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WHAT IS FULL STACK?

Full-stack is the development of an application of both front end and back end portions. Full-stack development means handling the entire steps starting from the origin of knowledge to the final end product. This whole procedure involves three layers. They are,

·       Presentation layer

·       Business logic layer

·       Database layer

 PRESENTATION LAYER

It is the front end of an application. It contains each component reachable by every end-user. Programming languages like HTML, JavaScript, Jquery, and a few other JavaScript libraries like AngularJS, ReactJS, EmberJS, Backbone, Foundation, etc., are used to build the presentation layer.

 BUSINESS LOGIC LAYER

It is the back end involving the entire development methods that are not visible to the end-users. It will be visible only if the developers allow. This layer is spinning around core logic. It is accountable for performing various tasks in an application. Python, Net, PHP, Java, Ruby are the programming languages that are used to build the business logic layer.

 DATABASE LAYER

It is also known as the subgroup of the logic layer. This layer deals with data creation, data modification, management, and data deletion using MySQL, PostgreSQL, SQL Server, and Oracle.

 ABOUT FULL STACK DEVELOPERS

A full-stack developer can perform active projects with ability and expertise, channeling all of their experiences to acquire the desired product. The full-stack developers are getting into the technical requirements, just to create a product with their extensive methods. They have wider viewpoint and an energetic attitude. They will be good assistance and saves a lot of technical costs and time with effective communication.

 ADVANTAGES OF FULL STACK

·       VERSATILITY:- A full-stack developer is good at both front end and back end development. Front end developers create codes using CSS, HTML, and JavaScript to control the presence and interactivity in a browser. Back end developers write prototype codes to connect with the CMS or Content management system with your website.

·       BIGGER PICTURE:- The major advantage of full-stack is that you can get the whole design structure easily and afford an input at any time. You will be able to maintain and optimize the existing systems.

·       EASY UPGRADE:- Because of this, full-stack developers are good at making desirable changes and make the projects user-friendly with the latest features. You will get responses from clients and interactive websites.

·       VAST EXPERIENCE:- You will get vast experience when you are working on a full-stack as you will be working on many projects. You would gain knowledge and experience in web development and app development.

·       SUITABLE FOR SMALL AND MEDIUM ENTERPRISES:- Full-stack is very much suitable for small and medium enterprises. Large, complex website requirements can be broken into numerous small segments.

 REASONS FOR CLAIMING FULL STACK DEVELOPMENT IN IT COMPANIES

Full-stack developers are proficient and brilliant in various programs like JavaScript, HTML, CSS, PHP, and so on. Many IT companies prefer full-stack developers for their specific qualities. Full-stack development gives complete finish on the look and the functionality. It helps to convert the complex designs into user-friendly graphics. It helps to create a unique code using multiple software tools resulting in both complex and simple codes. At any stage of development, transferring the design and implementation ownership is very easy in full stack. Every task of design and development can be divided into many, to work as a co-operative team. Because of these reasons, huge companies like Facebook are opting for Full Stack instead of Single Stack.

 If one completes learning Full Stack development, the developers will be proficient in the following aspects.

·       DATA MODELING:- The learning of Full Stack enables you to create a sensible normalized relational model, foreign keys completion, creation of views, indexes, lookup tables, etc.

·       USER INTERFACE:- You will be able to understand the process of creating a readable layout and implement the best visual design.

·       BUSINESS AND CLIENT NEED:- You will easily gain knowledge about the business and software used by the customers.

·       USER EXPERIENCE:- You will know how to create one-click codes and create a user-friendly user interface. You can write some useful error messages to alert the users.

·       NETWORK, SERVER, AND HOSTING ENVIRONMENT:- You will know how to use cloud storage, file system, network resources, application scale, etc.

 CAREER AND SALARY FOR FULL STACK DEVELOPERS

Today, most of the companies are hiring Full Stack developers instead of hiring for separate posts. Many huge enterprises as well as start-ups have begun hiring Full Stack developers.

There are various opportunities for them like Full-time, part-time, hourly basis jobs. Even some people are working as independent contractors and working consultants in this field.

Regarding salary, a Full Stack developer receives about $110,700 per annum. For a beginner, there will be about $55000 per annum. Thus a Full Stack developer would definitely get high pay. Companies provide a large pay because one individual does the job of about three individuals. And saves a lot of time, energy, and money. If you are ready to face the challenges and focus on work, Full Stack is the best career option.

 Apponix Offers Web designing Training in Bangalore

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VMware Training

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Apponix Technologies is the most innovative Training & Recruitment Company located in Bangalore, delivering classroom & online trainings across India, UK & USA

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Describe Azure architecture components, the infrastructure, tools, and portals.

Implement virtual networking in Microsoft Azure and configure cross-premise connectivity.

Plan and develop Azure Virtual Machines.

Configure, manage, and monitor Azure VM (Virtual Machines) to optimize availability and reliability.

Implement Azure App Service.

Plan and implement storage and backup, and recovery services.

Implement container-based workloads in Azure.

Deploy, configure, monitor, and diagnose cloud services.

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Basics of Mobile App Development

Process of designing a app for mobile is call mobile app development.  Some of the app by default need to install during manufacturing of mobile device also we have to give option to download via internet. During the app development we have to take care of UI and UX of Mobile App.

Different Types of mobile app development

·         Native apps Development

·         Mobile web apps Development

·         Hybrid web apps Development

Native apps

Those app appears in the home screen of mobile those application we can say native apps. They are default came from through application store. These native apps work without internet also sent notification to devices

Mobile web apps

Mobile web apps can use only via internet because these apps can’t access without internet.

Hybrid web apps

Hybrid web apps is like part of mobile web apps and partly native apps. Like native apps they  use mobile default features for communicating and like mobile web apps  they use html and other codes

Technologies used for mobile application development

·         We can design android and ios Applications using technologies j2ee, c, c++, react js and native js etc. and they use html5, CSS3, media query and fa icons for ui designing

·         Few companies used for mobile application developments are adobe flex, mobile jQuery, and Telerik

·         Adobe xd, Wireframe and Photoshop used for designing prototype of screen

Popularly used mobile apps

Flipkart, Google play Store, Google Meet,Amazon, YouTube, Facebook, What’s app, Google chrome are the top popularly used mobile apps

How to satisfy App users?

·         With Good UI

·         Secure Data

·         It should consume less battery

·         Synchronize features

·         Should consume less internet

·         Make it faster Loading speed

Growth for Mobile Application Development in 2020

Now a days android and ios is getting more popular and 70% users access information via mobile device because of this reason every one depends on android and ios app for their business or any kind of information’s. So learning android app in Bangalore at Apponix technologies will definitely helps to your bright future.

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Python for Data Science

Data science is about exploration, problem-solving, and extracting valuable information from data. It may be the easiest way to describe what Data science is by listing the below concrete components.

 Data Analysis and Exploration

Included here: SciPy; NumPy; Pandas; a helping hand from Python’s Standard Library.

Data visualization

Included here: Seaborn; Datashader; Matplotlib;

Classical machine learning

Included here: StatsModels, Scikit-Learn

Deep learning

Included here: TensorFlow, Keras, and a whole host of others.

Data storage and big data frameworks

Included here: Apache Hadoop; HDFS; Dask; Apache Spark; h5py/pytables.

 Why Python for Data Science?

Before understanding why python for data science, first we should understand python in the first place.

 Python is one of the valuable skills necessary for data science and it is the programming language of choice for data science.

 Python is the best choice for Data Science here are the top reasons:

·       Free and Open Source

·       Easy to learn; intuitive

·       Portability

·       Very few lines of code

·       Popularity and Demand

·       Better productivity

·       Excellent Community / Online presence

·       It is faster than similar tools like MATLAB and R

·       Great memory management abilities.

 Python has a great set of libraries geared towards Data Science, like NumPy, SciPy, Pandas, Matplotlib, sci-kit-learn, Seaborn and TensorFlow

Steps to Learn Python for Data Science

Step 1 – Strengthen the Python Basics

·       Python is an easy language; it is a good choice for introducing students to programming.

·       It has a very simple syntax.

·       Python programs are easy to understand read and write.

·       To get started with Python, first, we have to start with the basics. These include expressions, variables, types, and string operations.

Step2 – Understand Python Data Structures

·       After the basics, you need to understand various data structures like tuples and lists and dictionaries and sets. we will use these when writing code in Python.

·       This will helps in understanding how things work in Python. Try a few exercises on understanding Data structures

Step 3 – Master some Language Fundamentals

·       Learn about conditions like for- and while- loops, if..else and if..elif..else, recursion and functions.

·       You should also learn about objects and classes, and packages in Python.

Step 4 – Learn to Use Python to Work with Real Data

·       It is important to learn to use Python to work with data. This includes writing and reading files with Python.

·       This includes learning to use Pandas to read, work with, and save data using Pandas and also need to preprocess data.

Step 5 – Study to Gain Insights and Analyze Data

·       Learn to analyze data and gain insight from it using various Python libraries. This includes data frame from Pandas, ndarray from NumPy, multiple functions and methods from SciPy, and various machine learning methods from sci-kit-learn.

Step 6 – Grasp the Data Visualization Concept

·       Python has many options for choosing a library to perform visualization. Some of these are Seaborn, ggplot, Matplotlib, Plotly, and Bokeh.

·       We need to learn to visualize data if you want to become a Data Scientist. This reveals patterns in data that are otherwise hidden.

Step 7 – Learn to Use Python Libraries

·       Python has many libraries geared toward Machine Learning and Data Science. These include NumPy, Pandas, sci-kit-learn, SciPy, Matplotlib, Seaborn, TensorFlow, Keras, Theano,  and XGBoost. Learn about them and their usage.

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AWS Hit with a Record 2.3 TbpsDDoS Attack

AWS said it was hit by a DDoS attack of record 2.3 Tbps this year, with an unsuccessful attempt to knock cloud services offline, continuously for three days in February.

To put the size of the attempt into context, it is near twice the 1.3 Tbps attack that blasted GitHub in 2018, or the circa 1 TbpsMirai botnet DDoS that famously knocked Dyn offline in 2016.

Record DDoS Attack: AWS Reports CLDAP Incident 

DDoS attacks come in a wide variety of flavors. The attack made on AWS was a CLDAP reflection-based attack and was 44% bigger than anything the cloud provider has seen before, it said in a Q1 AWS Shield threat landscape report [pdf]. 

AWS did not cite any apparent motive but noted that attacks increase when a new vector is located by attackers. 

Reflection attacks ill-use legitimate protocols, by sending a request to a third-party server, using a spoofed IP address.

The response given was much larger and is returned to the spoofed IP address of the unwitting victim.

CLDAP reflection attacks ill-use the connectionless version of the Lightweight Directory Access Protocol (LDAP).

AWS weathered this attack as shown by its threat report, but it came after the public cloud giant saw services knocked offline in October 2019 by a DDoS attack on its DNS service.

What Else’s is Being Used to Attack the Cloud?

The report has also highlighted the four most important malicious “interaction types” used to try and hack services running on AWS in Quarter1.

41 million attempts were made to compromise services using these four techniques along during the quarter which makes 31% of all events.

Without naming any explicit CVEs, AWS points out:

·       “Docker unauthenticated RCE, wherein suspect tries to exploit a Docker engine API to build a container, without authorization.

·       “SSH intrusion attempts, where the suspect searches for ways to gain unauthorized access to the application using commonly used credentials or other exploits.

·       “Redis unauthenticated RCE, where the suspect tries to exploit the API of a Redis database to gain access to the application remotely, gain access to the contents of the database, or make it unavailable to end-users.

·       “Apache Hadoop YARN RCE, where the suspect tries to exploit the API of a Hadoop cluster’s resource management system and execute code, without authorization.

The report says: “The motivation of an attacker could vary. Individual interactions may come from an attacker with a specific goal which is related to the targeted application. The higher volume interactions are motivated by control of computing and network resources at scale for purposes like cryptocurrency mining, DDoS attacks, or data exfiltration.

It concludes by saying: “The frequency of interaction with an application depends on factors like its prevalence on the Internet, availability of unpatched RCE vulnerabilities, and the possibility that application owners have effectively restricted access to those applications”.

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Introduction to Digital marketing

Comparison of Traditional and Digital Marketing

Statistics of Digital Marketing

Benefits of Digital marketing

Latest Digital marketing trends

Digital Marketing strategy for websites

Challenges in Traditional Application

Career opportunities in digital marketing

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Recognise AWS terminology and concepts as they relate to the AW

Navigate the AWS Management Console Understand the security measures AWS provides

Differentiate AWS Storage options and create an Amazon Simple Storage Service (S3) bucket

Recognise AWS Compute and Networking options and use Amazon Elastic Compute Cloud (EC2) and Amazon Elastic Block Storage (EBS)

Identify Deployment and Management options

Load balancer and Auto-Scale with EC2

Use EC2 APIs and Configure Virtual Private Cloud

Debug and Troubleshoot AWS EC2 instance