Apache NiFi uses logback library to handle its logging. There is a file logback.xml present in the conf directory of NiFi, which is employed to configure the logging in NiFi. The logs are generated in logs folder of NiFi and the log files are as described below.

nifi-app. log

This is the main log file of nifi, which logs all the activities of apache NiFi application ranging from NAR files loading to the run time errors or bulletins encountered by NiFi components. Below is the default appender in logback.xml file for nifi-app.log file.

<appender name="APP_FILE"

class="ch.qos.logback.core.rolling.RollingFileAppender">

   <file>${org.apache.nifi.bootstrap.config.log.dir}/nifi-app.log</file>

   <rollingPolicy

      class="ch.qos.logback.core.rolling.SizeAndTimeBasedRollingPolicy">

      <fileNamePattern>

         ${org.apache.nifi.bootstrap.config.log.dir}/

                     nifi-app_%d{yyyy-MM-dd_HH}.%i.log

      </fileNamePattern>

      <maxFileSize>100MB</maxFileSize>

      <maxHistory>30</maxHistory>

   </rollingPolicy>

   <immediateFlush>true</immediateFlush>

   <encoder class="ch.qos.logback.classic.encoder.PatternLayoutEncoder">

      <pattern>%date %level [%thread] %logger{40} %msg%n</pattern>

   </encoder>

</appender>

The appender name is APP_FILE, and the class is RollingFileAppender, which means logger is using rollback policy. By default, the max file size is 100 MB and can be changed to the required size. The maximum retention for APP_FILE is 30 log files and can be changed as per the user requirement.

nifi-user.log

This log contains the user events like web security, web api config, user authorization, etc. Below is the appender for nifi-user.log in logback.xml file.

<appender name="USER_FILE"

   class="ch.qos.logback.core.rolling.RollingFileAppender">

   <file>${org.apache.nifi.bootstrap.config.log.dir}/nifi-user.log</file>

   <rollingPolicy class="ch.qos.logback.core.rolling.TimeBasedRollingPolicy">

      <fileNamePattern>

         ${org.apache.nifi.bootstrap.config.log.dir}/

                     nifi-user_%d.log

      </fileNamePattern>

      <maxHistory>30</maxHistory>

   </rollingPolicy>

   <encoder class="ch.qos.logback.classic.encoder.PatternLayoutEncoder">

      <pattern>%date %level [%thread] %logger{40} %msg%n</pattern>

   </encoder>

</appender>

The appender name is USER_FILE. It follows the rollover policy. The maximum retention period for USER_FILE is 30 log files. Below is the default loggers for USER_FILE appender present in nifi-user.log.

<logger name="org.apache.nifi.web.security" level="INFO" additivity="false">

   <appender-ref ref="USER_FILE"/>

</logger>

<logger name="org.apache.nifi.web.api.config" level="INFO" additivity="false">

   <appender-ref ref="USER_FILE"/>

</logger>

<logger name="org.apache.nifi.authorization" level="INFO" additivity="false">

   <appender-ref ref="USER_FILE"/>

</logger>

<logger name="org.apache.nifi.cluster.authorization" level="INFO" additivity="false">

   <appender-ref ref="USER_FILE"/>

</logger>

<logger name="org.apache.nifi.web.filter.RequestLogger" level="INFO" additivity="false">

   <appender-ref ref="USER_FILE"/>

</logger>

nifi-bootstrap.log

This log contains the bootstrap logs, apache NiFi’s standard output (all system.out written in the code mainly for debugging), and standard error (all system.err written in the code). Below is the default appender for the nifi-bootstrap.log in logback.log.

<appender name="BOOTSTRAP_FILE" class="ch.qos.logback.core.rolling.RollingFileAppender">

   <file>${org.apache.nifi.bootstrap.config.log.dir}/nifi-bootstrap.log</file>

   <rollingPolicy class="ch.qos.logback.core.rolling.TimeBasedRollingPolicy">

      <fileNamePattern>

         ${org.apache.nifi.bootstrap.config.log.dir}/nifi-bootstrap_%d.log

      </fileNamePattern>

      <maxHistory>5</maxHistory>

   </rollingPolicy>

   <encoder class="ch.qos.logback.classic.encoder.PatternLayoutEncoder">

      <pattern>%date %level [%thread] %logger{40} %msg%n</pattern>

   </encoder>

</appender>

nifi-bootstrap.log file,s appender name is BOOTSTRAP_FILE, which also follows rollback policy. The maximum retention for BOOTSTRAP_FILE appender is 5 log files. Below is the default loggers for nifi-bootstrap.log file.

<logger name="org.apache.nifi.bootstrap" level="INFO" additivity="false">

   <appender-ref ref="BOOTSTRAP_FILE" />

</logger>

<logger name="org.apache.nifi.bootstrap.Command" level="INFO" additivity="false">

   <appender-ref ref="CONSOLE" />

   <appender-ref ref="BOOTSTRAP_FILE" />

</logger>

<logger name="org.apache.nifi.StdOut" level="INFO" additivity="false">

   <appender-ref ref="BOOTSTRAP_FILE" />

</logger>

<logger name="org.apache.nifi.StdErr" level="ERROR" additivity="false">

   <appender-ref ref="BOOTSTRAP_FILE" />

</logger>

So, this brings us to the end of Deep Dive into Apache NiFi User Interface blog. This Tecklearn ‘Concept of Logging in Apache NiFi’ 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:

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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.

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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

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