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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
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
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
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