Course Outline
Core Concepts of NiFi and Data Flow
- Distinguishing data in motion from data at rest: key concepts and associated challenges
- NiFi architecture overview: cores, flow controller, provenance, and bulletin board
- Essential components: processors, connections, controllers, and provenance tracking
Big Data Context and System Integration
- The position of NiFi within Big Data ecosystems (Hadoop, Kafka, cloud storage)
- Introduction to HDFS, MapReduce, and contemporary alternatives
- Application scenarios: stream ingestion, log shipping, and event pipelines
Installation, Configuration & Cluster Deployment
- Deploying NiFi on a single node and in cluster mode
- Cluster setup: defining node roles, integrating Zookeeper, and configuring load balancing
- Managing NiFi deployments using Ansible, Docker, or Helm
Architecting and Overseeing Dataflows
- Techniques for routing, filtering, splitting, and merging data streams
- Managing schemas, data enrichment, and transformation processes
Integration Use Cases
- Establishing connections to databases, messaging systems, and REST APIs
- Streaming data to analytics platforms: Kafka, Elasticsearch, or cloud storage
Monitoring, Recovery & Provenance Management
- Building strategies for autonomous recovery and graceful failure management
- Implementing backup, flow versioning, and change management protocols
Performance Tuning & Optimization
- Adjusting JVM, heap, thread pools, and clustering parameters
- Refining flow design to minimize bottlenecks
- Applying resource isolation, flow prioritization, and throughput regulation
Best Practices & Governance
- Security measures: TLS, authentication, access control, and data encryption
Troubleshooting & Incident Management
- Addressing common challenges: deadlocks, memory leaks, and processor errors
- Conducting log analysis, error diagnostics, and root cause investigations
- Executing recovery strategies and flow rollbacks
Practical Lab: Implementing a Realistic Data Pipeline
- Constructing a complete end-to-end flow: ingestion, transformation, and delivery
- Conducting performance tests and fine-tuning the pipeline
Recap and Future Directions
Requirements
- Proficiency with the Linux command line
- Familiarity with data streaming or ETL principles
Target Audience
- System administrators
- Data engineers
- Software developers
- DevOps specialists
Testimonials (7)
Hands on exercises. Class should have been 5 days, but the 3 days helped to clear up a lot of questions that I had from working with NiFi already
James - BHG Financial
Course - Apache NiFi for Administrators
I thought the trainer's pace was good. He left no student behind with his approach. He was very supportive with us NEWBIES that may not have had a System Administrator or Infrastructure role during our career or resurrected those skills from a prior period of our career.
Pamdrea Ivory - BHG Financial
Course - Apache NiFi for Administrators
I like the hands on section. It helped me to better retain information by completing the provided exercises. Also, the trainer's ability to engage with the entire class made me feel comfortable to ask questions on things I was not sure about.
Leila - BHG Financial
Course - Apache NiFi for Administrators
Use-cases, examples for building NiFi dataflows. We worked on troubleshooting common problems and gotchas.
Nelson - BHG Financial
Course - Apache NiFi for Administrators
I loved the structure. We dove into the basics of Nifi, concepts, use cases, etc. on day 1. On day 2, we got to put Day 1 knowledge into practice by building out flows to meet scenario requirements. Day 3 we got to see Nifi Registry and version control, mulit-tenancy, and go over Q&A.
Adam - BHG Financial
Course - Apache NiFi for Administrators
I like how he was able to elaborate about Nifi and how powerful it is. You can basically use it for any infrastructure and use many different computer languages. Also i was glad we were able to fix the Nifi cert renewal issue we were having with the Truststore.
Joachim Martin - BHG Financial
Course - Apache NiFi for Administrators
general knowledge and the possibilities that the training offered in terms on the tool.
