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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
IBM® Workload Automation offers a robust solution for managing both batch and real-time hybrid workloads, whether on distributed systems, mainframes, or in the cloud. Enhance your workload management capabilities with a solution driven by analytics. The latest version, Workload Automation 9.5, unveils innovative features that significantly enhance the management of enterprise workloads while streamlining automation processes. By centralizing management and eliminating manual interventions, you can make better decisions and lower operational costs. This solution also fosters greater agility in development and aligns seamlessly with the DevOps toolchain, enhancing both business and infrastructure responsiveness. Users can tailor workload dashboards, providing developers and operators with autonomy and precise governance. Its contemporary interface facilitates quick, data-driven decision-making, while customization options are made simple with integrated widgets that support data from any REST API. Furthermore, users can leverage catalogs and services to execute routine business tasks, enabling the running and monitoring of processes conveniently from a mobile device, thus ensuring flexibility and efficiency in workflow management.
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
Hue
IBM Cloud
IronCore Labs
RunCode
Integrations
ActiveBatch Workload Automation
Apache Knox
Apache PredictionIO
Apache Ranger
Cloudera Data Platform
DX Unified Infrastructure Management
Hue
IBM Cloud
IronCore Labs
RunCode
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
IBM
Founded
1911
Country
United States
Website
www.ibm.com/products/workload-automation
Product Features
Product Features
Workload Automation
Alerts / Notifications
Audit Trails
Business Process Management
Cross-Platform Scheduling
Dashboard
Data Analysis / Visualization
Event-Triggers
Load Balancing
Resource-Based Scheduling
Robotic Process Automation (RPA)
Workflow Foundation Support