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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

Introducing Kubestone, the operator designed for benchmarking within Kubernetes environments. Kubestone allows users to assess the performance metrics of their Kubernetes setups effectively. It offers a standardized suite of benchmarks to evaluate CPU, disk, network, and application performance. Users can exercise detailed control over Kubernetes scheduling elements, including affinity, anti-affinity, tolerations, storage classes, and node selection. It is straightforward to introduce new benchmarks by developing a fresh controller. The execution of benchmark runs is facilitated through custom resources, utilizing various Kubernetes components such as pods, jobs, deployments, and services. To get started, refer to the quickstart guide which provides instructions on deploying Kubestone and running benchmarks. You can execute benchmarks via Kubestone by creating the necessary custom resources within your cluster. Once the appropriate namespace is created, it can be utilized to submit benchmark requests, and all benchmark executions will be organized within that specific namespace. This streamlined process ensures that you can easily monitor and analyze the performance of your Kubernetes applications.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

ActiveBatch Workload Automation Yes 
Apache Knox Yes 
Apache PredictionIO Yes 
Apache Ranger Yes 
Astera Dataprep Yes 
Cloudera Data Platform Yes 
DX Unified Infrastructure Management Yes 
Hue Yes 
IronCore Labs Yes 
Kubernetes No 
RunCode Yes 
Sematext Cloud Yes 
Terminals Yes 
Velotix Yes 
WINDEV Yes 

Integrations

ActiveBatch Workload Automation No 
Apache Knox No 
Apache PredictionIO No 
Apache Ranger No 
Astera Dataprep No 
Cloudera Data Platform No 
DX Unified Infrastructure Management No 
Hue No 
IronCore Labs No 
Kubernetes Yes 
RunCode No 
Sematext Cloud No 
Terminals No 
Velotix No 
WINDEV No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

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

Kubestone

Website

kubestone.io/en/latest/

Product Features

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