Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Google Cloud Run Reviews & Ratings
    4.5 out of 5 stars 352 Ratings
    Company Website for Google Cloud Run
  • ActiveBatch Workload Automation Reviews & Ratings
    4.5 out of 5 stars 383 Ratings
    Company Website for ActiveBatch Workload Automation
  • JAMS Scheduler Reviews & Ratings
    4.5 out of 5 stars 285 Ratings
    Company Website for JAMS Scheduler
  • JS7 JobScheduler Reviews & Ratings
    5.0 out of 5 stars 1 Rating
    Company Website for JS7 JobScheduler
  • Stonebranch Reviews & Ratings
    4.5 out of 5 stars 190 Ratings
    Company Website for Stonebranch
  • RunMyJobs by Redwood Reviews & Ratings
    4.8 out of 5 stars 429 Ratings
    Company Website for RunMyJobs by Redwood
  • Chainstack Reviews & Ratings
    4.8 out of 5 stars 35 Ratings
    Company Website for Chainstack
  • Resource Guru Reviews & Ratings
    4.6 out of 5 stars 1,056 Ratings
    Company Website for Resource Guru
  • Bacula Enterprise Reviews & Ratings
    4.5 out of 5 stars 125 Ratings
    Company Website for Bacula Enterprise
  • Ganttic Reviews & Ratings
    4.3 out of 5 stars 242 Ratings
    Company Website for Ganttic

What is Apache Hadoop YARN?

The fundamental principle of YARN centers on distributing resource management and job scheduling/monitoring through the use of separate daemons for each task. It features a centralized ResourceManager (RM) paired with unique ApplicationMasters (AM) for every application, which can either be a single job or a Directed Acyclic Graph (DAG) of jobs. In tandem, the ResourceManager and NodeManager establish the computational infrastructure required for data processing. The ResourceManager acts as the primary authority, overseeing resource allocation for all applications within the framework. In contrast, the NodeManager serves as a local agent on each machine, managing containers, monitoring their resource consumption—including CPU, memory, disk, and network usage—and communicating this data back to the ResourceManager/Scheduler. Furthermore, the ApplicationMaster operates as a dedicated library for each application, tasked with negotiating resource distribution with the ResourceManager while coordinating with the NodeManagers to efficiently execute and monitor tasks. This clear division of roles significantly boosts the efficiency and scalability of the resource management system, ultimately facilitating better performance in large-scale computing environments. Such an architecture allows for more dynamic resource allocation and the ability to handle diverse workloads effectively.

What is Amazon EKS?

Amazon Elastic Kubernetes Service (EKS) provides an all-encompassing solution for Kubernetes management, fully managed by AWS. Esteemed companies such as Intel, Snap, Intuit, GoDaddy, and Autodesk trust EKS for hosting their essential applications, taking advantage of its strong security features, reliability, and efficient scaling capabilities. EKS is recognized as the leading choice for running Kubernetes due to several compelling factors. A significant benefit is the capability to launch EKS clusters with AWS Fargate, which facilitates serverless computing specifically designed for containerized applications. This functionality removes the necessity of server provisioning and management, allows users to distribute and pay for resources based on each application's needs, and boosts security through built-in application isolation. Moreover, EKS integrates flawlessly with a range of Amazon services, such as CloudWatch, Auto Scaling Groups, IAM, and VPC, ensuring that users can monitor, scale, and balance loads with ease. This deep level of integration streamlines operations, empowering developers to concentrate more on application development instead of the complexities of infrastructure management. Ultimately, the combination of these features positions EKS as a highly effective solution for organizations seeking to optimize their Kubernetes deployments.

Media

Media

Integrations Supported

Apache Knox
Apache PredictionIO
Cloudera Data Platform
Hue

Integrations Supported

Amazon CloudWatch
Amazon Elastic File System (EFS)
Ambient Mesh
Apono
Cequence Security
CloudAvocado
Control Plane
Envoi
Kubegrade
Kuma
NudgeBee
Octopus Deploy
Procyon
ThreatMapper
Traceable
Zesty

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

Uniited States

Company Website

hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/YARN.html

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/eks/

Categories and Features

Job Scheduler

Not specified

Categories and Features

Popular Alternatives

Apache Helix Reviews & Ratings

Apache Helix

Apache Software Foundation

Popular Alternatives

Amazon EC2 Reviews & Ratings

Amazon EC2

Amazon
5.0 out of 5 stars
AWS Fargate Reviews & Ratings

AWS Fargate

Amazon