Kong excels at high-throughput, synchronous API management because its underlying NGINX core is optimized for Layer 7 traffic processing with minimal latency. For example, in standard benchmark configurations, Kong can handle over 50,000 requests per second when validating JWTs, making it a strong choice for RESTful agent-to-service communication where low-latency, request-response cycles are critical.
Difference
Kong vs Gravitee: Event-Native vs. API-Native Gateway

Introduction
A technical comparison of Kong's API-centric architecture versus Gravitee's event-native approach for securing autonomous agent communication.
Gravitee takes a fundamentally different approach by natively supporting asynchronous protocols and event-driven architectures. Rather than treating WebSockets, Server-Sent Events (SSE), and Kafka protocols as afterthoughts, Gravitee's core was designed to manage long-lived connections and mediate event streams. This results in superior support for AsyncAPI definitions and persistent token validation, but it can introduce slightly higher baseline latency for simple synchronous calls compared to a pure NGINX-based proxy.
The key trade-off: If your priority is securing high-volume, synchronous REST APIs with a vast plugin ecosystem for standards like OpenID Connect and mTLS, choose Kong. If you prioritize managing long-lived, event-driven agent workflows that rely on WebSocket authentication and AsyncAPI governance, choose Gravitee. For a deeper dive into securing machine identities at the gateway, see our analysis of Kong vs Tyk: API Gateway for Machine Identity and Envoy Proxy vs Kong: Service Mesh Gateway vs. API Management.
Feature Comparison: Machine Identity Enforcement
Direct comparison of key metrics and features for securing agent-to-API communication.
| Metric | Kong | Gravitee |
|---|---|---|
Architecture Focus | API-Native (Synchronous) | Event-Native (Asynchronous) |
AsyncAPI Support | ||
WebSocket Auth Persistence | Plugin-based (e.g., session) | Native policy enforcement |
Token Introspection (OAuth2) | Plugin (High maturity) | Policy (High maturity) |
mTLS Offloading | ||
Declarative Configuration | db-less mode (YAML/JSON) | Kubernetes CRDs / Management API |
Plugin/Policy Language | Lua, Go, WebAssembly | Java, JavaScript (via script policy) |
Long-Lived Token Management | Rate limiting, TTL enforcement | Rate limiting, quota, TTL enforcement |
TL;DR Summary
Key strengths and trade-offs for securing agent-to-API communication in event-driven versus request-response architectures.
Kong: The Synchronous Security Fortress
Mature plugin ecosystem: Over 200 plugins for OpenID Connect, mTLS, and OAuth2, providing battle-tested security for request-response APIs. Declarative, db-less mode: Ideal for GitOps-driven, ephemeral agent environments where infrastructure must be immutable and instantly reproducible. High-performance NGINX core: Delivers predictable, low-latency authentication for high-concurrency, synchronous agent workloads. This matters for enforcing strict machine identity on traditional REST and gRPC APIs.
Kong: The Event-Driven Blind Spot
Limited AsyncAPI support: Kong's architecture is fundamentally request-response, making it complex to natively authenticate and manage long-lived WebSocket or Kafka connections without custom development. Plugin-centric, not protocol-centric: Extending Kong to deeply understand asynchronous protocols like MQTT or AMQP requires building and maintaining complex custom plugins, increasing operational overhead. This is a critical gap for securing event-native agentic workflows.
Gravitee: The Asynchronous Identity Broker
Native AsyncAPI support: Gravitee is built from the ground up to manage, secure, and mediate asynchronous protocols. It can enforce authentication on WebSocket handshakes and validate tokens on message streams. Protocol mediation: Excels at bridging synchronous and asynchronous worlds, allowing a REST call from an agent to be securely translated into a Kafka message. This matters for managing long-lived machine identity tokens in event-driven agentic workflows.
Gravitee: The Synchronous Maturity Gap
Smaller plugin marketplace: While extensible, Gravitee's plugin ecosystem is less mature than Kong's, potentially requiring more custom development for niche synchronous security integrations. Performance profile: Its Java-based core may introduce different latency characteristics under high-throughput, pure request-response loads compared to Kong's NGINX foundation. This is a key trade-off for teams primarily securing traditional RESTful APIs.
When to Choose Kong vs. Gravitee
Kong for API-First Architectures
Verdict: The industry standard for synchronous REST and gRPC traffic. Kong's plugin ecosystem and declarative configuration are purpose-built for managing the full lifecycle of APIs.
Strengths:
- Mature Plugin Ecosystem: Over 200 plugins for authentication (OAuth2, OIDC, mTLS), rate limiting, and transformation.
- Declarative Management: Kong's decK tool and Kubernetes CRDs allow for GitOps-driven machine identity enforcement.
- Low-Latency Proxying: Built on NGINX, it excels at high-throughput, low-latency synchronous request/response patterns.
Gravitee for API-First Architectures
Verdict: A strong contender, especially if you need a unified control plane for synchronous APIs and asynchronous events, but it is less mature in pure REST plugin depth.
Strengths:
- Unified Policy Engine: Define a single authentication policy and apply it to both an API and an event stream.
- Drag-and-Drop Designer: Low-code policy design can accelerate deployment for teams without deep Lua or Go expertise.
- Full Lifecycle Management: Strong built-in support for API documentation, developer portals, and versioning.
Enabling Efficiency, Speed & Accuracy
Intelligent Analysis, Decision & Execution
We build AI systems for teams that need search across company data, workflow automation across tools, or AI features inside products and internal software.
Talk to Us
Search across company data
Give teams answers from docs, tickets, runbooks, and product data with sources and permissions.
Useful when people spend too long searching or get different answers from different systems.

Automate internal workflows
Use AI to route work, draft outputs, trigger actions, and keep approvals and logs in place.
Useful when repetitive work moves across multiple tools and teams.

Add AI to products and internal tools
Build assistants, guided actions, or decision support into the software your team or customers already use.
Useful when AI needs to be part of the product, not a separate tool.
Technical Deep Dive: AsyncAPI and Token Management
A granular comparison of how Kong and Gravitee handle the unique security and protocol challenges of event-driven agentic workflows, focusing on AsyncAPI support, WebSocket authentication, and long-lived token management.
Gravitee has native, first-class AsyncAPI support. Gravitee's platform is built on an event-native architecture, allowing you to import, design, and manage AsyncAPI definitions directly in its management console. Kong relies on community plugins or custom development for AsyncAPI, as its core is API-centric (OpenAPI/REST). For organizations standardizing on event-driven architectures for agent communication, Gravitee provides a more integrated design-time and runtime experience for protocols like Kafka, MQTT, and WebSockets.
Verdict
A final, data-driven assessment to help CTOs choose between Kong's synchronous API-centric control and Gravitee's asynchronous, event-native architecture for securing agentic workflows.
Kong excels at high-throughput, synchronous API management because its NGINX-based core is optimized for minimal latency. For example, in standard load tests, Kong can handle over 50,000 requests per second with a p99 latency under 10ms for simple JWT validation. This makes it the superior choice for securing RESTful, request-response agent tool calls where predictable, low-latency enforcement is critical. Its vast plugin ecosystem provides battle-tested, declarative security for OpenID Connect and mTLS.
Gravitee takes a fundamentally different approach by being event-native, built from the ground up to manage asynchronous protocols like WebSockets, SSE, and Kafka. This results in a trade-off: its synchronous throughput may be lower than Kong's, but it natively authenticates and authorizes long-lived, persistent connections without custom workarounds. Gravitee's support for AsyncAPI means it can enforce machine identity on a stream of events over a single connection, a scenario where Kong's request-per-transaction model requires complex proxying.
The key trade-off: If your priority is securing high-volume, synchronous REST APIs with minimal latency and a mature plugin marketplace, choose Kong. If you prioritize managing long-lived, event-driven agent communication using protocols like WebSockets and Kafka with native AsyncAPI support, choose Gravitee. For a hybrid agentic architecture, consider deploying both: Kong as the synchronous API gateway and Gravitee as the event-native broker gateway.

About the author
Prasad Kumkar
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
Partnered with leading AI, data, and software stack.
How We Work
Custom AI workflows for your Business
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
01
Review the use case
We understand the task, the users, and where AI can actually help.
Read more02
Pick the right approach
We define what needs search, automation, or product integration.
Read more03
Build the first useful version
We implement the part that proves the value first.
Read more04
Improve from there
We add the checks and visibility needed to keep it useful.
Read moreThe first call is a practical review of your use case and the right next step.
Talk to Us