI gateway from Maxim AI, alongside other popular options in the market.

Key Criteria for Evaluating a Bedrock AI Gateway

When selecting a gateway for AWS Bedrock, engineering teams should evaluate solutions based on several core capabilities:

• Performance and Latency: The gateway must add minimal overhead to the request path. Low-latency routing is critical for real-time applications.
• Provider and Model Support: The gateway should not only support AWS Bedrock but also other major providers like OpenAI, Google Gemini, and Anthropic's direct APIs to avoid vendor lock-in.
• Reliability Features: Automatic failover and load balancing are essential for production stability. The gateway must intelligently route traffic around unresponsive models or regional AWS outages.
• Governance and Security: Features like virtual keys, role-based access control (RBAC), budgets, rate limits, and audit logs are necessary for managing access and costs at scale.
• Observability: The ability to monitor requests, track performance metrics, and integrate with tools like Prometheus and Datadog is crucial for operational health.
• Deployment Flexibility: Support for deployment in a private VPC, on-premise, or in air-gapped environments is often a requirement for regulated industries.

1. Bifrost

Bifrost is a high-performance, open-source AI gateway designed for enterprise scale and reliability. It unifies access to AWS Bedrock and 20+ other LLM providers through a single, OpenAI-compatible API.

Best for: Enterprises running mission-critical or multi-cloud AI workloads on AWS Bedrock that require best-in-class performance, comprehensive governance, and deployment flexibility. Bifrost's unified LLM and MCP gateway capabilities make it a strong choice for teams building complex, agentic applications.

Key Features

• High Performance: Bifrost's Go-based architecture is built for speed, adding only 11 microseconds of overhead at 5,000 requests per second. This ensures that the gateway is not a bottleneck for production traffic to Bedrock models.
• Advanced Routing and Failover: It provides automatic fallbacks and intelligent load balancing across providers. Teams can configure rules to failover from a Bedrock model to an equivalent model on another provider (like Anthropic direct or Azure) during an outage.
• Comprehensive Governance: Bifrost offers a robust governance framework. Virtual keys allow teams to set per-user or per-project budgets, rate limits, and model access permissions. Bifrost Enterprise adds RBAC, OIDC integration, and immutable audit logs for compliance.
• Native Bedrock Integration: The AWS Bedrock SDK integration allows teams to use Bifrost as a drop-in replacement by changing only the base URL, with no other code changes required.
• Unified Observability: Bifrost exposes native Prometheus metrics and supports OpenTelemetry (OTLP) for integration with platforms like Grafana, Datadog, and New Relic.
• Endpoint Governance: A key differentiator is Bifrost Edge, which extends the gateway's governance policies to AI traffic on employee machines. This ensures that even direct use of tools that access Bedrock models is secure and compliant, an essential feature for managing shadow AI.

Deployment

Bifrost can be deployed anywhere: in a public cloud, a private VPC for secure access to Bedrock, or even in fully air-gapped environments. It supports high-availability clustering for zero-downtime deployments.

2. LiteLLM

LiteLLM is a popular open-source library that provides a unified interface for calling over 100 LLM APIs, including AWS Bedrock. It is often used as a lightweight proxy or gateway.

Best for: Startups and development teams looking for a simple, open-source way to abstract LLM provider APIs and manage API keys.

Key Features

• Broad Model Support: LiteLLM's primary strength is its extensive list of supported models.
• Unified API Format: It translates requests into the format required by each provider, simplifying code for multi-provider applications.
• Basic Routing: It supports failover and cooldown logic for routing around temporary API errors.
• UI for Management: LiteLLM provides a user interface for managing keys, viewing logs, and creating virtual keys.

Limitations Compared to Bifrost

While excellent for its core purpose, LiteLLM lacks the enterprise-grade performance and governance features of a dedicated gateway like Bifrost. Its Python-based architecture introduces more latency than a compiled Go binary. Features like RBAC, advanced audit logging, and in-VPC enterprise deployments are not its focus. Teams looking to move from LiteLLM to a more robust solution can review the Bifrost LiteLLM alternatives page.

3. Kong AI Gateway

The Kong AI Gateway is a product from the well-known API gateway provider Kong. It extends their existing infrastructure to manage AI and LLM traffic.

Best for: Large organizations that have already standardized on the Kong API Gateway for their microservices architecture and want to apply similar policies to their AI workloads.

Key Features

• Unified AI Policies: Allows teams to apply existing Kong policies (rate limiting, auth) to AI endpoints.
• Multi-LLM Support: It can proxy requests to various providers, including AWS Bedrock.
• AI-Specific Plugins: Kong offers plugins for prompt engineering, response caching, and observability for AI traffic.

Limitations Compared to Bifrost

Kong AI Gateway is a powerful tool but can be complex and expensive, especially for teams not already invested in the Kong ecosystem. Bifrost is purpose-built for AI traffic, offering deeper, more native features like semantic caching and MCP support. Bifrost's open-source core also provides a more accessible starting point.

4. Cloudflare AI Gateway

Cloudflare AI Gateway is a managed service that provides observability and control for AI applications.

Best for: Teams already using the Cloudflare ecosystem for network and security services who want a simple, managed way to add caching and analytics to their Bedrock API calls.

Key Features

• Global Caching: Leverages Cloudflare's global network to cache responses and reduce latency.
• Analytics and Logging: Provides a dashboard for viewing requests, tracking errors, and monitoring costs.
• Rate Limiting: Protects backend APIs from traffic spikes.

Limitations Compared to Bifrost

Cloudflare's offering is primarily focused on caching and analytics. It lacks the advanced routing, failover, and granular governance capabilities of Bifrost. As a managed cloud service, it does not support on-premise or in-VPC deployments, which can be a non-starter for organizations with strict data residency or security requirements.

How the Options Compare on Key Features

Feature	Bifrost	LiteLLM	Kong AI Gateway	Cloudflare AI Gateway
Primary Focus	Enterprise AI Gateway	Unified LLM API Library	General API Gateway	Caching & Analytics
Performance	Very High (11µs latency)	Moderate	High	High
Open Source	Yes (Core)	Yes	Yes (Core)	No
Automatic Failover	Yes, advanced	Yes, basic	Yes	No
Virtual Keys	Yes, with budgets	Yes	Via plugins	No
RBAC / OIDC	Yes (Enterprise)	No	Yes (Enterprise)	Yes
Audit Logging	Yes, immutable logs	Basic logging	Yes, advanced	Basic logging
Endpoint Governance	Yes (Bifrost Edge)	No	No	No
In-VPC Deployment	Yes	Yes (Self-hosted)	Yes	No

Centralizing AWS Bedrock Governance and Security

A primary reason to adopt an AI gateway is to centralize control over how models are accessed and used. For AWS Bedrock, this means ensuring that every request, regardless of origin, adheres to corporate policies. The Bifrost AI gateway applies governance and security controls like virtual keys, budgets, guardrails, and audit logs centrally. Critically, Bifrost Edge extends that same governance and security to AI traffic on employee machines, with endpoint enforcement on each device. This combined approach ensures that both application traffic and user-driven "shadow AI" traffic to Bedrock are fully governed.

This is particularly important for organizations in regulated industries like healthcare and life sciences, where a complete audit trail of data access is a compliance requirement. By routing all Bedrock traffic through a central gateway, teams can maintain a single source of truth for all AI interactions.

Recommendation

For teams building production applications on AWS Bedrock, choosing the right AI gateway is a critical architectural decision.

• For small projects or teams primarily needing a unified API layer, LiteLLM is a great open-source starting point.
• For enterprises already using Kong or Cloudflare, their respective AI gateway products can be a natural extension of their existing infrastructure.

However, for most teams, and especially for enterprises that prioritize performance, security, and multi-cloud flexibility, Bifrost stands out as the best overall choice. Its combination of high-speed, open-source architecture, advanced reliability features, and comprehensive enterprise governance makes it the most capable platform for managing AWS Bedrock workloads at scale.

Teams evaluating AI gateways for AWS Bedrock can request a Bifrost demo or review the open-source repository to learn more.