This course is for senior system and storage administrators who are interested in deploying scalable, highly available storage on off-the-shelf hardware and in cloud environments. Students will lea> how to install, configure, and maintain a cluster of Red Hat Storage servers. The course will also explore highly available common Internet file systems (CIFS) and network file systems (NFS) using Clustered Trivial DataBase (CTDB), unified file and object storage, and geo-rep ...

Study points for the exam To help you prepare, the exam objectives highlight the task areas you can expect to see covered in the exam. Red Hat reserves the right to add, modify, and remove exam objectives. Such changes will be made public in advance. Install Red Hat Storage Server on both physical and virtual systems and work with existing Red Hat Storage Server appliances Configure a Red Hat Storage Server storage pool Create individual storage bricks on either physical devices or logical volumes Create various Red Hat Storage Server volumes such as: Distributed Replicated Distributed-replicated Stripe-replicated Distributed-striped Distributed-striped-replicated • Format the volumes with an appropriate file system Create Red Hat Storage Server volume snapshots Extend existing storage volumes by adding additional bricks and performing appropriate rebalancing operations * The following audiences may be interested in earning the Red Hat Certificate of Expertise in Hybrid Cloud Storage: System administrators, architects, and others who need to demonstrate their skills, knowledge, and ability in using Red Hat Storage Server RHCEs interested in pursuing Red Hat Certified Architect (RHCA) Study points for the exam To help you prepare, the exam objectives highlight the task areas you can expect to see covered in the exam. Red Hat reserves the right to add, modify, and remove exam objectives. Such changes will be made public in advance. Install Red Hat Storage Server on both physical and virtual systems and work with existing Red Hat Storage Server appliances Configure a Red Hat Storage Server storage pool Create individual storage bricks on either physical devices or logical volumes Create various Red Hat Storage Server volumes such as: Distributed Replicated Distributed-replicated Stripe-replicated Distributed-striped Distributed-striped-replicated • Format the volumes with an appropriate file system Create Red Hat Storage Server volume snapshots Extend existing storage volumes by adding additional bricks and performing appropriate rebalancing operations Configure clients to use Red Hat Storage Server appliance volumes using native and network file systems (NFS) Configure clients to use Red Hat Storage Server appliance volumes using SMB Configure Red Hat Storage Server features including disk quotas and POSIX access control lists (ACLs) Configure IP failover for NFS-and SMB-based cluster services Configure geo-replication services Configure unified object storage Configure Red Hat Storage Server to support hadoop Troubleshoot Red Hat Storage Server problems Monitor Red Hat Storage Server workloads Perform Red Hat Storage Server management tasks such as tuning volume options, volume migration, stopping and deleting volumes, and configuring server-side quorum As with all Red Hat performance-based exams, configurations must persist after reboot without intervention. Scores and reporting Official scores for exams come exclusively from Red Hat Certification Central. Red Hat does not authorize examiners or training partners to report results to candidates directly. Scores on the exam are usually reported within 3 U.S. business days. Exam results are reported as section scores. Red Hat does not report performance on individual items, nor will it provide additional information upon request. Prerequisites Exam candidates should: Be a Red Hat Certified System Administrator (RHCSA) or have comparable work experience and skills. Have taken the Red Hat Gluster Storage Administration (RH236) course or have work experience using Red Hat Gluster Storage. Recommended course RH236 - R ...

Big Data on AWS introduces you to cloud-based big data solutions such as Amazon Elastic MapReduce (EMR), Amazon Redshift, Amazon Kinesis and the rest of the AWS big data platform. In this course, we show you how to use Amazon EMR to process data using the broad ecosystem of hadoop tools like Hive and Hue. We also teach you how to create big data environments, work with Amazon DynamoDB, Amazon Redshift, and Amazon Kinesis, and leverage best practices to design big data environments for securi ...

Big Data Technology Fundamentals provides baseline general knowledge of the technologies used in big data solutions. It covers the development of big data solutions using the hadoop ecosystem, including MapReduce, HDFS, and the Pig and Hive programming frameworks. This web-based course helps you build a foundation for working with AWS services for big data solutions. This course is offered at no charge, and can be used on its own or to help you prepare for the Big Data on AWS instructor-led ...

Data has become an integral part of every organization, be it small or large; and maintaining it in a proper form has become difficult. hadoop is a revolutionary opensource framework for software programming that took the data storage and processing to next level. hadoop platform is used for structuring data and solves formatting problem for subsequent analytic purposes. hadoop Administration is one of the specialization areas of hadoop framework which helps in hadoop in ...

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This four-day data analyst training course focusing on Apache Pig and Hive and Cloudera Impala will teach you to apply traditional data analytics and business intelligence skills to big data. Cloudera presents the tools data professionals need to access, manipulate, transform, and analyze complex data sets using SQL and familiar scripting languages. Apache Hive makes multi-structured data accessible to analysts, database administrators, and others without Java programming ...

Cloudera University’s three-day Search training course is for developers and data engineers who want to index data in hadoop for more powerful real-time queries. Participants will lea> to get more value from their data by integrating Cloudera Search with external applications. Cloudera Search brings fulltext, interactive search and scalable, flexible indexing to hadoop and an enterprise data hub. Powered by Apache Solr, Search delivers scale and reliability for a new ge ...

This four-day training course for Apache HBase enables participants to store and access massive quantities of multi-structured data and perform hundreds of thousands of operations per second. Apache HBase is a distributed, scalable, NoSQL database built on Apache hadoop. HBase can store data in massive tables consisting of billions of rows and millions of columns, serve data to many users and applications in real time, and provide fast, random read - write access to users ...

This four-day hands-on training course delivers the key concepts and expertise participants need to ingest and process data on a hadoop cluster using the most up-to-date tools and techniques. Employing hadoop ecosystem projects such as Spark, Hive, Flume, Sqoop, and Impala, this training course is the best preparation for the real-world challenges faced by hadoop developers. Participants lea> to identify which tool is the right one to use in a given situation, and will ...