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alibaba/higress

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7,558 स्टार्स·993 फोर्क्स·Go·apache-2.0·33 व्यूज़higress.ai↗

Higress

Higress is an AI API gateway and cloud-native traffic manager that functions as a Kubernetes ingress controller. It provides a centralized system for routing, securing, and optimizing traffic directed toward large language models, AI agents, and microservice architectures.

The project distinguishes itself through deep AI orchestration, including the ability to host and manage Model Context Protocol servers that transform REST APIs into tools for AI agents. It features specialized AI infrastructure for model request proxying, protocol translation across multiple providers, and semantic-based caching to reduce token consumption and latency.

Broad capabilities cover API lifecycle management and traffic control, including canary releases, load balancing, and rate limiting. The system includes a comprehensive security suite with WAF filtering, OIDC and OAuth2 identity integration, and automated TLS certificate management. Extensibility is provided via a WebAssembly-based plugin system that allows for hot-loading custom logic without interrupting traffic.

The gateway can be deployed to Kubernetes or Docker and supports the Kubernetes Gateway API and Ingress standards.

Features

  • AI API Gateways - Provides a specialized gateway for routing, securing, and optimizing traffic specifically for large language models and AI agents.
  • AI Gateway Management - Provides a centralized AI gateway for routing, load balancing, and token quota management for LLMs.
  • Traffic Management - Provides a specialized gateway for proxying, auditing, and securing traffic specifically for AI models.
  • Ingress Controllers - Functions as a Kubernetes ingress controller supporting the Gateway API and Nginx Ingress annotations.
  • Model Context Protocol - Converts requests from a single interface into the specific protocols required by various AI models.
  • MCP Server Management - Provides interfaces for registering and organizing MCP server connections from registries and external providers.
  • AI Agent Orchestration - Implements orchestration templates to deploy customizable API agents that execute external tools via web requests.
  • AI Tool Converters - Transforms existing REST APIs into callable AI tools by mapping requests to HTTP calls using templates.
  • Retrieval-Augmented Generation - Augments model responses by retrieving relevant documents from vector search services to provide factual context.
  • Token Quota Enforcement - Implements global and dynamic token consumption limits to manage AI model costs and resource usage.
  • Semantic Caching Systems - Stores and retrieves model responses using vector-based semantic matching to reduce token consumption and latency.
  • MCP Servers - Provides implementations of the Model Context Protocol to expose databases and APIs as tools for AI agents.
  • Model Context Protocol Servers - Implements standardized interfaces to connect AI models to external tools and data sources via MCP.
  • Model Format Translators - Detects request formats and translates payloads to match the specific requirements of different LLM providers.
  • Fallback Configurations - Implements failover logic to redirect requests to backup AI models when primary models fail.
  • Usage Quotas - Enforces token-based usage quotas and balances for consumers interacting with AI models.
  • Response Caching - Retrieves previous model responses using string or vector matching to lower API costs and latency.
  • Semantic Caching - Stores model responses and dialogue context using semantic matching to reduce token usage and latency.
  • Request Path Rewriters - Modifies original request paths and host headers to correctly route traffic to backend services.
  • MCP Protocol Adapters - Transforms external REST APIs into protocol servers using templates to map tool calls to API endpoints.
  • API Gateways - Implements a cloud-native API gateway compatible with both Kubernetes Ingress and Gateway API standards.
  • AI Traffic Routing - Manages load balancing, fallback, and rate limiting for traffic routed to multiple model providers.
  • API Traffic Management - Manages microservice entry points with advanced routing, rate limiting, and automated TLS certificates.
  • Routing Policy Resources - Uses Kubernetes custom resource definitions to declaratively define routing and traffic policies within a cluster.
  • Canary Deployment Controllers - Gradually shifts traffic to new versions using weight percentages to minimize deployment risk.
  • Load Balancing Algorithms - Allows the selection and configuration of algorithms used to balance traffic across available backend nodes.
  • Microservice Traffic Management - Implements cloud-native traffic management including canary releases, load balancing, and rate limiting for microservice architectures.
  • Distributed Rate Limiting - Synchronizes request limits across multiple instances using a shared data store for consistent global throttling.
  • Service Discovery - Dynamically locates and routes traffic to backend service instances using multiple service registries.
  • Dynamic Service Discovery - Integrates with registries like Nacos and Consul to automatically resolve logical service names to network addresses.
  • Load Balancers - Distributes incoming requests across backend services using algorithms like round-robin and consistent hashing.
  • Model Request Proxies - Routes requests to various AI service providers using a unified interface for chat and embedding tasks.
  • Service Traffic Routing - Routes traffic to specific service versions using weights or cookies for gradual rollouts.
  • Proxy Headers - Manages the addition of real-IP headers and removal of proxy headers before forwarding traffic.
  • API Gateway - Maps incoming HTTP requests to various backend protocols like gRPC, Dubbo, and MCP using request templates.
  • Service Discovery Integrations - Connects to upstream clusters using discovery mechanisms such as DNS, Kubernetes, or external service registries.
  • Traffic Routing - Provides a console and configuration system to define how requests are directed to backend services.
  • Traffic Routing Policies - Provides declarative routing policies using metadata to control network traffic behavior.
  • Weighted Traffic Splitting - Distributes traffic to specific service versions based on weights or headers to enable gradual rollouts.
  • API Access Security - Protects API endpoints using a combination of WAF filtering and authentication strategies like JWT and HMAC.
  • Enterprise Identity Providers - Secures API access using OIDC, OAuth2, and JWT to manage enterprise-grade authentication and authorization policies.
  • Usage Limits - Enforces AI model access quotas per consumer to ensure fair token distribution.
  • Plugin-Based Logic Extensions - Uses a plugin-based architecture to execute custom logic and built-in extensions during the request lifecycle.
  • Rate Limiting - Provides rate limiting based on dynamic attributes such as IP addresses, headers, or consumer identities.
  • Service Discovery Registries - Connects to external discovery instances using server addresses and credentials to track service locations.
  • Wasm-Based Plugins - Executes custom logic through WebAssembly modules to modify request and response handling without restarting the proxy.
  • Agent API Gateways - Exposes autonomous agents as secure, observable, and scalable web services through an AI-specific API gateway.
  • API Lifecycle Management Suites - Provides an integrated platform for end-to-end API deployment, including version control, canary releases, and automated rollbacks.
  • Request and Response Transformers - Provides comprehensive transformation of request and response headers, query parameters, and body content.
  • Protected Endpoints - Provides protected endpoints secured via WAF capabilities and identity providers including OIDC, JWT, and HMAC.
  • HTTP Redirects - Handles HTTP redirection to send client requests to different target destinations.
  • Intent Classification Pipelines - Categorizes incoming requests into predefined domains to determine the appropriate downstream model or cache.
  • Skill Packaging - Bundles agent skills, configurations, and dependencies into versioned packages for portable distribution.
  • Custom Agent Distributions - Provides mechanisms for bundling and publishing versioned agent packages to a discovery marketplace.
  • Agent Installation - Provides web-based and CLI methods for deploying agent packages to local environments.
  • Sandbox Environments - Creates hosted, sandboxed runtime environments for MCP servers including resource allocation and authentication.
  • AI Access Control - Provides fine-grained authorization logic to restrict access to specific AI tools based on whitelists or role-based headers.
  • Skill Marketplaces - Hosts AI skills in a searchable portal where users can filter and subscribe to specific capabilities.
  • AI Monitoring - Provides observability tools to track real-time token counts and performance metrics per AI model provider.
  • AI Provider Managers - Manages API keys for multiple AI vendors and implements health-based token degradation strategies.
  • AI Tool Definitions - Automatically discovers and refreshes structured specifications for tools used by AI agents from registered servers.
  • Conversation History Management - Caches dialogue based on request headers and injects previous turns into the prompt context.
  • Model Comparison Tools - Executes a single prompt across multiple models simultaneously to compare response quality and accuracy.
  • Private Context Integration - Integrates proprietary documents and knowledge bases to ground large language models in private domain-specific data.
  • Prompt Engineering - Inserts custom text or dynamic data into prompts to optimize language model performance.
  • Prompt Templates - Creates reusable request structures to ensure consistency across similar types of AI interactions.
  • Query Optimization - Analyzes natural language queries and rewrites them into optimized keywords for better retrieval relevance.
  • Web Search Integrations - Enables language models to query real-time web data to expand their knowledge base with current information.
  • Agent Cataloging - Creates catalog entries for agents by defining names, types, and technical metadata for users.
  • Agent Marketplaces - Enables users to discover and filter available AI agents and view their technical configurations via a portal.
  • Server Discovery Portals - Lists configured MCP servers in a developer portal for user discovery and tool subscription.
  • A/B Testing - Routes traffic to specific application versions based on request attributes to execute A/B tests.
  • REST to GraphQL Translation - Translates incoming REST requests into GraphQL queries and forwards them to a GraphQL endpoint.
  • Usage Billing Systems - Tracks resource consumption based on tokens or request counts to generate internal or commercial billing details.
  • Developer Portals - Distributes configured API products to centralized developer portals for discovery and subscription.
  • Gateway Installation Profiles - Provides predefined configuration profiles for installing the gateway and observability tools onto Kubernetes or Docker.
  • Interactive API Explorers - Renders an interactive interface for visualizing and testing available API endpoints directly from the console.
  • AI Artifact Catalogs - Distributes models and agents through a centralized artifact catalog featuring versioning and grayscale releases.
  • Inter-Plugin State Sharing - Stores and retrieves metadata properties during a request lifecycle to pass state across different plugins.
  • Backend Endpoint Definitions - Configures and registers the base URLs and addresses of backend services for targeted routing.
  • Request Retries - Automatically retries failed requests to the next available upstream server based on defined conditions.
  • Custom Resource Mappings - Translates Kubernetes custom resources and Gateway API definitions into active network filter configurations.
  • Standalone Container Deployments - Provides a single-container image deployment for rapid local setup and testing of the gateway.
  • Custom Resource Definitions - Creates custom API resources using protobuf definitions to extend configuration capabilities within Kubernetes.
  • Custom Resource Controllers - Monitors changes to custom resource instances to trigger business logic and automate network filter generation.
  • Deployment Scaling - Manages gateway scaling via manual replica counts or automatic CPU-based pod scaling.
  • Progressive Delivery Strategies - Coordinates workload updates and routing rules to execute phased rollouts with automated approvals.
  • Multi-Architecture Deployments - Supports installation across Kubernetes Operator mode, non-Kubernetes environments, and ARM architectures.
  • OCI-Compliant Plugin Packaging - Packages WebAssembly binaries and metadata into OCI-compliant container images for standardized distribution and hot-loading.
  • Rate Limiting Algorithms - Implements the Token Bucket algorithm to allow traffic bursts while maintaining a steady request rate.
  • Plugin Development Kits - Provides a development kit with wrappers for context management to simplify the creation of custom gateway extensions.
  • Scope Configurations - Assigns plugin settings at global, service, domain, or route levels to enable granular configuration overrides.
  • Traffic Tagging - Adds specific request headers based on content matching to identify traffic for canary deployments and testing.
  • Version Upgrades - Provides tools for updating existing gateway installations to newer versions without losing configuration.
  • Registry-Based Service Discovery - Forwards requests to microservices by resolving addresses from external registries like Nacos or Consul.
  • gRPC Traffic Routing - Directs requests to backend services using specialized protocols such as gRPC and HTTP/2.
  • HTTP Traffic Manipulation Tools - Provides tools for intercepting and modifying HTTP headers and body content for both requests and responses in real-time.
  • Load Balancer IP Address Management - Configures listening ports, load balancer IP addresses, and source IP ranges for incoming network traffic.
  • Network Port Configuration - Allows custom configuration of the network ports the gateway uses for listening to HTTP and HTTPS traffic.
  • Backend Protocol Settings - Provides configurations for specifying the communication protocols, such as HTTP or gRPC, used between the gateway and upstream services.
  • Protocol-Agnostic Proxies - Routes client requests to backend servers using streaming protocols while managing the connection lifecycle.
  • Proxy Servers - Routes requests to native services and maintains sessions to facilitate communication with specialized data sources.
  • Dubbo Integration - Transforms standard HTTP requests into Dubbo protocol calls to trigger remote service methods.
  • Layer 4 TCP Routing - Directs raw TCP network traffic to backend services using a layer 4 routing mechanism.
  • Traffic Shadowing - Duplicates a percentage of live traffic to a shadow service for auditing and testing.
  • Transport Timeouts - Configures idle timeouts and buffer limits for both downstream clients and upstream service connections.
  • AI Security - Filters sensitive information and performs security checks specifically on requests directed at AI resources.
  • Mutual TLS Authentication - Implements bidirectional identity verification via mutual TLS between clients and the gateway.
  • API Credential Managers - Generates and manages unique API keys and secrets for different environments to maintain multiple credential sets.
  • API Key Authentication - Validates clients by matching API keys from request headers or URL parameters against authorized consumers.
  • Bot Blocking - Identifies and blocks web crawlers and scrapers based on User-Agent patterns.
  • Authentication Scope Management - Controls which requests require identity verification using path-based whitelist or blacklist rules.
  • Basic Authentication - Validates users based on the HTTP Basic Auth standard and attaches identity to the request header.
  • Communication Encryption - Secures the communication channel between the gateway and backend services using client certificates and SNI.
  • AI Content Filters - Scans and filters AI model prompts and responses to block harmful content and ensure compliance.
  • Content Moderation - Inspects model inputs and outputs via security services to block non-compliant or inappropriate content.
  • SSL/TLS Certificate Management - Automates the provisioning and renewal of SSL/TLS certificates through Let's Encrypt.
  • Request Access Restrictions - Implements per-request authorization logic to restrict domain access to authorized JWT consumers.
  • External Identity Provider Integration - Authenticates users via OIDC or OAuth2 providers to automatically create or link developer accounts.
  • TLS Certificate Management - Simplifies the provisioning and renewal of security certificates for secure traffic.
  • Security Policy Scoping - Allows security policies to be applied at global, domain, or route levels for precise traffic control.
  • HTTP Request Filtering - Blocks suspicious traffic using a rule-based engine integrated with the OWASP Core Rule Set.
  • External Authorization Proxies - Delegates permission validation to an external security service via proxy requests for centralized authorization.
  • JWT Authentication - Validates JSON Web Tokens from headers or cookies using public keys or symmetric secrets.
  • Mutual TLS Configurations - Configures TLS cipher suites and CA certificates to secure the connection between clients and the gateway.
  • Mutual TLS Transports - Establishes mutual TLS and verifies SNI for encrypted traffic between the gateway and upstream services.
  • OIDC Authentication Plugins - Verifies user identities using the OpenID Connect protocol to manage the full authentication lifecycle.
  • Policy-Based Access Control - Enforces security permissions by evaluating incoming requests against external Open Policy Agent rules.
  • Model Inference Metrics - Tracks model inference metrics including token usage and request latency across gateways and routes.
  • Request Authentication - Verifies caller identity by validating a cryptographic HMAC signature generated from a shared secret.
  • Dynamic Data Masking - Replaces sensitive words in request and response bodies using regex and grok patterns to prevent data leaks.
  • PII Masking - Encrypts or masks sensitive information in requests and responses to prevent PII leaks.
  • Service Communication Security - Defines trust domains and root certificates to manage identities and encryption for inter-service communication.
  • SSL Certificate Automation - Automates the issuance and renewal of SSL certificates using ACME providers.
  • TLS Management - Configures minimum and maximum TLS protocol versions and cipher suites for secure communication.
  • Token Signature Verification - Validates incoming JWT tokens against configured consumers to determine if a request is permitted.
  • OAuth2 Access Token Issuance - Generates JWT-based access tokens using the client credentials grant flow to authenticate service callers.
  • Traffic Filtering - Inspects request headers and bodies using predefined security rule sets to block attacks.
  • Service Call Fallbacks - Forwards traffic to a backup service when the primary backend is unavailable or returns errors.
  • Hierarchical Configuration Overrides - Applies configuration settings across global, service, domain, and route levels using a hierarchical override system.
  • Plugin Execution Ordering - Allows precise control over the order of plugin execution within the filter chain using phases and priority values.
  • Static Endpoint Mapping - Directs requests to backend services using fixed IP addresses or DNS domain names.
  • URL-Based Plugin Loading - Fetches Wasm plugins from remote URLs via HTTP or HTTPS to extend functionality without rebuilding images.
  • Capability Packaging - Wraps models, agents, and servers into standardized product packages with custom metadata and guides.
  • Plugin Configuration Defaults - Implements a tiered configuration system where specific plugin settings override global defaults to control traffic.
  • Execution Scoping - Applies plugins based on match rules for domains or routes to control exactly where logic is executed.
  • Traffic Modification Plugins - Provides Wasm plugins to intercept and alter HTTP headers, bodies, and TCP data frames.
  • API Gateways - Functions as an API gateway that extends request processing logic using hot-loadable WebAssembly plugins.
  • Gateway Observability - Provides integrated dashboards to track gateway traffic, system health, and overall performance.
  • IP Access Restrictions - Blocks or permits incoming requests based on IP address whitelists or blacklists.
  • Log Statistics Visualizers - Displays access logs through a centralized monitoring dashboard to visualize and analyze traffic patterns.
  • LLM Performance Monitoring - Tracks LLM performance metrics, including token usage, success rates, and response times.
  • AI Workload Dashboards - Offers global visualization dashboards to monitor AI workload health, API call trends, and traffic patterns.
  • Request Traffic Monitors - Generates dashboards to track request volume, processing duration, and success rates across API endpoints.
  • Observability Suites - Integrates and configures comprehensive toolsets for collecting and analyzing logs, metrics, and traces.
  • Proxy Management Dashboards - Provides a web-based console for configuring network traffic routing, access policies, and security protocols.
  • Request Timeouts - Defines the maximum duration the gateway waits for a response before timing out a request.
  • Concurrency Limiters - Caps the number of simultaneous requests to backend services to prevent resource exhaustion and system crashes.
  • Traffic Interception Tools - Uses Wasm-compiled logic to intercept and modify HTTP traffic during the request lifecycle.
  • Traffic Monitoring Tools - Collects and visualizes network traffic metrics to verify routing and audit user traffic metadata.
  • Token Usage Analytics - Tracks real-time input and output token consumption per model provider to enforce quotas and billing.
  • Token Consumption Trackers - Extracts and aggregates input and output token counts per second to analyze model consumption.
  • HTTP Header Manipulators - Provides utilities for adding, removing, or modifying HTTP header fields in both incoming requests and outgoing responses.
  • Tool Parameter Definitions - Defines data types and placement for AI tool arguments across URL paths, query strings, and request bodies.
  • Request Body Validations - Verifies request bodies and headers against JSON Schema or OAS3 definitions to reject malformed data.
  • AI Output Validation - Formats non-streaming AI outputs into valid JSON and validates them against defined schemas.
  • AI Response Templates - Converts raw HTTP responses into AI-friendly formats using a template engine with conditional logic.
  • RPC Service Mappers - Maps incoming HTTP paths and methods to specific internal service interfaces for RPC communication.
  • Search Result Injection - Retrieves live search engine data and incorporates it into model prompts to improve response accuracy.
  • Encrypted Backend Routing - Implements secure communication with backend services using encrypted protocols including HTTPS and GRPCS.
  • Frontend Version Routing - Routes users to different frontend versions based on cookies or headers to support A/B testing.
  • HTTP Response Handlers - Implements mechanisms to construct and return predefined HTTP responses, including custom status codes and bodies.
  • Service Mesh And Gateways - Delivers a cloud-native API gateway based on Istio.
  • API Gateways and Proxies - Next-generation gateway for cloud-native traffic management.

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alibaba/higress क्या करता है?

Higress is an AI API gateway and cloud-native traffic manager that functions as a Kubernetes ingress controller. It provides a centralized system for routing, securing, and optimizing traffic directed toward large language models, AI agents, and microservice architectures.

alibaba/higress की मुख्य विशेषताएं क्या हैं?

alibaba/higress की मुख्य विशेषताएं हैं: AI API Gateways, AI Gateway Management, Traffic Management, Ingress Controllers, Model Context Protocol, MCP Server Management, AI Agent Orchestration, AI Tool Converters।

alibaba/higress के कुछ ओपन-सोर्स विकल्प क्या हैं?

alibaba/higress के ओपन-सोर्स विकल्पों में शामिल हैं: fabiolb/fabio — Fabio is a network gateway that provides reverse proxying, layer 7 traffic management, and automated service discovery… transitive-bullshit/agentic — Agentic is a tool marketplace and management platform designed for the Model Context Protocol. It provides a gateway… haproxy/haproxy — HAProxy is a high-performance TCP and HTTP proxy that distributes traffic across multiple backend servers to ensure… aws/aws-cdk — The AWS Cloud Development Kit is an infrastructure-as-code framework that enables developers to define and provision… apache/apisix — This project is a high-performance, distributed API gateway designed to manage, secure, and observe traffic for… megaease/easegress — Easegress is a cloud native API gateway, Kubernetes ingress controller, and service mesh control plane. It serves as a…

Higress के ओपन-सोर्स विकल्प

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