Kong Konnect Features

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

Protect APIs from threats using authentication, access control and 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.

Manage and direct API requests between clients and backend services

Monitoring and measurement of relevant metrics to assess the performance of IT resources

Active monitoring of systems, applications, or networks

Track revisions and updates made to files and navigate between different versions

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.

Receive data and information in real time

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.

Search and filter data across systems to locate required information by entering keywords or certain criteria

Store, manage, and track all electronic documents in a centralized location

Central hub for developers to access documentation, tools and resources

Track and document all activities across devices, networks, and other systems

Enforce consistent standards and policies across the entire API lifecycle

Creation of a plan for an API to expose data and functionality to its users

Manage an API from its creation to deployment through updates, monitoring, and maintenance

Track and manage adherence to policies for any service, product, process, or supplier

Track, manage and store the applications of potential future members, customers or candidates

Assembly of graphs and charts for visualizing and tracking statistics/metrics

Track and interpret metrics on the usage of company resources

Track the management and flow of data throughout the organization

View and track pertinent metrics to find patterns and gain insights from data

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Automates and streamlines business processes by creating a sequence of predefined rules and actions that govern the flow of work

Use AI to generate content in the form of text, images, videos, etc.

Import and export data to and from software applications

Online portal through which end users can access the system, manage tasks, or obtain information

Allows users to manage data from a number of sources

Connect to big data sources

Assemble applications and processes by dragging over and arranging pre-built components

Test specific APIs to determine if systems are properly functioning

Manage user accounts, profiles, roles, permissions, and other details across applications, devices or networks

Synchronizing data between two or more devices/systems and automatically updating changes to maintain consistency

Active reporting of data and metrics

Supports common databases such as MySQL and Oracle

Create, design and manage workflows for repetitive tasks

Define levels of authorization for access to specific files or systems