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What is Automate Schedule?

Effective workload automation supports centralized job scheduling specifically for Linux environments. By streamlining workflows across diverse platforms like Windows, UNIX, Linux, and IBM i via a job scheduler, your IT team can concentrate on more impactful initiatives that enhance overall profitability. Shift away from fragmented job schedules managed by tools like cron or Windows Task Scheduler towards a unified enterprise solution. Improved integration of your job scheduler with essential software applications provides a holistic view, fosters data utilization across the organization, and efficiently consolidates job schedules. This approach not only boosts operational efficiency but also helps in achieving your workload automation goals more effectively. Automated job scheduling transforms your business operations and simplifies management tasks. Develop dynamic, event-driven job schedules that consider dependencies across numerous servers to better align with your organizational objectives. Furthermore, Automate Schedule offers high availability with a master server and a standby server, ensuring that vital tasks continue uninterrupted during outages, thus maintaining seamless operations. This enhanced reliability can significantly strengthen your team's responsiveness to unexpected challenges, allowing for a more resilient operational framework. Ultimately, embracing robust automation can lead to a transformative impact on your business's agility and efficiency.

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.

Media

Media

Integrations Supported

ActiveBatch Workload Automation
Apache Knox
Apache PredictionIO
Apache Ranger
Cloudera Data Platform
DX Unified Infrastructure Management
Fortra Automate
Hue
IBM i
IronCore Labs
RunCode
Sematext Cloud
Terminals
Velotix
WINDEV

Integrations Supported

ActiveBatch Workload Automation
Apache Knox
Apache PredictionIO
Apache Ranger
Cloudera Data Platform
DX Unified Infrastructure Management
Fortra Automate
Hue
IBM i
IronCore Labs
RunCode
Sematext Cloud
Terminals
Velotix
WINDEV

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Fortra

Date Founded

1982

Company Location

United States

Company Website

www.fortra.com/products/automate-schedule

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

Categories and Features

Data Center Management

Audit Trail
Behavior-Based Acceleration
Cross Reference System
Device Auto Discovery
Diagnostic Testing
Import / Export Data
JCL Management
Multi-Platform
Multi-User
Power Management
Sarbanes-Oxley Compliance

DevOps

Approval Workflow
Dashboard
KPIs
Policy Management
Portfolio Management
Prioritization
Release Management
Timeline Management
Troubleshooting Reports

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

Categories and Features

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