Apache NiFi Training Course 

(up to 4 days: 3 days for Administrator + 1 day for Developers) 

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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.

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Why Learn Apache NiFi?

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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.

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At the end of this training, you will be able to:

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Administrators

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• Install and configure Apachi NiFi

• Source, transform and manage data

• Automate dataflows

• Enable streaming analytics

• Apply various approaches for data ingestion

• Transform Big Data

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Developers

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• Understand NiFi's architecture and dataflow concepts

• Develop extensions using NiFi and third-party APIs

• Custom develop their own Apache Nifi processor

• Ingest and process real-time data from disparate and uncommon file formats and data sources

 

 

Course details

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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.

 

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Course Outline

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1. Administrators:

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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

• Load Balancing/Redundancy

• Mass Orchestration of NiFi (via Ansible)

 

NiFi Operations

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• Database Aggregating, Splitting and Transforming

• Data Extractions, Logging, etc.

• Integrating with Splunk (optional)

 

Monitoring and Recovery

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• Recovering without Data Loss

• Autonomous Recovery

 

Optimizing NiFI

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• Performance tuning

• Optimizing Nifi Setup

 

Best practices

 

Troubleshooting

 

Summary and Conclusion

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2. Developers:

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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

• 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

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