Amazon EMR Containers

Name: Amazon EMR Containers API
Brand: Amazon EMR Containers
Availability: InStock

★ Only Publicly Available OpenAPI DocumentCloud InfrastructureContainer OrchestrationapiKey19 EndpointsREST

For Agents

Submit Spark jobs to EMR on EKS, manage virtual clusters, job templates, and managed endpoints through a single API.

Quickstart

Get started with Amazon EMR Containers in minutes using your preferred integration method.

# Add to your MCP client config (Claude Desktop, Cursor, Windsurf)
{
  "jentic": {
    "url": "https://api.jentic.com/mcp",
    "auth": "oauth"
  }
}

# Then ask your agent:
"submit a Spark job to EMR on EKS"

# → Jentic returns the GET /events tool with parameter schema, agent executes.

Capabilities

What an agent can do with Amazon EMR Containers API.

Submit Spark job runs with custom configurations, monitoring, and execution roles

Create reusable job templates with parameter overrides for repeatable submissions

Manage interactive endpoints that expose Jupyter and Livy interfaces on EKS

GET STARTED

Start building with Amazon EMR Containers API

Explore with Jentic

View OpenAPI Document

Use for: I need to submit a Spark job to EMR on EKS, Register a new virtual cluster against my EKS namespace, List all running job runs in this virtual cluster, Cancel a Spark job that has been running too long

Not supported: Does not handle EKS cluster creation, container image builds, or non-Spark workloads — use for Spark on EKS job submission and virtual cluster management only.

Jentic publishes the only available OpenAPI document for Amazon EMR Containers, keeping it validated and agent-ready.

Jentic publishes the only available OpenAPI specification for Amazon EMR Containers, keeping it validated and agent-ready. Amazon EMR on EKS lets data teams run open-source big-data frameworks such as Apache Spark on existing Amazon EKS clusters. The API manages virtual clusters that map to EKS namespaces, job runs that submit Spark workloads, managed endpoints, and reusable job templates. It is designed for analytics platform teams that want EMR's runtime optimisations and managed Spark images while consolidating on Kubernetes for compute.

Use Cases

Patterns agents use Amazon EMR Containers API for, with concrete tasks.

★ Spark Job Submission on EKS

Data engineering teams use Amazon EMR on EKS to run Spark workloads on shared Kubernetes clusters instead of standing up dedicated EMR EC2 clusters. The API submits job runs with execution role, release label, and Spark configuration so that pipelines can run hundreds of jobs per day on a single virtual cluster. EMR on EKS shares cluster resources between workloads, reducing idle compute compared with per-job EMR clusters.

Submit a Spark job run to virtual cluster vc-prod with release label emr-6.10.0-latest, executing s3://etl/scripts/load.py with execution role role-etl.

Reusable Job Templates

Platform teams use job templates to standardise Spark configuration, IAM roles, and monitoring across many submissions. The API stores templates with parameterised fields so analyst-submitted jobs inherit guardrails such as max executor count and security configuration without hand-editing each run. Templates also keep job submissions short and reduce the surface area for drift between environments.

Create a job template named nightly-etl with release emr-6.10.0-latest, default execution role role-etl, and a parameter inputDate that overrides the script argument.

Interactive Spark Endpoints

Data science teams use managed endpoints to expose Livy or Jupyter access into the EKS-hosted Spark environment for ad-hoc analysis. The API creates and tears down endpoints with custom Spark configuration so notebooks connect to a curated runtime without leaving the cluster. This shortens the path from notebook prototype to a productionised job template.

Create a managed endpoint of type JUPYTER_ENTERPRISE_GATEWAY in virtual cluster vc-prod with execution role role-etl and release emr-6.10.0-latest.

Agent-Driven Spark Job Operations via Jentic

AI agents use the EMR Containers API through Jentic to dispatch Spark jobs in response to upstream events such as new files in S3 or detected anomalies. Jentic exposes EMR on EKS operations as discoverable tools so an agent can search by intent and launch a parameterised job in seconds. This removes the need for a dedicated orchestration layer for one-off and event-driven jobs.

Search Jentic for submit spark job, load the StartJobRun schema, and execute it for virtual cluster vc-prod using job template nightly-etl with parameter inputDate=2026-06-09.

Key Endpoints

19 endpoints — jentic publishes the only available openapi specification for amazon emr containers, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

POST

/virtualclusters

Create a virtual cluster

GET

/virtualclusters

List virtual clusters

DELETE

/virtualclusters/{virtualClusterId}

Delete a virtual cluster

POST

/virtualclusters/{virtualClusterId}/jobruns

Submit a Spark job run

DELETE

/virtualclusters/{virtualClusterId}/jobruns/{jobRunId}

Cancel a job run

POST

/virtualclusters/{virtualClusterId}/endpoints

Create a managed endpoint

POST

/jobtemplates

Create a reusable job template

POST

/virtualclusters

Create a virtual cluster

GET

/virtualclusters

List virtual clusters

DELETE

/virtualclusters/{virtualClusterId}

Delete a virtual cluster

POST

/virtualclusters/{virtualClusterId}/jobruns

Submit a Spark job run

DELETE

/virtualclusters/{virtualClusterId}/jobruns/{jobRunId}

Cancel a job run

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

AWS access keys for EMR on EKS are stored encrypted in the Jentic vault. Agents receive scoped, short-lived signing access — raw secret access keys never enter the agent context.

Intent-based discovery

Agents search by intent (for example submit a spark job) and Jentic returns matching EMR Containers operations with their input schemas, so the agent can call the right endpoint without browsing AWS docs.

Time to first call

Direct EMR on EKS integration: 1-2 days for SigV4 signing, virtual cluster setup, and job-driver formatting. Through Jentic: under 30 minutes — search, load schema, execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Complementary

Amazon EKS

Provides the underlying Kubernetes cluster that EMR on EKS runs against

Choose EKS when you need to manage the cluster, namespaces, or RBAC that host EMR workloads.

Alternative

AWS Lambda

Serverless functions for short-lived data processing

Choose Lambda when the workload is small, single-record, and does not need a Spark runtime.

Complementary

Amazon EventBridge

Triggers EMR job submissions in response to upstream events

Choose EventBridge when EMR jobs should run on a schedule or when an upstream event arrives.

FAQs

Specific to using Amazon EMR Containers API through Jentic.

Why is there no official OpenAPI spec for Amazon EMR Containers?

AWS does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Amazon EMR Containers via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.

What authentication does the Amazon EMR Containers API use?

EMR on EKS uses AWS Signature Version 4 request signing. Through Jentic, AWS access keys are stored encrypted in the vault and signing happens server-side, so the agent never sees the raw secret access key.

Can I submit Spark jobs through this API?

Yes. POST /virtualclusters/{virtualClusterId}/jobruns submits a Spark job with a release label, execution role, and job driver configuration. The job runs in the EKS namespace mapped by the virtual cluster.

What are the rate limits for the Amazon EMR Containers API?

AWS applies per-account, per-region API throttling. Job submission and describe calls have separate buckets. Use exponential backoff on ThrottlingException responses; AWS does not publish exact TPS numbers in the spec.

How do I cancel a long-running Spark job through Jentic?

Search Jentic for cancel emr job run, load the schema for DELETE /virtualclusters/{virtualClusterId}/jobruns/{jobRunId}, and execute it with the virtual cluster ID and job run ID. Jentic returns the cancellation acknowledgement.

Do I need an existing EKS cluster to use this API?

Yes. EMR on EKS runs workloads inside an EKS cluster you already operate. You must register the EKS cluster as a virtual cluster, which maps EMR submissions to a specific Kubernetes namespace.