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Description

YARN's core concept revolves around the division of resource management and job scheduling/monitoring into distinct daemons, aiming for a centralized ResourceManager (RM) alongside individual ApplicationMasters (AM) for each application. Each application can be defined as either a standalone job or a directed acyclic graph (DAG) of jobs. Together, the ResourceManager and NodeManager create the data-computation framework, with the ResourceManager serving as the primary authority that allocates resources across all applications in the environment. Meanwhile, the NodeManager acts as the local agent on each machine, overseeing containers and tracking their resource consumption, including CPU, memory, disk, and network usage, while also relaying this information back to the ResourceManager or Scheduler. The ApplicationMaster functions as a specialized library specific to its application, responsible for negotiating resources with the ResourceManager and coordinating with the NodeManager(s) to efficiently execute and oversee the execution of tasks, ensuring optimal resource utilization and job performance throughout the process. This separation allows for more scalable and efficient management in complex computing environments.

Description

Rkt is an advanced application container engine crafted specifically for contemporary cloud-native environments in production. Its design incorporates a pod-native methodology, a versatile execution environment, and a clearly defined interface, making it exceptionally compatible with other systems. The fundamental execution unit in rkt is the pod, which consists of one or more applications running in a shared context, paralleling the pod concept used in Kubernetes orchestration. Users can customize various configurations, including isolation parameters, at both the pod level and the more detailed per-application level. In rkt, each pod operates directly within the traditional Unix process model, meaning there is no central daemon, allowing for a self-sufficient and isolated environment. Rkt also adopts a contemporary, open standard container format known as the App Container (appc) specification, while retaining the ability to run other container images, such as those generated by Docker. This flexibility and adherence to standards contribute to rkt's growing popularity among developers seeking robust container solutions.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

ActiveBatch Workload Automation
Apache Knox
Apache PredictionIO
Apache Ranger
Cloudera Data Platform
DX Unified Infrastructure Management
Docker
Fedora CoreOS
Google Cloud Container Registry
Hue
IronCore Labs
Kubernetes
RunCode
Sematext Cloud
Terminals
Velotix
WINDEV

Integrations

ActiveBatch Workload Automation
Apache Knox
Apache PredictionIO
Apache Ranger
Cloudera Data Platform
DX Unified Infrastructure Management
Docker
Fedora CoreOS
Google Cloud Container Registry
Hue
IronCore Labs
Kubernetes
RunCode
Sematext Cloud
Terminals
Velotix
WINDEV

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

Uniited States

Website

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

Vendor Details

Company Name

Red Hat

Country

United States

Website

cloud.redhat.com/learn/topics/rkt

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