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

  • Install and configure Apachi NiFi

  • Source, transform and manage data

  • Automate dataflows

  • Enable streaming analytics

  • Apply various approaches for data ingestion

  • Transform Big Data

Developers

  • 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

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

  • Data at rest vs data in motion

 

Overview of Big Data and Apache Hadoop

  • HDFS and MapReduce architecture

 

Setting up and Running a NiFi Cluster

  • Cluster Integration

  • Load Balancing/Redundancy

  • Mass Orchestration of NiFi (via Ansible)

 

NiFi Operations

  • Database Aggregating, Splitting and Transforming

  • Data Extractions, Logging, etc.

  • Integrating with Splunk (optional)

 

Monitoring and Recovery

  • Recovering without Data Loss

  • Autonomous Recovery

 

Optimizing NiFI

  • Performance tuning

  • Optimizing Nifi Setup

 

Best practices

 

Troubleshooting

 

Summary and Conclusion

2. Developers:

Introduction

  • Data at rest vs data in motion

 

Overview of Big Data Tools and Technologies

  • Hadoop (HDFS and MapReduce) and Spark

 

Installing and Configuring NiFi

 

Overview of NiFi Architecture

 

Development Approaches

  • 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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