Apache NiFi Training Course
(up to 4 days: 3 days for Administrator + 1 day for Developers)
Note: this outline is our proposal, but the training can be tailored to your specific requirements upon prior request ahead of the proposed course date.
Why Learn Apache NiFi?
Apache NiFi is an open source platform for automating and managing data flow between systems. It is an efficient and reliable data processing and delivery system. It offers a web-based user interface for building, tracking , and managing data flows. It has a fully customizable and configurable data flow mechanism that can change data during runtime. It is easily extensible by designing custom components.
At the end of this training, you will be able to:
Administrators
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Install and configure Apachi NiFi
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Source, transform and manage data
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Automate dataflows
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Enable streaming analytics
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Apply various approaches for data ingestion
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Transform Big Data
Developers
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Understand NiFi's architecture and dataflow concepts
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Develop extensions using NiFi and third-party APIs
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Custom develop their own Apache Nifi processor
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Ingest and process real-time data from disparate and uncommon file formats and data sources
Course details
The agenda covers both fundamentals and advanced topics.
The final training outline will be designed depending on your particular requirements.
The practical exercises constitute a big part of the course time, besides demonstrations and theoretical presentations. Discussions and questions can be asked throughout the course.
Course Outline
1. Administrators:
Introduction to Apache NiFi
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Data at rest vs data in motion
Overview of Big Data and Apache Hadoop
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HDFS and MapReduce architecture
Setting up and Running a NiFi Cluster
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Cluster Integration
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Load Balancing/Redundancy
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Mass Orchestration of NiFi (via Ansible)
NiFi Operations
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Database Aggregating, Splitting and Transforming
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Data Extractions, Logging, etc.
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Integrating with Splunk (optional)
Monitoring and Recovery
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Recovering without Data Loss
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Autonomous Recovery
Optimizing NiFI
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Performance tuning
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Optimizing Nifi Setup
Best practices
Troubleshooting
Summary and Conclusion
2. Developers:
Introduction
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Data at rest vs data in motion
Overview of Big Data Tools and Technologies
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Hadoop (HDFS and MapReduce) and Spark
Installing and Configuring NiFi
Overview of NiFi Architecture
Development Approaches
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Application development tools and mindset
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Extract, Transform, and Load (ETL) tools and mindset
Design Considerations
Components, Events, and Processor Patterns
Exercise: Streaming Data Feeds into HDFS
Error Handling
Controller Services
Exercise: Ingesting Data from IoT Devices using Web-Based APIs
Exercise: Developing a Custom Apache Nifi Processor using JSON
Testing and Troubleshooting
Contributing to Apache NiFi
Summary and Conclusion