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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
Mesos operates on principles similar to those of the Linux kernel, yet it functions at a different abstraction level. This Mesos kernel is deployed on each machine and offers APIs for managing resources and scheduling tasks for applications like Hadoop, Spark, Kafka, and Elasticsearch across entire cloud infrastructures and data centers. It includes native capabilities for launching containers using Docker and AppC images. Additionally, it allows both cloud-native and legacy applications to coexist within the same cluster through customizable scheduling policies. Developers can utilize HTTP APIs to create new distributed applications, manage the cluster, and carry out monitoring tasks. Furthermore, Mesos features an integrated Web UI that allows users to observe the cluster's status and navigate through container sandboxes efficiently. Overall, Mesos provides a versatile and powerful framework for managing diverse workloads in modern computing environments.
API Access
Has API
API Access
Has API
Integrations
ActiveBatch Workload Automation
Apache Flink
Apache Knox
Apache OpenWhisk
Apache PredictionIO
Apache Ranger
Cloudera Data Platform
Docker
IronCore Labs
Kapacitor
Integrations
ActiveBatch Workload Automation
Apache Flink
Apache Knox
Apache OpenWhisk
Apache PredictionIO
Apache Ranger
Cloudera Data Platform
Docker
IronCore Labs
Kapacitor
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
Apache Software Foundation
Founded
1999
Country
United States
Website
mesos.apache.org
Product Features
Product Features
Cloud Management
Access Control
Billing & Provisioning
Capacity Analytics
Cost Management
Demand Monitoring
Multi-Cloud Management
Performance Analytics
SLA Management
Supply Monitoring
Workflow Approval
Container Management
Access Control
Application Development
Automatic Scaling
Build Automation
Container Health Management
Container Storage
Deployment Automation
File Isolation
Hybrid Deployments
Network Isolation
Orchestration
Shared File Systems
Version Control
Virtualization