Knowledge Factory

Secrets Manager enables us to supersede hardcoded credentials in our code, including passwords, with an API call to Secrets Manager to retrieve the secret programmatically . These avails ascertain the secret can't be compromised by someone examining our code, because the secret no longer subsists in the code. Withal, we can configure Secrets Manager to automatically rotate the secret for us according to a designated schedule. This enables us to supersede long-term secrets with short-term ones, significantly abbreviating the peril of compromise. Overview 1. The admin creates a new secret in AWS Secrets Manager 2. A Spring Boot application uses the secret name to access the secrets stored in AWS Secrets Manager Step 1: Create & Store secrets in AWS Secret Manager. Use the AWS Console to create and store a new secret in AWS Secrets Manager.  Link Step 2:  Add the below dependency to the pom.xml file. <dependency> <groupId> com.amazonaws </groupId> <art

The EFK Stack is an amassment of three open-source products — Elasticsearch, Fluentd, and Kibana. EFK stack provides centralized logging in order to identify quandaries with servers or applications. It sanctions us to search all the logs in a single place. It withal avails to find issues in multiple servers by connecting logs during a concrete time frame. The EFK stack provides a simple yet robust log analysis solution for our developers and DevOps engineers to gain valuable insights on failure diagnosis, application performance, and infrastructure monitoring. Modern log management and analysis solutions include the following capabilities: Aggregation  – the facility to accumulate and ship logs from multiple data sources. Processing  – the faculty to transform log messages into consequential data for more facile analysis. Storage  – the faculty to store data for elongated time periods to sanction for monitoring, trend analysis, and security use cases. Analysis  – the faculty to dissect

The ELK Stack is an amassment of three open-source products — Elasticsearch, Logstash, and Kibana. ELK stack provides centralized logging in order to identify quandaries with servers or applications. It sanctions us to search all the logs in a single place. It withal avails to find issues in multiple servers by connecting logs during a concrete time frame. The ELK stack provides a simple yet robust log analysis solution for our developers and DevOps engineers to gain valuable insights on failure diagnosis, application performance, and infrastructure monitoring. Modern log management and analysis solutions include the following capabilities: Aggregation – the facility to accumulate and ship logs from multiple data sources. Processing – the faculty to transform log messages into consequential data for more facile analysis. Storage – the faculty to store data for elongated time periods to sanction for monitoring, trend analysis, and security use cases. Analysis – the faculty to dissec

PlantUML is an open-source implement and syntax for engendering diagrams from plain-text definitions. We utilize simple text syntax to describe a type of diagram, as well as the elements which make up the diagram, and our away. Utilizing this plain text syntax and a rendering server/plugin to convert our text into diagrams, we can draw near on any architectural diagram that we require when designing a system. Here are just a few of the types of diagrams we can engender: Sequence diagram Usecase diagram Class diagram Object diagram Activity diagram  Component diagram Deployment diagram State diagram Timing diagram Steps to create sequence diagrams    Step 1:  Download and Install Visual Studio Code : https://code.visualstudio.com/download Step 2: Add PlantUML extension for Visual Studio Code  Install the extension Step 3: Create a text file with PlantUML commands, like this example called sequenceDiagram.txt: @startuml skinparam SequenceMessageAlignment center actor User User ->

A node.js web application contains the following three components: Import required modules : The "require" directive is utilized to load a Node.js module. Engender server : You have to establish a server that will listen to the client's request akin to Apache HTTP Server. Read request and return replication : The server engendered in an earlier step will read the HTTP request made by the client which can be a browser or a console and return the replication. Example 1: index.js var http = require( "http" ); http.createServer( function (request, response) { // Send the HTTP header // HTTP Status: 200 : OK // Content Type: application/json response.writeHead( 200 , { "Content-Type" : "application/json" }); var otherArray = [ "Java" , "Kotlin" ]; var otherObject = { item1: "Angular" , item2: "React Native" }; var json = JSON.stringify({ anObject: otherObject,

Let us create a new React app - click here   For more topics, click below link: React JS Setup, Installation, and First React Project :  part 1 ReactJS - JSX :  part 2 ReactJS - Components :  part 3 ReactJS - State and Props :  part 4 ReactJS - Component API : part 5 ReactJS - Events  :  part 6 Reactjs - Form :  part 7 ReactJS - Bootstrap - Buttons : part 8 ReactJS - Bootstrap - Table : part 9 ReactJS - Keys : part 10 Mini Projects React J+Node JS+Express+MongoDB CRUD:MERN Stack development  Kotlin + Spring Boot + React JS + MongoDB CRUD - Full stack development React JS+SpringBoot+RDBMS-CRUD:Full-stack development foundation React.js + Python + MongoDB CRUD application After engendering the React app, the best way to install Bootstrap is via the npm package. To install Bootstrap, navigate to the React app folder, and run the following command. $ npm install react-bootstrap bootstrap --save Example 1: background="dark" and variant="dark" import React from 'react