Apache NiFi is a powerful, easy to use and reliable system to process and distribute data between disparate systems. It is based on Niagara Files technology developed by NSA and then after 8 years donated to Apache Software foundation. It is distributed under Apache License Version 2.0, January 2004. The latest version for Apache NiFi is 1.7.1.

Apache NiFi is a real time data ingestion platform, which can transfer and manage info transfer between different sources and destination systems. It supports a wide variety of info formats like logs, geo location info, social feeds, etc. It also supports many protocols like SFTP, HDFS, and KAFKA, etc. This support to wide variety of info sources and protocols making this platform popular in many IT organizations.

Why Apache NiFi?

Apache NiFi helps to manage and automate the flow of data between the systems. It can easily manage the info transfer between source and destination systems. It can be described as data logistics. Apache NiFi helps to maneuver and track info similar to the parcel services as how data maneuver and track. It provides web-based User Interface (UI) to manage data in real-time.

As we have already discussed that Apache NiFi is an open-source, therefore it is freely available. It supports various data formats (such as logs, social feeds, and geographical location data, etc.) and protocols (such as KAFKA, SFTP, and HDFS, etc.). \Supports of a wide variety of protocols make this platform more popular in IT industry.

Below are some reasons given that why use Apache NiFi:

NiFi allows you to pull the data from various sources into NiFi and create flow files.
It allows you to use the existing libraries and Java ecosystem functionality.
It guarantees that the data must be delivered to the destination.
NiFi helps to fetch, aggregate, split, transform, listen, route, and drag & drop dataflow.
It visualizes the dataflow at an enterprise level.
NiFi can easily install on AWS (Amazon Web Service).
It allows us to start and stop components individually as well as group level.

History of NiFi

NiFi originally named Niagara File, which is now known as Apache NiFi. It was developed by National Security Agency (NSA) which is now handed over to the Apache Software Foundation.

7.1

The changes that made within the history of Apache NiFi is given below year-wise:-

Year	Description
2006	Niagara Files (NiFi) was developed by the NSA (United State National Security Agency) in 2006 for over eight years.
2014	In November 2014, NSA released it as open-source software and donated to Apache Software Foundation (ASF).
2015	In July 2015, it reached to ASF top-level project status and became an official part of Apache Project Suite.
Till now	Every 6-8 months since then, Apache releases a new update of Apache NiFi.

Features of Apache NiFi

Apache NiFi supports the directed graph of data routing, system mediation, and transformation. There are some reasons why NiFi came up is because of the data challenges we have. NiFi has a list of data challenges that are the features of NiFi. So, the various features of NiFi are described below:

7.2

Web-based UI –

NiFi offers web-based User Interface (UI) that can run over HTTPS, which makes user interaction secure with NiFi. It also manages the data in real-time. NiFi provides experience with design, control, monitoring, and feedback.

Guaranteed Delivery –

It is one of the most important and very powerful features of Apache NiFi that the delivery of data is guaranteed to be done. It can be achieved by the effective use of persistent write-ahead log and content repository. They both are designed together in such a way that allows for high transaction rate, copy-on-write, effective load spreading. NiFi is highly configurable.

Data Provenance or Data Lineage –

NiFi provides a data provenance module for tracking and monitoring data flows from beginning to end. NiFi automatically records, indexes, and makes available the provenance data as objects flow through the system. For supporting compliance, optimization, troubleshooting, and many other scenarios, this information becomes very useful.

Extensible –

This feature allows you to create your own processor. It enables fast development and effective testing. NiFi supports secure protocols such as SSH, SSL, HTTPS, encrypted content and also provides multi-tenant authorization as well as internal policy management. In NiFi, the number of different connectors is increasing.

The user can build their custom processor according to the requirement.
This feature of NiFi offers rapid development and effective testing.

Visual Command and control –

Dataflows can be quite complex. NiFi has an interactive user interface for the user, capable of visualizing and expressing the dataflows. It allows the visual formation of dataflows and helps to express them visually to reduce the complexity of dataflow. NiFi not only enables the visual formation of dataflows but is performed in real-time. If you make any change in data flow or modify it, that change is immediately reflected. You don’t need to stop the entire flow to make any specific modification.

Security –

Apache NiFi offers system to system, user to system, and multi-tenant authorization security feature. NiFi uses secure protocols such as SSL, SSH, and HTTPS for security reasons. It also uses other encryption to make data secure.

Apache NiFi- General Features

The general features of Apache NiFi are as follows −

Apache NiFi provides a web-based user interface, which provides seamless experience between design, control, feedback, and monitoring.
It is highly configurable. This helps users with guaranteed delivery, low latency, high throughput, dynamic prioritization, back pressure and modify flows on runtime.
It also provides data provenance module to track and monitor data from the start to the end of the flow.
Developers can create their own custom processors and reporting tasks according to their needs.
NiFi also provides support to secure protocols like SSL, HTTPS, SSH and other encryptions.
It also supports user and role management and also can be configured with LDAP for authorization.

Apache NiFi -Key Concepts

The key concepts of Apache NiFi are as follows −

Process Group − It is a group of NiFi flows, which helps a userto manage and keep flows in hierarchical manner.
Flow − It is created connecting different processors to transfer and modify data if required from one data source or sources to another destination data sources.
Processor − A processor is a java module responsible for either fetching data from sourcing system or storing it in destination system. Other processors are also used to add attributes or change content in flowfile.
Flowfile − It is the basic usage of NiFi, which represents the single object of the data picked from source system in NiFi. NiFiprocessormakes changes to flowfile while it maneuvers from the source processor to the destination. Different events like CREATE, CLONE, RECEIVE, etc. are performed on flowfile by different processors in a flow.
Event − Events represent the change in flowfile while traversing through a NiFi Flow. These events are tracked in data provenance.
Data provenance − It is a repository.It also has a UI, which enables users to check the information about a flowfile and helps in troubleshooting if any issues that arise during the processing of a flowfile.

Advantages of Apache NiFi

Apache NiFi supports SFTP protocol using which it enables the data fetching from remote machines.
Apache NiFi offers web-based User Interface (UI). So that NiFi can run on a web browser using localhost and port. On a web browser, it uses HTTPS protocol that makes user interaction with NiFi secure.
It also provides security policies at user level, process group level as well as other modules.
NiFi supports all the devices that run Java.
A user can create custom plugins to support different types of data systems, although NiFi already supports around 188 processors.
It provides real-time control that eases the maneuverment of data between source and destination.

Disadvantages of Apache NiFi

In case of primary node switching, Apache NiFi has a state persistence issue. Because of this issue, sometimes it does not enable the processor to fetch the data from the source.
While making any change by a user node gets disconnected from the NiFi cluster, and then flow.xml becomes invalid. A node cannot reconnect to the cluster until the administrator manually copies the xml file from the connected node.
All data are not created similarly.
It offers SSL and topic level authorization, which may not be sufficient.
To work with Apache NiFi, you must have good underlying system knowledge.

Architecture of Apache NiFi

Apache NiFi has a processor, flow controller, and web server that executes on the JVM machine. Additionally, it also includes three repositories, as shown within the figure, which are FlowFile repository, Content repository, and Provenance repository. NiFi runs within a JVM (Java Virtual Machine) on a host Operating System and every data or metadata store in repositories. The well-organized architecture of NiFi is as follows:

7.3

The key components of Apache NiFi architecture are discussed below in detail:

Web Server

The Web Server hosts the HTTP-based commands and control API of NiFi.

Flow Controller

The flow controller provides threads to execute the extensions. It also schedules the extensions when resources are received to execute. It works as a brain of operations.

Extension

Extensions are various type of plugin that allows Apache NiFi to interact with different systems. Extensions help the process to complete the task. NiFi has several types of extensions. These extensions are executed and operated withwithin the Java Virtual Machine (JVM).

FlowFile repository

The FlowFile repository contains the current state and attribute of each FlowFile that passes through the data flows of NiFi. NiFi keeps track of the state in FlowFile repository, which is currently active within the flow. The root directory is the default location of this repository, it can be changed. The default location of this repository can be changed by changing the property “nifi.flowfile.repository.directory“.

Content repository

The content repository stores all the data present in all the flowfiles. Implementation of the content repository is pluggable equivalent as the FlowFile repository. Its default approach is a simple mechanism to store block of data in file system.

The default directory of content repository is in root directory of NiFi and can be changed by changing the “org.apache.nifi.controller.repository.FileSystemRepository” property.

Provenance repository

The provenance repository is the repository that stores all the provenance event data. Event data is indexed and searchable within each location. It allows the user to check information about FlowFile, which means it tracks and stores all the events of all flowfiles that flows within the Apache NiFi. It also enables the troubleshooting if any issue occurs while processing FlowFile

Provenance repository has divided into two types:

Volatile provenance repository – All provenance data is lost after restart in this repository.
Persistence provenance repository – The default directory of persistence provenance is within the root directory of Apache NiFi. It can be changed using the “apache.nifi.provenance.PersistanceProvenanceRepository” property.

Apache NiFi can also work within a cluster.

7.4

A Zero-Master Clustering paradigm is employed with the beginning NiFi 1.0 first version release. In NiFi cluster, each node works on a different set of data, but it performs the equivalent task on the data. Apache Zookeeper chooses a single node as the cluster coordinator and handles the failure automatically. Each node of the cluster reports to the cluster coordinator about heartbeat and status. The cluster coordinator is responsible for connecting or disconnecting the nodes.

In addition, each cluster again has a primary node, which is also selected by Zookeeper. You’ll interact with NiFi cluster as a data flow manager or end developer using the user interface (UI) of any node. Any changes that are made by the user are replicated for all nodes of the cluster, which will allow several entry points.

So, this brings us to the end of Deep Dive into Apache NiFi User Interface blog. This Tecklearn ‘Introduction to Apache NiFi, its History, Features and Architecture’ helps you with commonly asked questions if you are looking out for a job in Apache NiFi and Big Data Domain.

If you wish to learn Apache NiFi and build a career in Apache NiFi or Big Data domain, then check out our interactive, Apace NiFi Training, that comes with 24*7 support to guide you throughout your learning period. Please find the link for course details:

https://www.tecklearn.com/course/apache-nifi-training/

Apache NiFi Training

About the Course

Tecklearn Apache NiFi Training makes you an expert in Cluster integration and the challenges associated, Usefulness of Automation, Apache NiFi configuration challenges and etc. Apache NiFi that helps you master various aspects of automating dataflow, managing flow of information between systems, streaming analytics, the concepts of data lake and constructs, various methods of data ingestion and real-world Apache NiFi projects .Transforming the databases is becoming a challenge for many organizations and thus they often look for those who have certification in Apache NiFi to help them in automating the flow of data between the systems.

Why Should you take Apache NiFi Training?

The Average Salary for Apache NiFi Developers is $96,578 per year. – paysa.com
Micron, Macquarie Telecom Group , Dovestech, Payoff, Flexilogix , Hashmap Inc. & many other MNC’s worldwide use Ansible across industries.
Apache NiFi is an open-source software for automating and managing the flow of data between systems. It is a powerful and reliable system to process and distribute data. It provides a web-based User Interface for creating, monitoring, & controlling data flows.

What you will Learn in this Course?

Overview of Apache NiFi and its capabilities

Understanding the Apache NiFi
Apache NiFi most interesting features and capabilities

High Level Overview of Key Apache NiFi Features

Key features categories: Flow management, Ease of use, Security, Extensible architecture and Flexible scaling model

Advantages of Apache NiFi over other traditional ETL tools

Features of NiFi which make it different form traditional ETL tool and gives NiFi an edge over them

Apache NiFi as a Data Ingestion Tool

Introduction to Apache NiFi for data ingestion
Apache NiFi Processor: Data ingestion tools available for transferring, importing, loading and processing of data

Data Lake Concepts and Constructs (Big Data & Hadoop Environment)

Concept of data lake and its attributes
Support for colocation of data in various formats and overcoming the problem of data silos

Apache NiFi capabilities in Big Data and Hadoop Environment

Introduction to NiFi processors which sync with data lake and Hadoop ecosystem
An overview of the various components of the Hadoop ecosystem and data lake

Installation Requirements and Cluster Integration

Apache NiFi installation requirements and cluster integration
Successfully running Apache NiFi and addition of processor to NiFi
Working with attributes and Process of scaling up and down
Hands On

Apache NiFi Core Concepts

Apache NiFi fundamental concepts
Overview of FlowFile, Flow Controller, FlowFile Processor, and their attributes
Functions in dataflow

Architecture of Apache NiFi

Architecture of Apache NiFi
Various components including FlowFile Repository, Content Repository, Provenance Repository and web-based user interface
Hands On

Performance Expectation and Characteristics of NiFi

How to utilize maximization of resources is particularly strong with respect to CPU and disk
Understand the best practices and configuration tips

Queuing and Buffering Data

Buffering of Data in Apache NiFi
Concept of queuing, recovery and latency
Working with controller services and directed graphs
Data transformation and routing
Processor connection, addition and configuration
Hands On

Database Connection with Apache NiFi

Apache NiFi Connection with database
Data Splitting, Transforming and Aggregation
Monitoring of NiFi and process of data egress
Reporting and Data lineage
Expression language and Administration of Apache NiFi
Hands On

Apache NiFi Configuration Best Practices

Apache NiFi configuration Best Practices
ZooKeeper access, properties, custom properties and encryption
Guidelines for developers
Security of Data in Hadoop and NiFi Kerberos interface
Hands On

Apache NiFi Project

Apache NiFi Installation
Configuration and Deployment of toolbar
Building a dataflow using NiFi
Creating, importing and exporting various templates to construct a dataflow
Deploying Real-time ingestion and Batch ingestion in NiFi
Hands On

Got a question for us? Please mention it in the comments section and we will get back to you.

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