Niles Partners in association with Azure presents Nagios a powerful, user-friendly network monitoring software. Nagios Core is a computer software application which monitors systems, networks, and infrastructure. It also offers monitoring and alerting check for switches, servers, and applications.
Nagios provides comprehensive monitoring of Linux operating systems and distributions that includes service state, process state, file system usage, operating system metrics, and more. While using Nagios to monitor the Linux environment, users are basically using one of the most powerful Linux monitoring tools available. The scope of Nagios Core is mainly focused on duties to check execution, check schedules, check processing, alerting, and event handling.
Niles Partners, one of the leading IT Solutions Providers is launching a product that will configure and publish Nagios Core, a monitoring tool which is embedded pre-configured tool with LAMP and ready-to-launch Machine Image on AzureCloud containing Apache, MySQL, Linux, PHP (LAMP).
Nagios Core is designed with an extensible, focused architecture which is designed for scalability and flexibility. Nagios features numerous APIs that are used to extend its competences for performing additional tasks, is applied as a daemon written in C for performance reasons, and is planned to run natively on Linux/*nix systems.
Nagios Core features include:
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.
bashCopy
ssh azureuser@10.111.12.123
Usage/Deployment Instructions
Step 1: Access the Nagios-core in Azure Marketplace and click on Get it now button.
Click on continue and then on Create;
Step 2: In create a virtual machine window, enter or select appropriate values for zone, machine type, and so on.
Click on create button.
Step 3: The Azure Console confirms that Nagios was deployed
Step 4: Hit the public ip on the browser as follows:
Public ip/nagios
Step 5: Enter the details as follows:
Username- nagiosadmin
Password- Niles@123
Enjoy Nagios-core.
The Apache Hadoop software library allows for the distributed processing of large data sets across clusters of computers using a simple programming model. The software library is designed to scale from single servers to thousands of machines; each server using local computation and storage. Instead of relying on hardware to deliver high-availability, the library itself handles failures at the application layer. As a result, the impact of failures is minimized by delivering a highly-available service on top of a cluster of computers.
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: