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Amazon EMR

Amazon EMR is a cloud big data platform for running large-scale distributed data processing jobs, interactive SQL queries, and machine learning applications using open-source analytics frameworks such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto.

agent aware

Solid contracts, transparent operations, and an easy start — typically complete on four or five facets with one clear soft spot.

Kin Score

API Evangelist profiles Amazon EMR the way a machine reads it — 35 machine-readable artifacts across 1 API, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.

Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Amazon EMR scores 68.7/100 (strong), with a separate agent-readiness read of 39/100 (agent aware). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.

Kin Score

This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 68.7/100 · strong
Contract Quality 15.9 / 25
Developer Ergonomics 7.0 / 20
Commercial Clarity 17.9 / 20
Operational Transparency 8.2 / 13
Governance 10.4 / 12
Discoverability 9.3 / 10
Agent readiness — 39/100 · agent aware
Machine-Readable Contract 18 / 18
Agentic Access Contract 15 / 15
MCP Server 0 / 12
Machine-Readable Auth 0 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 7 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 5
Well-Known Catalog 0 / 4
Consent & Bot Identity 0 / 3

How we profile Amazon EMR

Each block below is one kind of artifact we hold for Amazon EMR. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.

APIs 1

Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.

Individual APIs this provider publishes, each with its own machine-readable definition.

Amazon EMR Clusters API

Operations for creating, managing, and terminating EMR clusters

Postman Collections 1

A runnable collection turns the contract into something a developer can execute in seconds. We profile them because the fastest way to trust an API is to make a real call against it.

Ready-to-run Postman collections for exercising this provider's APIs.

Open Collections 1

Open, tool-agnostic collections carry the same runnable value as Postman without locking you to one client — the portable, forkable form of the same exercise.

Open, tool-agnostic API collections (OpenAPI-derived and Bruno).

Amazon EMR API

OPEN COLLECTION

Arazzo Workflows 6

Real integrations are rarely a single call. Arazzo describes the multi-step sequences — auth, then create, then confirm — so both a human and an agent can follow the choreography, not just the endpoints.

Multi-step API workflows described with the Arazzo specification.

Amazon EMR Launch a Cluster With Processing Steps

Create a cluster and queue processing steps to run as soon as it starts.

ARAZZO

Amazon EMR Launch a Hadoop and Hive Cluster

Create an EMR cluster with the Hadoop and Hive applications installed.

ARAZZO

Amazon EMR Launch an HBase Cluster

Create an EMR cluster with the Apache HBase application installed.

ARAZZO

Amazon EMR Launch a Presto Query Cluster

Create an EMR cluster with the Presto application for interactive SQL.

ARAZZO

Amazon EMR Launch a Spark Cluster

Create and start a new EMR cluster pre-configured to run Apache Spark.

ARAZZO

Amazon EMR Run a Spark ETL Job

Launch a Spark cluster and queue an ETL processing step in one call.

ARAZZO

Pricing Plans 1

Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.

Published pricing tiers and plan structures.

Rate Limits 1

Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.

Documented rate limits and quota policies.

Amazon Emr Rate Limits

5 limits

RATE LIMITS

FinOps 1

Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.

Cost, billing, and metering signals for API financial operations.

Features 5

The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.

Notable capabilities this provider offers.

Apache Spark Support

Run Apache Spark jobs for large-scale data processing and machine learning

Auto Scaling

Automatically adjust cluster size based on workload demand

Spot Instance Integration

Use EC2 Spot instances to reduce costs up to 90%

EMR Serverless

Run analytics without provisioning or managing clusters

Studio Notebooks

Develop and debug jobs using EMR Studio Jupyter notebooks

Semantic Vocabularies 1

JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.

JSON-LD contexts and semantic vocabularies used across these APIs.

Amazon Emr Context

0 classes · 2 properties

JSON-LD

Spectral Rules 2

Governance rulesets we run against this provider's specs — the automated checks behind parts of the score. Profiling them makes the quality bar explicit and re-runnable, not a matter of opinion.

Amazon EMR API Rules

5 rules · 3 warnings

SPECTRAL

Amazon EMR API Rules

21 rules · 10 errors · 10 warnings

SPECTRAL

JSON Schema 1

Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.

Standalone JSON Schema definitions for this provider's data models.

Amazon EMR Cluster

9 properties

JSON SCHEMA

JSON Structure 1

JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.

JSON Structure definitions describing this provider's data shapes.

Amazon Emr Structure

9 properties

JSON STRUCTURE

Examples 1

Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.

Example request and response payloads for these APIs.

Amazon Emr Example

9 fields

EXAMPLE

Security Posture 3

Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Amazon Emr Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Amazon Emr Vulnerability Disclosure

security.txt · contact published

SECURITY

Amazon Emr Trust Center

PCI DSS, HIPAA, FedRAMP, GDPR, FIPS 140

SECURITY

Agentic Access 1

An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.

Recommended x-agentic-access execution contracts for AI agents.

Amazon Emr Agentic Access

1 operation · 1 acting

1 operations · 1 acting

AGENTIC

Use Cases 4

What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.

What developers build with this provider.

ETL Data Processing

Extract, transform, and load large datasets across data lakes and warehouses

Machine Learning

Train machine learning models on large datasets using Spark MLlib

Log Analytics

Process and analyze application logs at petabyte scale

Financial Risk Analysis

Run Monte Carlo simulations and risk models on large datasets

Integrations 4

Pre-built integrations with other platforms tell you where this provider already fits in a stack.

Pre-built integrations with other platforms and tools.

Amazon S3

Use S3 as data lake storage for EMR clusters

AWS Glue

Integrate with Glue Data Catalog for metadata management

Amazon Athena

Query data processed by EMR using Athena SQL

Amazon SageMaker

Hand off processed data to SageMaker for model training

Resources

Every other property we hold for Amazon EMR — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.

Documentation 1

Reference material describing how the API behaves

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 8

Pagination, idempotency, versioning, errors, and events

Scroll within the panel for all 8 ·

Build 2

SDKs, sample code, and the tooling you integrate with

Learn 1

Tutorials, courses, talks, and written guidance

Commercial 2

Pricing, plans, and the legal terms of use

Company 1

The organization behind the API

Other 1

Properties that don't map to a standard resource type

← All providers · Data indexed from github.com/api-evangelist/amazon-emr · machine-readable index on apis.io