Kong Konnect Features

Provides an environment for users to rest their API's functionality, efficiency, and data accuracy.

Allows users to secure access to data. Provides additional support for security practices like IP whitelisting, attack mitigation, and data encryption.

Allows administrators to create APIs that utilize multiple backend resources and databases.

Expands functionality while maintaining balanced loads. Serves growing demand without reducing functionality.

Limits access to suspicious visitors and monitors for traffic spikes to prevent overloads like DDoS attacks.

Records details related to usage and functionality for analytics and reporting.

Detects anomalies in functionality, user accessibility, traffic flows, and tampering.

Allows administrators to manage pricing and billing of API integration with customer applications.

Provides a dashboard for users to manage, govern, and secure their API.

The functionality at which APIs integrate with and perform within third-party applications.

Translates complex datasets and backend systems into formats that can be interpreted by applications.

Provides additional functionality for increased security, analytics, monitoring, and other features not included in the native feature set.

Provides an environment for users to test their API's functionality, efficiency, and data accuracy.

Allows users to secure access to data. Provides additional support for security practices like IP whitelisting, attack mitigation, and data encryption.

Allows developers to create APIs that utilize multiple backend resources and databases.

Expands functionality while maintaining balanced loads. Serves growing demand without reducing functionality.

Allows administrators to set API design guidelines and best practices.

Enables administrators to set permissions for team members to access workspaces.

Allows members across teams to view progress and updates throughout the design process.

Support TCP, HTTP/1.1+, HTTP/2, gRPC protocols for communication between cloud services and integrations.

Allows developers to deploy multiple containers for implementation within applications.

Plug-in capable for added resources, features, and functions within the product itself.

Tracks container performance, collects event data, and measures the effects of container-sharing resources.

Defines container connections, balances loads, and organizes routes.

Manages and controls high peak web traffic by distributing network traffic evenly.

Allows DNS routing to resolve requests across HTTP or HTTPs requests and/or covers IPv4 and IPv6 protocols.

Automates the detection of microservices within a computer network.

Enables administrators to create access policies and applies policy controls throughout request and provisioning processes

Provides a secure means for managing and sharing encryption, certificates, and authentications.

Offers SEO guidance to aid users with public-facing documentation

Utilizes API contracts to create customizable documentation

Empowers users to make needed edits and updates with change management

Features a central repository that provides users with an organized space to access and store documents

Integrates easily with portals and third-party tools

Manages users and permissions with access management capabilities

Provides users with the ability to test and optimize prompts to improve LLM output quality and efficiency.

Gives users a collection of reusable prompt templates for various LLM tasks to accelerate development and standardize output.

Offers tools for users to compare multiple LLMs side-by-side based on performance, speed, and accuracy metrics.

Provides users with a user-friendly interface for fine-tuning LLMs on their specific datasets, allowing better alignment with business needs.

Gives users tools to integrate LLM functionality into their existing applications through SDKs and APIs, simplifying development.

Offers users the capability to deploy models quickly to production environments with minimal effort and configuration.

Provides users with tools to automatically scale LLM resources based on demand, ensuring efficient usage and cost-effectiveness.

Gives users the ability to set boundaries and filters to prevent inappropriate or sensitive outputs from the LLM.

Offers users tools to ensure their LLMs adhere to compliance standards such as GDPR, HIPAA, and other regulations, reducing risk and liability.

Gives users notifications when the LLM performance deviates significantly from expected norms, indicating potential model drift or data issues.

Provides users with live insights into model accuracy, latency, and user interaction, helping them identify and address issues promptly.

Provides users with encryption capabilities for data in transit and at rest, ensuring secure communication and storage when working with LLMs.

Offers users tools to set access permissions for different roles, ensuring only authorized personnel can interact with or modify LLM resources.

Provides users with middleware to route requests efficiently to the appropriate LLM based on criteria like cost, performance, or specific use cases.

Gives users tools to process multiple inputs in parallel, improving inference speed and cost-effectiveness for high-demand scenarios.

Provides an environment for users to test their API's functionality, efficiency, and data accuracy.

Expands functionality while maintaining balanced loads. Serves growing demand without reducing functionality.

Allows developers to create APIs that utilize multiple backend resources and databases.

Allows users to secure access to data. Provides additional support for security practices like IP whitelisting, attack mitigation, and data encryption.

Allows members across teams to view progress and updates throughout the design process.

Enables administrators to set permissions for team members to access workspaces.

Allows administrators to set API design guidelines and best practices.

Detects anomalies in functionality, user accessibility, traffic flows, and tampering.

Limits access to suspicious visitors and monitors for traffic spikes to prevent overloads like DDoS attacks.

Provides a dashboard for users to manage, govern, and secure their API.

Records details related to usage and functionality for analytics and reporting.

Allows administrators to manage pricing and billing of API integration with customer applications.

Enforces strict request and token quotas per user, tenant, or application to prevent system overloads and manage API budget limits.

Caches responses for identical or semantically similar prompts to significantly reduce API latency and eliminate redundant token costs.

Routes API requests to various LLM providers via a single unified API and automatically fails over to backup models if downtime occurs.

Intercepts traffic to detect and mask Personally Identifiable Information (PII) or block malicious prompt injections before the request reaches the external model.

Provides granular dashboards to monitor token consumption and calculate exact monetary costs broken down by application, team, or specific model.

Securely vaults and manages external LLM API keys within the gateway so developers do not need to hardcode credentials into their applications.