Apache Ambari Training

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Course level:Intermediate
Apache Ambari is an open-source management platform designed for provisioning, managing, and monitoring Apache Hadoop clusters. It simplifies the deployment and management of Hadoop ecosystems, making it easier for administrators to configure and monitor the health and performance of the Hadoop environment. Apache Ambari provides a user-friendly web interface and RESTful APIs for managing clusters, services, and components of the Hadoop stack.
Apache Ambari Training
Apache Ambari Training – Learn Online

Why should you choose Nisa For Apache Ambari Training?

Nisa Trainings is the best online training platform for conducting one-on-one interactive live sessions with a 1:1 student-teacher ratio. You can gain hands-on experience by working on near-real-time projects under the guidance of our experienced faculty. We support you even after the completion of the course and happy to clarify your doubts anytime. Our teaching style at Nisa Trainings is entirely hands-on. You’ll have access to our desktop screen and will be actively conducting hands-on labs on your desktop.

Job Assistance

If you face any problem while working on Apache Ambari Course, then Nisa Trainings is simply a Call/Text/Email away to assist you. We offer Online Job Support for professionals to assist them and to solve their problems in real-time.

The Process we follow for our Online Job Support Service:

  • We receive your inquiry for Online Job
  • We will arrange a telephone call with our consultant to grasp your complete requirement and the tools you’re
  • If our consultant is 100% confident in taking up your requirement and when you are also comfortable with our consultant, we will only agree to provide service. And then you have to make the payment to get the service from
  • We will fix the timing for Online Job Support as mutually agreed by you and our consultant.

Course Information

Apache Ambari Training
Duration: 25 Hours
Timings: Weekdays (1-2 Hours per day) [OR] Weekends (2-3 Hours per day)
Training Method: Instructor Led Online One-on-One Live Interactive
Sessions.

COURSE CONTENT :

Module 1: Introduction to Apache Ambari and Hadoop Ecosystem
  • Overview of Apache Hadoop Ecosystem
    • Introduction to Hadoop and its components (HDFS, YARN, Hive, HBase, etc.)
    • Importance of cluster management and monitoring
  • What is Apache Ambari?
    • Purpose of Apache Ambari in Hadoop cluster management
    • Ambari’s architecture and components
    • Benefits of using Apache Ambari for Hadoop management
Module 2: Installing Apache Ambari
  • Preparing the Environment
    • Prerequisites for Ambari installation (hardware, software, network configurations)
    • Understanding Ambari architecture (Ambari Server and Agents)
  • Installing Ambari Server
    • Step-by-step installation on a single node
    • Installing Ambari Agent on cluster nodes
    • Verifying the installation and Ambari components
  • Setting Up Ambari Repositories
    • Configuring repositories for Ambari and Hadoop components
    • Updating and patching Ambari
Module 3: Configuring Apache Ambari
  • Cluster Setup with Ambari
    • Launching the Ambari Web UI
    • Configuring basic settings for Ambari Server
    • Setting up a multi-node Hadoop cluster using Ambari
    • Configuring Ambari Services (HDFS, YARN, Hive, HBase, etc.)
  • Adding and Removing Nodes
    • Adding new nodes to the cluster
    • Removing nodes from the cluster
    • Managing node health and status
Module 4: Cluster and Service Management
  • Managing Hadoop Services with Ambari
    • Configuring HDFS, YARN, Hive, HBase, and other Hadoop services
    • Understanding service dependencies and configurations
    • Starting, stopping, and restarting services through Ambari
  • Service Configuration and Customization
    • Modifying service configurations using Ambari UI
    • Setting up service-specific configurations (memory, replication factor, etc.)
  • Configuring Data Sources and Services
    • Setting up and configuring databases (e.g., Hive Metastore)
    • Managing external services and integrations
Module 5: Monitoring and Administration
  • Monitoring Cluster Health
    • Using Ambari Dashboard for cluster health checks
    • Monitoring resource utilization (CPU, memory, disk, etc.)
    • Viewing and analyzing service and host metrics
  • Setting Up Alerts and Notifications
    • Configuring health checks and alerts for services and hosts
    • Setting up email or SMS notifications for critical events
  • Log Management and Troubleshooting
    • Accessing and viewing service logs through Ambari
    • Using Ambari to troubleshoot common issues and errors
    • Using Ambari for performance tuning and optimization
Module 6: Security and High Availability
  • Cluster Security and Authentication
    • Configuring Kerberos authentication for secure communication
    • Integrating Ambari with LDAP or Active Directory for user management
    • Role-based access control (RBAC) in Ambari
  • High Availability Setup
    • Configuring High Availability for Ambari Server
    • Setting up HDFS and YARN for high availability
    • Configuring failover mechanisms for services like HBase and Hive
Module 7: Automating with Ambari REST API
  • Introduction to Ambari REST API
    • Overview of Ambari REST API and its capabilities
    • Authentication and authorization for Ambari API access
  • Using REST API for Cluster Management
    • Automating cluster provisioning and scaling using APIs
    • Accessing cluster health and performance metrics programmatically
  • Ambari API for Configuration and Deployment
    • Managing services and configurations via REST API
    • Integrating Ambari with other automation tools (Ansible, Puppet, etc.)
Module 8: Managing Users and Resources
  • User and Group Management in Ambari
    • Adding, modifying, and deleting users and groups in Ambari
    • Assigning roles and permissions for cluster resources
    • Managing service-level permissions and access control
  • Resource Management and Quotas
    • Managing resource usage across nodes and services
    • Setting and managing quotas for resource allocation (memory, CPU, etc.)
    • Using Ambari for efficient capacity planning
Module 9: Troubleshooting and Performance Optimization
  • Cluster Troubleshooting Best Practices
    • Identifying common issues with services and nodes
    • Using Ambari logs for debugging and diagnostics
    • Handling service failures and recovery
  • Performance Tuning and Optimization
    • Tuning configurations for better cluster performance
    • Monitoring resource usage and optimizing service allocation
    • Capacity planning for large Hadoop clusters
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