JENKINS

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About

Niles partners INC in association with Azure brings an automation server tool, Jenkins that offers hundreds of plugins to support building, deploying and automating projects.

Jenkins is an automation server with an unparalleled plugin ecosystem for supporting practically every tool as a part of the delivery pipelines. A self-contained Server-Jenkin can be used to effortlessly automate all sorts of tasks related to building, testing, and delivering software. High in its flexibility level, Jenkins allows for continuous integration and is installed on a server where the central build takes place.

The basic functionality of Jenkins is to perform a predefined list of steps, for instance, to compile Java source code and build a JAR from the resultant classes. The trigger for this execution could be time or event. Jenkin is not only limited to this but it also has more than 133,000 active sites, worldwide, and approximately 1,000,000 users.

Niles partners INC, one of the leading IT Solutions Provider is launching a product which will configure a tool called Jenkins to a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering) and graphical techniques which is embedded pre-configured tool with Ubuntu 18.04 and ready-to-launch Machine Image on Azure Cloud that contains Hadoop, Javadocs and version control server.
Why Jenkins Automation from Azure Cloud Marketplace?

Continuous Integration
Continuous Delivery
Easy installation
Easy configuration
Plugins
Extensible
Distributed
Plugins for Jenkins extend its use for projects written in languages other than Java. Plugins are available for integrating Jenkins with most of the version control systems as well as bug databases. Many build tools are maintained via their respective plugins and also change the way Jenkins looks or add new functionalities. Some useful plugins which are used in Jenkins,

Maven 2 project
Copy artifact
HTML publisher
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Green Ball
  1. Type virtual machines in the search.
  2. Under Services, select Virtual machines.
  3. In the Virtual machines page, select Add. The Create a virtual machine page opens.
  4. In the Basics tab, under Project details, make sure the correct subscription is selected and then choose to Create new resource group. Type myResourceGroup for the name.*.
  5. Under Instance details, type myVM for the Virtual machine name, choose East US for your Region, and choose Ubuntu 18.04 LTS for your Image. Leave the other defaults.
  6. Under Administrator account, select SSH public key, type your user name, then paste in your public key. Remove any leading or trailing white space in your public key.
  7. Under Inbound port rules > Public inbound ports, choose Allow selected ports and then select SSH (22) and HTTP (80) from the drop-down.
  8. Leave the remaining defaults and then select the Review + create button at the bottom of the page.
  9. On the Create a virtual machine page, you can see the details about the VM you are about to create. When you are ready, select Create.

It will take a few minutes for your VM to be deployed. When the deployment is finished, move on to the next section.

Connect to virtual machine

Create an SSH connection with the VM.

  1. Select the Connect button on the overview page for your VM.
  2. In the Connect to virtual machine page, keep the default options to connect by IP address over port 22. In Login using VM local account a connection command is shown. Select the button to copy the command. The following example shows what the SSH connection command looks like:

bashCopy

ssh azureuser@10.111.12.123

  1. Using the same bash shell you used to create your SSH key pair (you can reopen the Cloud Shell by selecting >_ again or going to https://shell.azure.com/bash), paste the SSH connection command into the shell to create an SSH session.

 

 

Usage/Deployment Instructions

Step 1: Access Jenkins from Azure Marketplace and click ON Get it now button.

Click on continue then on create;

Step 2: Now to create a virtual machine, enter or select appropriate values for zone, machine type, resource group and so on as per your choice.

Click on Create;

Use the browser to access the application at http://<instance ip address> replace <instance ip address> with the actual IP address of the running  instance.

Note: You will get the Instance IP Address as shown in the screenshot below:

Step 3: Get the InitialPassword to login. Use the following commands:

sudo su

cd /

vi InitialPassword

Note: copy the text and exit the editor.

https://www.cloud.miritech.com/images/CloudProducts/Jenkins/235618_jenkins_password.PNG

Step 4: Use following Linux command to start Jenkins

cd /home/ec2-user/

java -jar jenkins.war

https://www.cloud.miritech.com/images/CloudProducts/Jenkins/235641_jenkins_start.PNG

https://www.cloud.miritech.com/images/CloudProducts/Jenkins/235654_jenkins_starting.PNG

Step 5: open the browser and hit : http://<instanceip>:8080

Username: admin

Password: Initial password retrieved from step 3

https://www.cloud.miritech.com/images/CloudProducts/Jenkins/235716_jenkins_ipfire.PNG

Enjoy Jenkins

https://www.cloud.miritech.com/images/CloudProducts/Jenkins/235733_jenkins_dasshboard.PNG

 

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Hadoop, as a scalable system for parallel data processing, is useful for analyzing large data sets. Examples are search algorithms, market risk analysis, data mining on online retail data, and analytics on user behavior data.

Add the words “information security” (or “cybersecurity” if you like) before the term “data sets” in the definition above. Security and IT operations tools spit out an avalanche of data like logs, events, packets, flow data, asset data, configuration data, and assortment of other things on a daily basis. Security professionals need to be able to access and analyze this data in real-time in order to mitigate risk, detect incidents, and respond to breaches. These tasks have come to the point where they are “difficult to process using on-hand data management tools or traditional (security) data processing applications.”

The Hadoop JDBC driver can be used to pull data out of Hadoop and then use the DataDirect JDBC Driver to bulk load the data into Oracle, DB2, SQL Server, Sybase, and other relational databases.

Front-end use of AI technologies to enable Intelligent Assistants for customer care is certainly key, but there are many other applications. One that I think is particularly interesting is the application of AI to directly support — rather than replace — contact center agents. Technologies such as natural language understanding and speech recognition can be used live during a customer service interaction with a human agent to look up relevant information and make suggestions about how to respond. AI technologies also have an important role in analytics. They can be used to provide an overview of activities within a call center, in addition to providing valuable business insights from customer activity.

There are many machine learning algorithms in use today, but the most popular ones are:

  • Decision Trees
  • Naive Bayes Classification
  • Ordinary Least Squares Regression
  • Logistic Regression
  • Support vector machines
  • Ensemble Methods
  • Clustering Algorithms
  • Principal Component Analysis
  • Singular Value Decomposition
  • Independent Component Analysis

 

 

Highlights

  • High Flexibility Level
  • Globally Active Server
  • Additional plugins can be added any time

Application Installed