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What is Automic Automation?

In order to succeed in the highly competitive digital environment of today, businesses need to implement automation across a diverse range of applications, platforms, and technologies to ensure effective service delivery. Service Orchestration and Automation Platforms are essential for enhancing IT operations and reaping the full advantages of automation; they provide the ability to manage complex workflows that encompass various platforms, such as ERP systems and business applications, spanning from mainframes to microservices within multi-cloud settings. Moreover, optimizing big data pipelines is crucial, as it allows data scientists to access self-service tools while guaranteeing extensive scalability and strong governance over the flow of data. Companies are also required to provide computing, networking, and storage resources both in-house and via the cloud to meet the needs of development and business users. Automic Automation delivers the flexibility, speed, and dependability needed for effective digital business automation, offering a consolidated platform that integrates orchestration and automation functionalities to support and accelerate digital transformation initiatives efficiently. By leveraging these powerful capabilities, organizations can quickly respond to evolving market demands while ensuring their operations remain efficient and productive. Ultimately, this adaptability not only helps in sustaining a competitive edge but also fosters long-term growth and innovation.

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
Hue
Intertrust ExpresssPlay
IronCore Labs
MBX Hatch
OcNOS
Planview Viz
RadiantOne
RunCode
Sematext Cloud
Terminals
Velotix
WINDEV

Integrations Supported

ActiveBatch Workload Automation
Apache Knox
Apache PredictionIO
Apache Ranger
Cloudera Data Platform
DX Unified Infrastructure Management
Hue
Intertrust ExpresssPlay
IronCore Labs
MBX Hatch
OcNOS
Planview Viz
RadiantOne
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

Broadcom

Date Founded

1961

Company Location

United States

Company Website

www.automic.com

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

Application Development

Access Controls/Permissions
Code Assistance
Code Refactoring
Collaboration Tools
Compatibility Testing
Data Modeling
Debugging
Deployment Management
Graphical User Interface
Mobile Development
No-Code
Reporting/Analytics
Software Development
Source Control
Testing Management
Version Control
Web App Development

Continuous Delivery

Application Lifecycle Management
Application Release Automation
Build Automation
Build Log
Change Management
Configuration Management
Continuous Deployment
Continuous Integration
Feature Toggles / Feature Flags
Quality Management
Testing Management

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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