Apache Ambari Training
Introduction to Apache Ambari
Apache Ambari is an open-source management platform for provisioning, managing, and monitoring Apache Hadoop clusters. This module introduces Apache Ambari, covering its core features, architecture, and how it simplifies the management of Hadoop ecosystems.
Setting Up Apache Ambari
Learn how to install and configure Apache Ambari. This section covers system requirements, installation procedures, and initial setup. Explore how to configure your Ambari environment, including setting up clusters and nodes.
Managing Hadoop Clusters
Discover how to use Apache Ambari to manage Hadoop clusters. Learn about cluster configuration, service management, and resource management. Explore how to monitor and optimize cluster performance using Ambari’s tools and features.
Monitoring and Alerting
Understand how to monitor Hadoop clusters with Apache Ambari. Learn about using Ambari’s dashboard for real-time monitoring, setting up alerts, and responding to issues. Explore techniques for managing cluster health and performance.
Service Configuration and Management
Gain insights into configuring and managing Hadoop services through Ambari. Learn about configuring core services like HDFS, YARN, and MapReduce. Explore how to manage service dependencies, perform upgrades, and apply configurations.
Managing Users and Permissions
Learn how to manage users and permissions in Apache Ambari. Explore user roles, access controls, and how to configure security settings for cluster management. Understand how to control access to resources and services within your Hadoop environment.
Backup and Recovery
Discover best practices for backup and recovery in Apache Ambari. Learn about backing up configuration data, recovering from failures, and ensuring data integrity. Explore how to implement backup strategies to protect your Hadoop environment.
Advanced Features and Customization
Explore advanced features and customization options in Apache Ambari. Learn about extending Ambari’s capabilities with plugins, integrating with other tools, and customizing the Ambari interface. Understand how to tailor Ambari to meet specific requirements.
Best Practices and Troubleshooting
Learn best practices for using Apache Ambari effectively and troubleshooting common issues. Explore how to optimize cluster management, address challenges, and ensure smooth operation of your Hadoop environment.
Apache Ambari Training Syllabus
1. Introduction to Apache Ambari
- Overview of Apache Ambari: Features, benefits, and architecture
- Role of Ambari in managing Hadoop clusters
- Comparison with other Hadoop cluster management tools
2. Apache Ambari Installation and Setup
- Installing Ambari Server: Requirements and prerequisites
- Setting up Ambari Agents: Node setup and configuration
- Configuring Ambari Server: Database setup, Configuration settings
3. Ambari Concepts and Terminology
- Understanding Ambari Stacks: Services, Components, and Versions
- Ambari Blueprints: Automated cluster provisioning
- Managing Hadoop Services: Starting, stopping, and configuring services
4. Ambari Web Interface
- Navigating the Ambari Dashboard: Overview and navigation
- Monitoring Cluster Health: Alerts, Metrics, and Heatmaps
- Managing Configurations: Configuration management and overrides
5. Managing Hadoop Services
- Adding and Removing Services: Service management through Ambari
- Configuring Service Components: Custom configurations and properties
- High Availability (HA) Configurations: Setting up HA for critical services
6. Ambari Stacks and Versioning
- Creating and Managing Stacks: Custom stacks and versioning
- Adding Custom Services: Integrating third-party or custom services
- Upgrading Ambari and Hadoop: Version upgrade procedures
7. Ambari Blueprints and Automation
- Creating Blueprints: Defining cluster topologies and configurations
- Automating Cluster Provisioning: Using Blueprints for rapid deployment
- Advanced Blueprint Features: Handling dependencies and custom configurations
8. Security in Ambari
- Securing Ambari: Authentication and authorization mechanisms
- Integration with Kerberos: Configuring Kerberos for secure authentication
- SSL/TLS Configuration: Encrypting communications within the cluster
9. Ambari Metrics and Monitoring
- Monitoring Cluster Performance: Metrics collection and visualization
- Using Grafana and Ambari Metrics: Setting up and configuring dashboards
- Alerting and Notifications: Setting up alerts for critical events
10. Ambari REST API
- Introduction to Ambari REST API: API endpoints and capabilities
- Automating Tasks with Ambari API: Scripting and integration with other tools
- Practical Examples and Use Cases: API calls for common tasks
11. Backup and Disaster Recovery
- Backup Strategies for Ambari: Configuration and database backups
- Disaster Recovery Planning: Restoring Ambari and Hadoop services
12. Performance Tuning and Optimization
- Performance Optimization Techniques: Tuning Hadoop and Ambari configurations
- Capacity Planning: Scaling and resource management
- Monitoring and Tuning JVM Parameters
13. Ambari Views and Customizations
- Introduction to Ambari Views: Using pre-built and custom views
- Creating Custom Views: Developing and integrating custom UI components
- Integrating External Applications: Embedding external applications in Ambari
14. Advanced Topics
- Multi-Tenancy and Resource Isolation: Configuring multi-tenant environments
- Big Data Ecosystem Integration: Integrating Ambari with Apache Spark, Hive, etc.
- Cloud Integration: Managing Hadoop clusters on cloud platforms (AWS, Azure)
15. Real-world Use Cases and Projects
- Implementing Ambari in Production: Use cases across industries
- Project Work: Hands-on projects to apply learned concepts
- Project Planning and Execution: Applying learned concepts
16. Career Development and Job Preparation
- Building a career in Big Data and Hadoop: Skills and certifications
- Interview Preparation: Ambari-related interview questions
- Freelancing and Consulting Opportunities
Training
Basic Level Training
Duration : 1 Month
Advance Level Training
Duration : 1 Month
Project Level Training
Duration : 1 Month
Total Training Period
Duration : 3 Months
Course Mode :
Available Online / Offline
Course Fees :
Please contact the office for details