Amazon DeepRacer
AWS DeepRacer is an autonomous 1/18th scale race car designed to test reinforcement learning (RL) models by racing on a physical track. It provides a fully autonomous driving platform that enables developers to get hands-on experience with machine learning through a fun and engaging racing experience.
Amazon DeepRacer publishes 4 APIs on the APIs.io network, including Cars API, Leaderboards API, Models API, and 1 more. Tagged areas include Autonomous Vehicles, Machine Learning, Reinforcement Learning, and Robotics.
The Amazon DeepRacer catalog on APIs.io includes 1 JSON-LD context and 2 Spectral governance rulesets.
Amazon DeepRacer’s developer surface includes authentication, developer portal, documentation, support, engineering blog, developer console, signup flow, and 12 more developer resources.
Kin Score
APIs 4
Individual APIs this provider publishes, each with its own machine-readable definition.
Amazon DeepRacer Cars API
Manage DeepRacer physical vehicles and their configurations
Amazon DeepRacer Leaderboards API
Manage racing leaderboards and submissions
Amazon DeepRacer Models API
Manage reinforcement learning models for autonomous racing
Amazon DeepRacer Tracks API
Manage virtual and physical racing tracks
Postman Collections 4
Ready-to-run Postman collections for exercising this provider's APIs.
Amazon DeepRacer Cars API
POSTMANOpen Collections 1
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
Amazon DeepRacer API
OPEN COLLECTIONPricing Plans 1
Published pricing tiers and plan structures.
Rate Limits 1
Documented rate limits and quota policies.
Amazon Deepracer Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals for API financial operations.
Amazon Deepracer Finops
FINOPSSemantic Vocabularies 1
JSON-LD contexts and semantic vocabularies used across these APIs.
Amazon Deepracer Context
JSON-LDSpectral Rules 2
Spectral governance rulesets for linting and validating these APIs.
Amazon DeepRacer API Rules
SPECTRALAmazon DeepRacer API Rules
SPECTRALJSON Schema 11
Standalone JSON Schema definitions for this provider's data models.
Car
JSON SCHEMAError
JSON SCHEMALeaderboard
JSON SCHEMALeaderboardSubmission
JSON SCHEMAListCarsResponse
JSON SCHEMAListLeaderboardSubmissionsResponse
JSON SCHEMAListLeaderboardsResponse
JSON SCHEMAListModelsResponse
JSON SCHEMAListTracksResponse
JSON SCHEMAModel
JSON SCHEMATrack
JSON SCHEMAScroll for all 11
JSON Structure 11
JSON Structure definitions describing this provider's data shapes.
Car Structure
JSON STRUCTUREError Structure
JSON STRUCTURELeaderboard Structure
JSON STRUCTURELeaderboard Submission Structure
JSON STRUCTUREList Cars Response Structure
JSON STRUCTUREList Leaderboard Submissions Response Structure
JSON STRUCTUREList Leaderboards Response Structure
JSON STRUCTUREList Models Response Structure
JSON STRUCTUREList Tracks Response Structure
JSON STRUCTUREModel Structure
JSON STRUCTURETrack Structure
JSON STRUCTUREScroll for all 11
Examples 11
Example request and response payloads for these APIs.
Car Example
EXAMPLEError Example
EXAMPLELeaderboard Example
EXAMPLEList Cars Response Example
EXAMPLEList Models Response Example
EXAMPLEList Tracks Response Example
EXAMPLEModel Example
EXAMPLETrack Example
EXAMPLEScroll for all 11
Security Posture 4
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
Recommended x-agentic-access execution contracts for AI agents.
Resources
Get Started 4
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 4
Authentication, authorization, and security posture
Operate 3
Status, limits, changes, and where to get help
Commercial 2
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API