INSTALL

GUIDES

CONTACT

Preface

EFAK (Eagle For Apache Kafka, previously known as Kafka Eagle). This topic provides a high-level look at EFAK, the EFAK process, and EFAK features. It’s a good place to start if you want to learn more about EFAK software. To jump right in, refer to Getting started.

EFAK is open source visualization and management software. It allows you to query, visualize, alert on, and explore your metrics no matter where they are stored. In plain English, it provides you with tools to turn your kafka cluster data into beautiful graphs and visualizations.

After installed EFAK like you do in Getting started, there are many possible things you might do next. It all depends on your needs and your use case.

KSQL

KSQL your kafka topic data through ad-hoc queries and dynamic drilldown. Able to quickly read message records in kafka topic.

Refer to KSQL for more information.

Alerts

If you are using EFAK alerting, then you can have alerts sent through a number of different alert notifiers, including DingDing, WeChat, Email, or Webhook.

Alert hooks allow you to create different notifiers with a bit of code if you prefer some other channels of communication. Visually define alert rules for your most important metrics.

Configure

If you are a EFAK administrator, then you will want to thoroughly familiarize yourself with EFAK configuration options.

Configuration covers both config files and environment variables. You can set up default ports, logging levels, zookeeper address, kafka security etc.

Overview

This guide will help you get started and acquainted with EFAK. To learn more about EFAK in general, refer to What is EFAK?

Install EFAK

This step varies according to your computer operating system. Refer to the instructions for your OS in the Installation section for instructions.

Log in for the first time

Next steps

Different user types will have different features. Some suggestions are listed below, or refer to What is EFAK? for a general overview of EFAK features.

All Users

All users might want to learn about:

Admins

Administrators might want to learn about:

Overview

This page lists the minimum hardware and software requirements to install EFAK.

To run EFAK, you must have a supported operating system, hardware that meets or exceeds minimum requirements, a supported database, and a supported browser.

Supported operating systems

The following operating systems are supported for EFAK installation:

Hardware recommendations

EFAK does not use a lot of resources and is very lightweight in use of memory and CPU.

Minimum recommended memory: 2048 MB
Minimum recommended CPU: 1

Some features might require more memory or CPUs. Features require more resources include:

Supported databases

EFAK requires a database to store its configuration data, such as users, data sources, and dashboards. The exact requirements depend on the size of the EFAK installation and features used.

EFAK supports the following databases:

By default, EFAK installs with and uses SQLite, which is an embedded database stored in the EFAK installation location.

Supported web browsers

EFAK is supported in the current version of the following browsers. Older versions of these browsers might not be supported, so you should always upgrade to the latest version when using EFAK:

Overview

This page explains how to install EFAK dependencies, download and install EFAK, get the service up and running on your Linux or macOS system, and the installation package details.

1. Download and install

You can download the EFAK source code on GitHub to compile and install by yourself, or by downloading a binary .tar.gz file.

2. Install JDK

If there is a JDK environment on the Linux server, this step can be ignored, and the installation of the next steps. If there is no JDK, first to the Oracle official website to download JDK.

JAVA_HOME Configure

Extract the binary installation package to the specified directory:

cd /usr/java
tar -zxvf jdk-xxxx.tar.gz
mv jdk-xxxx jdk1.8
vi /etc/profile
export JAVA_HOME=/usr/java/jdk1.8
export PATH=$PATH:$JAVA_HOME/bin
									

Then, we use the source /etc/profile to enable the configuration to take effect immediately.

Finally, we input java -version, according to the following information:

3. Extract EFAK

Here we extract to '/data/soft/new' directory and extract:

tar -zxvf efak-xxx-bin.tar.gz

rm -rf efak
mv efak-xxx efak

Then, configure EFAK profile

vi /etc/profile
export KE_HOME=/data/soft/new/efak
export PATH=$PATH:$KE_HOME/bin

Finally, we use the source /etc/profile to enable the configuration to take effect immediately.

4. Configure EFAK system file

Configure EFAK according to the actual situation of its own Kafka cluster, For example, zookeeper address, version type of Kafka cluster (zk for low version, kafka for high version), Kafka cluster with security authentication enabled etc.

cd ${KE_HOME}/conf

vi system-config.properties
# Multi zookeeper&kafka cluster list -- The client connection address of the Zookeeper cluster is set here
efak.zk.cluster.alias=cluster1,cluster2
cluster1.zk.list=tdn1:2181,tdn2:2181,tdn3:2181
cluster2.zk.list=xdn1:2181,xdn2:2181,xdn3:2181
# Add zookeeper acl
cluster1.zk.acl.enable=false
cluster1.zk.acl.schema=digest
cluster1.zk.acl.username=test
cluster1.zk.acl.password=test123
# Kafka broker nodes online list
cluster1.efak.broker.size=10
cluster2.efak.broker.size=20
# Zkcli limit -- Zookeeper cluster allows the number of clients to connect to
# If you enable distributed mode, you can set value to 4 or 8
kafka.zk.limit.size=16
# EFAK webui port -- WebConsole port access address
efak.webui.port=8048
######################################
# EFAK enable distributed
######################################
efak.distributed.enable=false
# master worknode set status to master, other node set status to slave
efak.cluster.mode.status=slave
# deploy efak server address
efak.worknode.master.host=localhost
efak.worknode.port=8085
# Kafka offset storage -- Offset stored in a Kafka cluster, if stored in the zookeeper, you can not use this option
cluster1.efak.offset.storage=kafka
cluster2.efak.offset.storage=kafka
# Whether the Kafka performance monitoring diagram is enabled
efak.metrics.charts=false
# EFAK keeps data for 30 days by default
efak.metrics.retain=30
# If offset is out of range occurs, enable this property -- Only suitable for kafka sql
efak.sql.fix.error=false
efak.sql.topic.records.max=5000
# Delete kafka topic token -- Set to delete the topic token, so that administrators can have the right to delete
efak.topic.token=keadmin
# Kafka sasl authenticate
cluster1.efak.sasl.enable=false
cluster1.efak.sasl.protocol=SASL_PLAINTEXT
cluster1.efak.sasl.mechanism=SCRAM-SHA-256
cluster1.efak.sasl.jaas.config=org.apache.kafka.common.security.scram.ScramLoginModule required username="admin" password="admin-secret";
# If not set, the value can be empty
cluster1.efak.sasl.client.id=
# Add kafka cluster cgroups
cluster1.efak.sasl.cgroup.enable=false
cluster1.efak.sasl.cgroup.topics=kafka_ads01,kafka_ads02
cluster2.efak.sasl.enable=true
cluster2.efak.sasl.protocol=SASL_PLAINTEXT
cluster2.efak.sasl.mechanism=PLAIN
cluster2.efak.sasl.jaas.config=org.apache.kafka.common.security.plain.PlainLoginModule required username="admin" password="admin-secret";
cluster2.efak.sasl.client.id=
cluster2.efak.sasl.cgroup.enable=false
cluster2.efak.sasl.cgroup.topics=kafka_ads03,kafka_ads04
# Default use sqlite to store data
efak.driver=org.sqlite.JDBC
# It is important to note that the '/hadoop/kafka-eagle/db' path must be exist.
efak.url=jdbc:sqlite:/hadoop/kafka-eagle/db/ke.db
efak.username=root
efak.password=smartloli
# (Optional) set mysql address
#efak.driver=com.mysql.jdbc.Driver
#efak.url=jdbc:mysql://127.0.0.1:3306/ke?useUnicode=true&characterEncoding=UTF-8&zeroDateTimeBehavior=convertToNull
#efak.username=root
#efak.password=smartloli

5. Start the EFAK server (Standalone)

In the $KE_HOME/bin directory, there is a ke.sh script file. Execute the start command as follows:

cd ${KE_HOME}/bin
chmod +x ke.sh
ke.sh start

After that, when the EFAK server is restarted or stopped, execute the following command:

ke.sh restart
ke.sh stop

As shown in the following figure:

6. Start the EFAK server (Distributed)

In the $KE_HOME/bin directory, there is a ke.sh script file. Execute the start command as follows:

cd ${KE_HOME}/bin
# sync efak package to other worknode node
# if $KE_HOME is /data/soft/new/efak
for i in `cat $KE_HOME/conf/works`;do scp -r $KE_HOME $i:/data/soft/new;done
# sync efak server .bash_profile environment
for i in `cat $KE_HOME/conf/works`;do scp -r ~/.bash_profile $i:~/;done
chmod +x ke.sh
ke.sh cluster start

After that, when the EFAK server is restarted or stopped, execute the following command:

ke.sh cluster restart
ke.sh cluster stop

As shown in the following figure:

Overview

This page explains how to install EFAK dependencies, download and install EFAK, get the service up and running on your Windows system, and the installation package details.

1. Install JDK

If there is a JDK environment on the Linux server, this step can be ignored, and the installation of the next steps. If there is no JDK, first to the Oracle official website to download JDK.

JAVA_HOME Configure

Run the downloaded *.exe file installation package directly, then configure environment variables:

2. Check JDK

Finally, we input java -version, according to the following information:

3. KE_HOME Configure

Configure environment variables,As shown in the following figure:

4. Start the EFAK server

Go to the %KE_HOME%\bin directory and click the 'ke.bat' file.

Overview

EFAK has a number of configuration options that you can specify in a .properties configuration file or specified using environment variables.

Config file locations

Do not rename system-config.properties! EFAK defaults are stored in this file.

Base Common

Database Property

MySQL

SQLite

Overview

If your Kafka cluster has set security authentication, you need to set the corresponding security authentication information in EFAK.

Kerberos

EFAK system-config.properties file setting:

######################################
# kafka  sasl authenticate
######################################
cluster1.efak.sasl.enable=true
cluster1.efak.sasl.protocol=SASL_PLAINTEXT
cluster1.efak.sasl.mechanism=GSSAPI
cluster1.efak.sasl.jaas.config=com.sun.security.auth.module.Krb5LoginModule required useKeyTab=true storeKey=true keyTab="/etc/security/keytabs/kafka_client.keytab" principal="kafka-eagle.org@EXAMPLE.COM";
# make sure there is a local ticket cache "klist -l" to view
# cluster1.efak.sasl.jaas.config=com.sun.security.auth.module.Krb5LoginModule required useTicketCache=true renewTicket=true serviceName="kafka-eagle.org";
# if your kafka cluster doesn't require it, you don't need to set it up
# cluster1.efak.sasl.client.id=

PLAIN

EFAK system-config.properties file setting:

######################################
# kafka  sasl authenticate
######################################
cluster1.efak.sasl.enable=true
cluster1.efak.sasl.protocol=SASL_PLAINTEXT
cluster1.efak.sasl.mechanism=PLAIN
cluster1.efak.sasl.jaas.config=org.apache.kafka.common.security.plain.PlainLoginModule required username="kafka" password="kafka-eagle";
# if your kafka cluster doesn't require it, you don't need to set it up
# cluster1.efak.sasl.client.id=

SCRAM-SHA-256

EFAK system-config.properties file setting:

######################################
# kafka  sasl authenticate
######################################
cluster1.efak.sasl.enable=true
cluster1.efak.sasl.protocol=SASL_PLAINTEXT
cluster1.efak.sasl.mechanism=SCRAM-SHA-256
cluster1.efak.sasl.jaas.config=org.apache.kafka.common.security.scram.ScramLoginModule required username="kafka" password="kafka-eagle";
# if your kafka cluster doesn't require it, you don't need to set it up
# cluster1.efak.sasl.client.id=

OAUTHBEARER

If you use this authentication, you need to make sure that your Kafka cluster version is after 2.x, EFAK system-config.properties file setting:

######################################
# kafka  sasl authenticate
######################################
cluster1.efak.sasl.enable=true
cluster1.efak.sasl.protocol=SASL_PLAINTEXT
cluster1.efak.sasl.mechanism=OAUTHBEARER
cluster1.efak.sasl.jaas.config=org.apache.kafka.common.security.oauthbearer.OAuthBearerLoginModule required unsecuredLoginStringClaim_sub="kafka-eagle";
# if your kafka cluster doesn't require it, you don't need to set it up
# cluster1.efak.sasl.client.id=

SSL

If you use this authentication(ssl), you need to make sure that your Kafka cluster version is after 2.x, EFAK system-config.properties file setting:

######################################
# kafka ssl authenticate
######################################
cluster3.efak.ssl.enable=true
cluster3.efak.ssl.protocol=SSL
# kafka server.properties "ssl.truststore.location" value
cluster3.efak.ssl.truststore.location=/data/kafka/ssl/certificates/kafka.truststore
# kafka server.properties "ssl.truststore.password" value
cluster3.efak.ssl.truststore.password=ke123456
# kafka server.properties "ssl.keystore.location" value
cluster3.efak.ssl.keystore.location=/data/kafka/ssl/certificates/kafka.keystore
# kafka server.properties "ssl.keystore.password" value
cluster3.efak.ssl.keystore.password=ke123456
# kafka server.properties "ssl.endpoint.identification.algorithm" value
cluster3.efak.ssl.endpoint.identification.algorithm=https
# kafka server.properties "ssl.key.password" value
cluster3.efak.ssl.key.password=ke123456

CGroups

When using permission authentication (such as SASL Or SSL), the user you are using only supports managing a limited number of kafka topics. You can enable the following properties:

# SASL
cluster1.efak.sasl.cgroup.enable=true
cluster1.efak.sasl.cgroup.topics=topic1,topic2,topic3
# SSL
cluster2.efak.ssl.cgroup.enable=true
cluster2.efak.ssl.cgroup.topics=topic4,topic5,topic6

Overview

A dashboard is a set of one or more panels organized and arranged into one or more rows. EFAK ships with a variety of Panels. EFAK makes it easy to get the right queries, and customize the display properties so that you can view kafka topic data the perfect dashboard for your need.

Dashboard UI

• Kafka brokers
• All topics
• Zookeepers
• All consumer applications
• Broker memory usage
• Topic top10 logsize
• Topic top10 capacity

Overview

Topic columns under the current contains the creation and list, through the creation of a module can create a custom partition and the number of backup Topic. As shown in the following figure:

Create Topic

List Topic

The module follows all the Topic in the Kafka cluster, including the number of partitions, create time, and modify the Topic, as shown in the following figure:

Topic Detail

Each Topic is corresponding to a hyperlink, you can view the details of the Topic, such as: partition index number, Leader, Replicas and Isr, as shown in the figure below:

Topic Config

Select kafka topic, then edit the topic config, such as clean topic data, modify topic config, describe topic config etc:

Topic Hub

It is used to migrate the topic data or balance the expanded broker.

Overview

The module shows the Topic information of consumer records, which contains the following contents:

As shown in the following figure:

Each consumer group name of a is a hyperlink, show details of consumption, as shown below:

Click on the Topic name that is being consumed, showing the consumption and production rate diagram of the Topic, as shown below:

Overview

This module displays Kafka cluster information and Zookeeper cluster information, including the following:

As shown in the following figure:

Overview

New alarm module, to pay attention to their own Topic alarm settings. No consumer information when Topic, more than the threshold, the alarm. At present, the alarm way through the message to the alarm, set as shown in the following figure:

Support IM

In addition to supporting email or webhook alerts, EFAK also supports im alerts, such as DingDing and WeChat.

Mail Or WebHook

First of all, it is necessary to configure alarm channels, select different alarm modes, and divide different alarm groups.

It should be noted that EFAK alarm mail uri:

http://127.0.0.1:10086/email

Email or Webhook restful api server uri:

http://127.0.0.1:10086/email?address="xxx@gmail.com"&msg="alarm msg"

Api server uri java code:

@RestController
public class MailController {
    @RequestMapping(value="/email", method = RequestMethod.POST)
    public String sendPostMail(HttpServletRequest request) {
        // Send Alarm Message Interface
        System.out.println("[PUT] address: " + request.getParameter("address") + ",msg: " + request.getParameter("msg"));
        return "OK";
    }
}

Mail By ServerAddress

If you have the username and password of the mail server, you can use the following method to set the information about your mail server into the following JsonObject

{"host":"smtp.126.com","port":"465","sa":"ke","username":"ke@126.com","password":"*********","enable_ssl":true}

DingDing

WeChat

Overview

$KE_HOME/bin/ke.sh The following commands are included in the startup script:

Overview

Zookeeper client command operation, currently only supports ls, delete, get command operation, the command does not support, as shown below:

Overview

This module displays Multi Kafka clusters information and Zookeeper clusters information, including the following:

As shown in the following figure:

Overview

Use the SQL statement to the news data visualization in topic, for SQL queries, and table names field need to use double quotes to mark, example SQL is as follows:

select * from ke_test_topic where `partition` in (0,1,2) limit 100

As shown in the following figure:

DataSets

Parse JSONObject Or JSONArrays

Kafka topic datasets like this:

[{"id":123,"name":"smartloli"},{"id":456,"name":"smartloli2"},{"id":789,"name":"smartloli3"}]

Then you can use sql query topic like this:

select JSONS(msg,'name') from topic_name where `partition` in (0) limit 10

When Kafka topic datasets like this:

{"id":123,"name":"smartloli001"}

Then you can use sql query topic like this:

select JSON(msg,'name') from topic_name where `partition` in (0) limit 10

Using and syntax in SQL

select JSON(msg,'name') from topic_name where `partition` in (0) and JSON(msg,'name') = 'smartloli001' limit 10

Filter Query [where ... and]

Kafka topic datasets like this:

kafka-eagle-01
kafka-eagle-02
kafka-eagle-02
kafka-eagle-03
kafka-eagle-03
...
kafka-eagle-03
kafka-eagle-04

Then you can use sql query topic like this:

select * from topic_name where `partition` in (0) and msg = 'kafka-eagle-03' limit 10

Using like syntax in SQL

select * from topic_name where `partition` in (0) and msg like 'kafka-eagle%' limit 10

Or

select * from topic_name where `partition` in (0) and msg like '%kafka-eagle%' limit 10

Overview

Controls permissions for actions such as deletion, editing, etc., and the browsing operation is not controlled.

Resource

Role

Assign an accessible directory to each role.

User

Add users, fill in the corresponding user information, click Submit, and then fill in the mailbox will receive the corresponding login information (login name and password).

Overview

Through JMX to obtain data, monitor the Kafka client, the production side, the number of messages, the number of requests, processing time and other data to visualize performance.

If your data is empty, check that the port of JMX is started . If you do not start, you can edit the script before you start

vi kafka-server-start.sh
...
if [ "x$KAFKA_HEAP_OPTS" = "x" ]; then
    export KAFKA_HEAP_OPTS="-server -Xms2G -Xmx2G -XX:PermSize=128m -XX:+UseG1GC -XX:MaxGCPauseMillis=200 -XX:ParallelGCThreads=8 -XX:ConcGCThreads=5 -XX:InitiatingHeapOccupancyPercent=70"
    export JMX_PORT="9999"
fi

Zookeeper

When your zookeeper version is after 3.5, you need to open zkcli permission to repair the script content

vi zkServer.sh
...
// zookeeper enable client commands
ZOOMAIN="-Dzookeeper.4lw.commands.whitelist=* ${ZOOMAIN}"

Trend

Observe Kafka index data according to different dimensions.

Brokers Metrics

EFAK monitoring summarizes the node data of the whole cluster. Through the monitoring chart, you can observe the running state of the cluster.

Overview

We enter http://host:port/tv through the browser, access to the EFAK BScreen page. The page contains the following:

As shown in the following figure:

Overview

In the development work, consumer in the Kafka cluster message, data change is our concern, when the premise of business is not complicated, we can use the Kafka command to provide tools with Zookeeper client tools, you can easily finish our work. With the complexity of the business, increase Group and Topic, then we use Kafka to provide command tools, already felt powerless, then the Kafka monitoring system at the moment is particularly important, we need to observe the details of consumer applications.

There are so many excellent open source monitor systems in the industry. In the early stage, we were useing open source system, but with the rapid development of business, as well as some specific requirements of Internet Co, the current open source monitor systems does not quite meet the criteria of performance, extendibility and efficiency.

Therefore, in the past time, starting from the needs of the Internet Co, starting from the DEVS you use experience and feedback, combined with some of the industry's large open source Kafka monitoring system, starting with some thoughts on monitoring, we were designed and developed of the kafka monitoring system. So we called EFAK.

Background

There are four reasons to design EFAK system:

Overview

Monitor data is essential in a monitor system for the following analysis, graph, and alarm. How does EFAK deal with the problem of data collection?

For Kafka, that we can collect the following data

That's quite a lot, which come from different interfaces, such as JMX, Kafka API, internal topic etc.

Let's focus on the three representative categories above.

Kafka Machine Loading Information

The collection of this category is universal. We can collect data through Kafka broker JMX, Kafka API etc.

It should be noted here that if data acquisition fails, it is necessary to insist on whether the network is limited, such as firewall policy.

We can test whether the corresponding port is available on the server where EFAK is deployed. The command is as follows:

# Test Kafka Broker Server
telnet kafka01 9092
# Test Kafka Broker JMX
telnet kafka01 9999
# Test Zookeeper Server
telnet zk01 2181

For the introduction of JMX, please visit here.

Service Monitor Data

Service indicators such as QPS, TPS and RT reflect the performance of Kafka Broker services. These indicators are collected by different timers. After has finished collection, the collected data (from JMX or API) is stored in the database (such as MySQL or SQLite). Finally, the data is rendered in the dashboard to form a friendly graph web page.

You can check if static resources are limited:

Step1

Open the browser review element, switch to the network module, and check Disable cache.

Step2

Switch to the console module, refresh the browser, and observe whether the console module is abnormal. If there is an exception, you can use the search engine to solve it according to the exception prompt.

Applications Monitor

Indicators such as consumer groups, consumers, producers, and topics reflect the health of client programs. We can analyze whether our application is normal by observing these indicators on the EFAK web page.

We don't need to make any settings for these indicator data. After the client program starts, EFAK will automatically identify, collect and store the data.

If your Kafka version is less than 0.10.x (0.8.x, or 0.9.x etc.), set as follows:

# Set Kafka Offsets Storage
cluster1.efak.offset.storage=zk

If your Kafka version is greater than 0.10.x (1.x, or 2.x etc.), set as follows:

# Set Kafka Offsets Storage
cluster1.efak.offset.storage=kafka

Overview

The monitor system is the most important link of the operation process even the lifecycle of a product. It sends alarms before accidents and provides detailed data for the investigation of issues. There are many choices of open source kafka monitor system as a muture product in operation industry.

So, we can look up EFAK feature and architecture.

Feature

EFAK consists of dashboard, collect, storage, alarm, authority authentication and other core feature modules. Each feature module is responsible for the following:

Overview

EFAK has very low requirements for server hardware. Only 1 core of CPU and 2GB of memory can run, and it supports the whole platform (Linux, macOS, Windows). At the same time, EFAK can manage multiple Kafka clusters (without installing a EFAK service for each Kafka cluster).

Advanced

KSQL

Users can easily use KSQL, can quickly query the data in topic.

Consumers

Through the Consumers module. Users can view the runtime of consumer programs intuitively, and analyze and judge the health of applications with more graphs.

Bash

Manage and view EFAK process service status through ke.sh script command.

JDK Encoding

When you deploy EFAK on the server where it is installed, the encode of the installed JDK is not UTF-8. When you use the mock feature of EFAK, you will get an exception when sending data in Unicode encoding format.

Then, You can run the following command:

ke.sh jdk

GC

You can also view the process of EFAK by executing gc command:

ke.sh gc

[Release V3.0.1] 2022-08-30

[Release] Add: Release EFAK V3.0.1 version,The following changes:

[Release V2.1.0] 2022-02-04

[Release] Add: Release EFAK V2.1.0 version,The following changes:

[Release V2.0.9] 2021-12-24

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[Release V2.0.8] 2021-10-13

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[Release V2.0.7] 2021-09-13

[Release] Add: Release EFAK V2.0.7 version,The following changes:

[Release V2.0.6] 2021-07-25

[Release] Add: Release Kafka Eagle V2.0.6 version,The following changes:

[Release V2.0.5] 2021-05-08

[Release] Add: Release Kafka Eagle V2.0.5 version,The following changes:

[Release V2.0.4] 2021-02-18

[Release] Add: Release Kafka Eagle V2.0.4 version,The following changes:

[Release V2.0.3] 2020-11-19

[Release] Add: Release Kafka Eagle V2.0.3 version,The following changes:

[Release V2.0.2] 2020-09-27

[Release] Add: Release Kafka Eagle V2.0.2 version,The following changes:

[Release V2.0.1] 2020-08-10

[Release] Add: Release Kafka Eagle V2.0.1 version,The following changes:

[Release V2.0.0] 2020-07-03

[Release] Add: Release Kafka Eagle V2.0.0 version,The following changes:

[Release V1.4.8] 2020-06-02

[Release] Add: Release Kafka Eagle V1.4.8 version,The following changes:

[Release V1.4.7] 2020-05-13

[Release] Add: Release Kafka Eagle V1.4.7 version,The following changes:

[Release V1.4.6] 2020-04-12

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[Release V1.4.5] 2020-03-21

[Release] Add: Release Kafka Eagle V1.4.5 version,The following changes:

[Release V1.4.4] 2020-02-21

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[Release V1.4.3] 2020-01-24

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[Release V1.4.2] 2019-12-19

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[Release V1.4.1] 2019-11-26

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[Release V1.4.0] 2019-10-30

[Release] Add: Release Kafka Eagle V1.4.0 version,The following changes:

[Release V1.3.9] 2019-09-08

[Release] Add: Release Kafka Eagle V1.3.9 version,The following changes:

[Release V1.3.8] 2019-08-27

[Release] Add: Release Kafka Eagle V1.3.8 version,The following changes:

[Release V1.3.7] 2019-08-13

[Release] Add: Release Kafka Eagle V1.3.7 version,The following changes:

[Release V1.3.6] 2019-07-28

[Release] Add: Release Kafka Eagle V1.3.6 version,The following changes:

[Release V1.3.5] 2019-07-25

[Release] Add: Release Kafka Eagle V1.3.5 version,The following changes:

[Release V1.3.4] 2019-07-13

[Release] Add: Release Kafka Eagle V1.3.4 version,The following changes:

[Release V1.3.3] 2019-06-09

[Release] Add: Release Kafka Eagle V1.3.3 version,The following changes:

[Release V1.3.2] 2019-05-20

[Release] Add: Release Kafka Eagle V1.3.2 version,The following changes:

[Release V1.3.1] 2019-03-26

[Release] Add: Release Kafka Eagle V1.3.1 version,The following changes:

[Release V1.3.0] 2019-02-26

[Release] Add: Release Kafka Eagle V1.3.0 version,The following changes:

[Release V1.2.9] 2019-01-20

[Release] Add: Release Kafka Eagle V1.2.9 version,The following changes:

[Release V1.2.8] 2019-01-01

[Release] Add: Release Kafka Eagle V1.2.8 version,The following changes:

[Release V1.2.7] 2018-12-25

[Release] Add: Release Kafka Eagle V1.2.7 version,The following changes:

[Release V1.2.6] 2018-11-12

[Release] Add: Release Kafka Eagle V1.2.6 version,The following changes:

[Release V1.2.5] 2018-10-28

[Release] Add: Release Kafka Eagle V1.2.5 version,The following changes:

[Release V1.2.4] 2018-08-20

[Release] Add: Release Kafka Eagle V1.2.4 version,The following changes:

[Release V1.2.3] 2018-06-04

[Release] Add: Release Kafka Eagle V1.2.3 version,The following changes:

[Release V1.2.2] 2018-04-23

[Release] Add: Release Kafka Eagle V1.2.2 version,The following changes:

[Release V1.2.1] 2018-01-25

[Release] Add: Release Kafka Eagle V1.2.1 version,The following changes:

[Release V1.2.0] 2017-11-28

[Release] Add: Release Kafka Eagle V1.2.0 version,The following changes:

[Release V1.1.9] 2017-10-24

[Release] Add: Release Kafka Eagle V1.1.9 version,The following changes:

[Release V1.1.8] 2017-08-22

[Release] Add: Release Kafka Eagle V1.1.8 version,The following changes:

[Release V1.1.7] 2017-08-04

[Release] Add: Release Kafka Eagle V1.1.7 version,The following changes:

[Release V1.1.6] 2017-07-24

[Release] Add: Release Kafka Eagle V1.1.6 version,The following changes:

[Release V1.1.5] 2017-06-23

[Release] Add: Release Kafka Eagle V1.1.5 version,The following changes:

[Release V1.1.4] 2017-06-05

[Release] Add: Release Kafka Eagle V1.1.4 version,The following changes:

[Release V1.1.3] 2017-05-08

[Release] Add: Release Kafka Eagle V1.1.3 version,The following changes:

[Release V1.1.2] 2017-03-29

[Release] Add: Release Kafka Eagle V1.1.2 version,The following changes:

[Release V1.1.1] 2017-03-01

[Release] Add: Release Kafka Eagle V1.1.1 version,The following changes:

[Release V1.1.0] 2017-02-22

[Release] Add: Release Kafka Eagle V1.1.0 version,The following changes:

[Release V1.0.9] 2017-01-09

[Release] Add: Release Kafka Eagle V1.0.9 version,The following changes:

[Release V1.0.8] 2016-11-03

[Release] Add: Release Kafka Eagle V1.0.8 version,The following changes:

[Release V1.0.7] 2016-10-31

[Release] Add: Release Kafka Eagle V1.0.7 version,The following changes:

[Release V1.0.6] 2016-09-14

[Release] Add: Release Kafka Eagle V1.0.6 version,The following changes:

[Release V1.0.5] 2016-09-12

[Release] Add: Release Kafka Eagle V1.0.5 version,The following changes:

[Release V1.0.4.1] 2016-09-08

[Release] Add: Release Kafka Eagle V1.0.4.1 version,The following changes:

[Release V1.0.4] 2016-09-01

[Release] Add: Release Kafka Eagle V1.0.4 version,The following changes:

[Release V1.0.3] 2016-08-26

[Release] Add: Release Kafka Eagle V1.0.3 version,The following changes:

[Release V1.0.2] 2016-08-24

[Release] Add: Release Kafka Eagle V1.0.2 version,The following changes:

[Release V1.0.1] 2016-08-23

[Release] Add: Release Kafka Eagle V1.0.1 version,The following changes:

[Release V1.0.0] 2016-08-17

[Release] Add: Release Kafka Eagle V1.0.0 version,The following changes: