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Now available on Alibaba Cloud Network, Elastic Stack is a comprehensive end-to-end log analysis solution which helps in deep searching, analyzing, and visualizing the logs generated from different machines. Companies all over the world use these tools to perform critical business functions. These tools are most commonly used together for centralized logging in security and compliance, IT environments, business intelligence, and for web analytics as well.

ELK stack has been re-branded as Elastic Stack after the addition of Beats to the stack.

Elasticsearch is a search and analytics engine
Logstash is a data processing pipeline which ingests data from multiple sources concurrently, transforms it, and then sends it to a stash.
Kibana enables the users to visualize data using charts and graphs in Elasticsearch

Miri Infotech, one of the leading IT solutions provider is configuring ELK stack, a comprehensive end-to-end log analysis solution that which is embedded with Ubuntu along with ready-to-launch AMI on Alibaba Cloud Network that contains Elasticsearch, Kibana and Logstash.

Simply put, Logstash collects and analyzes logs, and then Elasticsearch indexes and stores the data. Kibana subsequently presents the information in visualizations which provide actionable insights.

These tools are spread across a compilation of different languages. Beats are written in “Go” for the convenient, efficient distribution of compiled binaries while Kibana uses Javascript for combined development of frontend and backend mechanisms.

Logstash

Logstash serves as the pillar for storage, querying, and analysis of the logs. With Logstash, it's really easy to collect those logs and store them in single centralized location. The only precondition is Java 8 runtime, and it takes only about two commands to get Logstash running. Since, it has a collection of ready-made inputs, codecs, filters, and outputs, users can grab hold of a dynamic feature-set easily.

Elasticsearch

Elasticsearch, a NoSQL database is based on the Lucene search engine. A single developer can use it to find the high-value information underneath all data haystacks, so users can put their team of data scientists to work efficiently. Elasticsearch comes along with these benefits:

Document orientation
Real-time analytics
Full-text search
Real-time data

Kibana

Kibana is a log-data dashboard which can be installed on Linux, Windows, and Mac. It runs on node.js, along with the installation packages that come incorporated with the required binaries. It provides a better grip on large data stores with point-and-click pie charts, trend lines, bar graphs, maps, and scatter plots. In the long run, user’s each business line can make practical use of data collection, as this helps them to customize their dashboards.

Usage / Deployment Instructions

Step 1: Open Putty for SSH.

Step 2: Open Putty and Type <instance public IP> at “Host Name”

Type "root" as user name and “miri@123” as Password.

Step 3: Use following Linux command to start ELK

$ echo "kibanaadmin:`openssl passwd -apr1`" | sudo tee -a /etc/nginx/htpasswd.users

Note: Enter the password as you like

$ nano /etc/nginx/sites-available/kibana

Note: Change the server_name with your Public ip of the running instance.

$ ln -s /etc/nginx/sites-available/kibana /etc/nginx/sites-enabled/kibana

$ systemctl restart nginx

Step 4: Hit the public ip of the running instance on the browser. Enter the username as “kibanaadmin” and password as you entered in step 3.

Enjoy your application.

(Optional Steps)

Step 1: Enter the following commands:

$ systemctl status elasticsearch

$ systemctl status logstash

$ systemctl status kibana

$ systemctl status nginx

All your queries are important to us. Please feel free to connect.

24X7 support provided for all the customers.

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Submit your Query: http://www.miritech.com/ContactUs.aspx

Contact Numbers:

(510) 298-5936
(510) 870-8668

Contact E-mail:

support@miritech.com

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You can subscribe to this product from Alibaba Cloud Marketplace and launch an instance from the product's image using the Alibaba ECS service.

Log on to the ECS console.
On the Instances page, click Create Instance to enter the Custom purchase page.
Follow these steps to finish Basic Configurations.
1. Select Billing Method. Select Pay-As-You-Go.
2. Select a region, such as China East 1. Select a zone, or allow one be allocated randomly, as by default.

Note After an instance is created, you cannot change its region and zone.

Select an instance type and specify the quantity of instances.

The available Instance type families are determined by the region selected. In this example, select All Generations > x86-Architecture > Entry-Level (Shared) > Compact Type xn4.

Select an image. The Product Image is selected.
Select a storage space. Only a system disk is used, and the 40 GiB Ultra Cloud Disk is selected, which is the default.

Click Next: Networking to finish the networking and security group configuration.
Select VPC as the network type. Select the default VPC and VSwitch.
Set the network billing method.

Select Assign public IP and Pay-By-Traffic.

Select a security group. You can use the default security group if you do not create one.
Add an Elastic Network Interface (ENI). Skip this step if the selected instance type does not support ENI.

Click Next: System Configurations.

Set configurations as needed. We recommend that you inherit the password from existing image.

Click Next: Grouping. You can set the options here as needed. In the case of multiple instances, we recommend that you add labels for ease of administration.
Click Next: Preview. Confirm the selected configuration. You can also click the edit icon to return and modify the configurations.
Read and confirm Terms of Service, then click Create Instance.

1How to keep my data safe in CRM?

To keep your data safe and sound just follow these basics: Let the specialist conduct security health check before CRM deployment to find vulnerabilities and prevent possible hacker attacks. Define access levels within your organization: set up the basic access to all the records for everyone in the system and impose restrictions on access to specific records, functionality, and workflows depending on the roles and human resource hierarchy. Keep track of user logins based on IP, API, or browser. Set up password defaults to make CRM users create a complex password and change it every 3-6 months. Regularly audit the system against the security regulations.
2What customizations can be done to CRM?

Depending on the type of CRM, there are several options available: Custom modules (sections) and fields. You can create a new section in CRM or remove default unnecessary ones and pick the fields to feature the module. Custom fields. You can create fields of any type (textbox, email, checkbox…) Custom UI/UX design. You can add or reorder the sections and fields on each layout, set up the navigation, add quicklinks. Custom workflow. You can map your processes across the CRM ecosystem, set alerts, data compliance checks, verifications, etc.
3What is big data security analytics?

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.”
4Is there an easy way to migrate data from Hadoop into a relational database?

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.
5What are the popular machine learning algorithms in use today?
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

ELK Stack

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1How to keep my data safe in CRM?

2What customizations can be done to CRM?

3What is big data security analytics?

4Is there an easy way to migrate data from Hadoop into a relational database?

5What are the popular machine learning algorithms in use today?

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