Five tools for managing hadoop Clusters

When using hadoop for big data analysis and processing, you must first make sure that you configure, deploy, and manage clusters. This is neither easy nor fun, but is loved by developers. This article provides five tools to help you achieve this.

Apache ambari

Apache ambari is an open-source project for hadoop monitoring, management, and lifecycle management. It is also a project that selects management for the hortonworks data platform. Ambari provides services to hadoop mapreduce, HDFS, hbase, pig, hive, hcatalog, and zookeeper.

 

Apache mesos

Apache mesos is a cluster manager that allows users to agree to run multiple hadoop tasks or other high-performance applications on the cluster at the same time. Chris aniszczyk, open-source Manager for Twitter, said mesos can run on hundreds of devices and make it easier to perform work.

Platform mapreduce

Platform mapreduce provides enterprise-level manageability and scalability, high resource utilization and availability, convenient operations, multi-application support, and an open distributed system architecture, including for hadoop Distributed File System (HDFS) and appistry cloud IQ Instant Support, more file systems and platforms will be supported later, which will ensure that enterprises are more concerned about migrating mapreduce applications to the production environment.

Stackiq rocks + Big Data

Stackiq rock + big data is a rocks commercial circulation cluster management software. The company has strengthened support for Apache hadoop. Rock + supports distribution of Apache, cloudera, hortonworks, and mapr, and manages hadoop cluster configuration from bare metal servers.

Zettaset Orchestrator

Zettaset Orchestrator is an end-to-end hadoop management product that supports distribution of multiple hadoop instances. Zettaset highlights orchestrator's UI-based experience and maaps (management, availability, automation, configuration, and security) processing capabilities.