Forem: Jay Baer

Key steps to achieve successful RPA Implementation

Jay Baer — Thu, 23 Sep 2021 07:53:05 +0000

Automation has invaded almost all industries and domains. And, RPA, known as robotic process automation, has begun to deeply penetrate the industries. Therefore, to compete and stay in the competition, companies, and organizations are forced to take up RPA implementation. There are various RPA automation examples in the industry that have been extremely successful.

Statistics say that RPA implementation and automation will reach a saturation point by 2023. Therefore it becomes apparent that by the time we reach 2023, almost all the areas of the industry will have RPA implementation.

There are various benefits of RPA implementation that the organization can take advantage of. RPA implementation project plan replaces repetitive human tasks with automated procedures. In turn, humans can focus on other high-priority tasks. These tasks include the decision-making process through the study of performance patterns of the organization.

Benefits of RPA Implementation:

1. Enhanced productivity and Efficiency:

RPA automation is applicable to the processes that are repetitive. Moreover, RPA eliminates human intervention to a great extent. For instance, a bot can run the calculations. A human can take an hour or more to finish these tasks. But RPA bots can do it in the matter of minutes which saves time. In addition to this, the RPA bots can this way increase the number of tasks accomplished in a certain amount of time. This paves way for increased productivity and efficiency.

2. Increased Accuracy:

Humans are prone to making mistakes and create erroneous results. But with the introduction of RPA implementation, the errors are removed completely. Although RPA requires governance, it effectively eliminates errors and mistakes. If the processes are well optimized and the bots are trained and programmed, there is no room for errors.

3. Secured Solution:

The RPA bots are popular to function at a granular level. The bots are assigned a single task. One bot performs only one task. Hence, there is no interconnection within two or more bots. This prevents the dripping of information within two bots. The information is maintained with security. The organization documents which bots can access what kind of information areas. Therefore, RPA implementation is extremely secure.

4. Enhanced Scalability:

The RPA bots are popular for their flexibility to take up numerous, unrelated tasks. Moreover, they can take up tasks as they come up. The bots can adjust to the time-bound and task-bound requirements. Hence, it is easy to allocate and reallocate the tasks to the bots. The markets these days display a lot of unpredictability. But these bots can meet all the unpredictability that enhances the business performance in many ways.

You May Also Like: Role of RPA in HR Operations

5. In-depth Analytics for Performance Measurement:

The bots perform various tasks and can increase the efficiency of the organization. But there are various ways to measure the performance in the long run. You can deploy other bots to gather information at periodic intervals. After the RPA implementation, it becomes easier to define the volume of the work, cycle frequencies, and errors. This gives you an insight into the areas that need improvement. With the passage of time, you can improve the functions of the bots to effectively utilize them.

But what drives the success of RPA implementation? RPA implementation does not necessarily bring the required efficiency and productivity sometimes. Well, in that case, there are certain factors that decide how to successfully implement RPA.

This blog discusses the steps in which the rpa automation can be implemented. Let us take a look at those steps:

1. Planning Strategically:

Any new implementation in the organization requires a well-thought plan. Without planning, we are bound to fail. For RPA implementation, it is important to go through the objectives you have to fulfill. These methods and techniques are supposed to be comprehensible.

The easy comprehension of the RPA implementation is easier for the employees to understand. It requires a good plan for introducing change management. In this step, you also define the roles of the employees around RPA implementation. A detailed plan can help you address issues before the RPA is actually implemented.

2. Preparing the Employees:

As the planning is accomplished, the organization is required to prepare the employees. Sometimes employees may resist the introduction of automation. But educating and training them well may help you achieve the exact results you expect. When the employees know the roles around RPA, you can expect a certain outcome. Moreover, if employees know the amount of ROI, RPA brings, they will be able to maximize the use of RPA.

3. Form rational ROI Expectations:

Determining ROI and time taken for its accomplishment is the most difficult thing to do for RPA adoption. The processes may expand and bring complications within them. This would need accurate administration, understanding of exceptions, and seasonality. When these factors are studied well the improvements can be targeted. Likewise, the cost of RPA implementation can also be effectively reduced.

4. Determine the Process that requires Automation:

This is the successful steps of the RPA implementation 2021 roadmap. In this step, an organization determines which process can be automated. Depending on the process that requires automation you can take immense advantage of RPA. There could be certain questions you can consider before RPA implementation:

Can you take up processes that are stable and predictable?
Are there any processes that have fewer exceptions and do not require human intervention?
Can we determine the processes that are highly frequent and provide faster ROI?

Determining such processes can help you implement RPA successfully.

5. Collaborate with the IT and Business teams:

Once the processes that need RPA automation are determined, organizations have to form the relevant teams. These teams consist of people from the company’s IT and business departments. The team members have to work cohesively to successfully implement and use RPA implementation.

The lack of cooperation between these teams can set up a road to failure of RPA. Business leaders often assume that the RPA setup does not require an IT team extensively. Hence, they are quick to forget the IT teams.

On other hand, the IT teams assume RPA implementation as something that requires a sound understanding of technology. Hence, they undermine the requirement of business teams. RPA can function successfully only if these teams collaborate and work in cohesion.

Also Read: How can RPA be Helpful in Recognizing and Fighting Off Fraud?

6. Implement RPA Successfully:

As an RPA roadmap is developed in previous steps, you can set the organization up towards successful implementation. An RPA roadmap includes documentation of RPA opportunities and project planning. This enables an enhanced understanding of the technology behind automation. Moreover, it can help you how RPA can be implemented in various other domains of the business. These automation processes can create highly efficient results.

Conclusion:

RPA implementation can be challenging and complicated if it is done without proper planning and allocation of tools and resources. In the absence of these, the implementation of RPA can seem daunting and intricated.

Therefore, having an RPA automation expert at your disposal can take off the burden from the organization. This also prevents failures and problematic anomalies. Moreover, you can study the RPA implementation examples to derive an insight before you implement them.

Top 10 Python Libraries for Machine Learning

Jay Baer — Thu, 09 Sep 2021 07:12:28 +0000

With the increase in the markets for smart products, auto-pilot cars and other smart products, the ML industry is on a rise. Machine Learning is also one of the most prominent tools of cost-cutting in almost every sector of industry nowadays.

ML libraries are available in many programming languages, but python being the most user-friendly and easy to manage language, and having a large developer community, is best suited for machine learning purposes and that's why many ML libraries are being written in Python.

Also, the python works seamlessly with C and C++ and so, the already written libraries in C/C++ can be easily extended to Python. In this tutorial, we will be discussing the most useful and best machine-learning libraries in the Python programming language.

1. TensorFlow :

Website: https://www.tensorflow.org/
GitHub Repository: https://github.com/tensorflow/tensorflow
Developed By: Google Brain Team
Primary Purpose: Deep Neural Networks

TensorFlow is a library developed by the Google Brain team for the primary purpose of Deep Learning and Neural Networks. It allows easy distribution of work onto multiple CPU cores or GPU cores, and can even distribute the work to multiple GPUs.

TensorFlow uses Tensors for this purpose. Tensors can be defined as a container that can store N-dimensional data along with its linear operations. Although it is production-ready and does support reinforcement learning along with Neural networks, it is not commercially supported which means any bug or defect can be resolved only by community help.

2. Numpy:

Website: https://numpy.org/
Github Repository: https://github.com/numpy/numpy
Developed By: Community Project (originally authored by Travis Oliphant)
Primary purpose: General Purpose Array Processing

Created on the top of an older library Numeric, the Numpy is used for handling multi-dimensional data and intricate mathematical functions. Numpy is a fast computational library that can handle tasks and functions ranging from basic algebra to even Fourier transforms, random simulations, and shape manipulations. This library is written in C language, which gives it an edge over standard python built-in sequencing.

Numpy arrays are better than pandas series in the term of indexing and Numpy works better if the number of records is less than 50k. The NumPy arrays are loaded into a single CPU which can cause slowness in processing over the new alternatives like Tensorflow, Dask, or JAX, but still, the learning of Numpy is very easy and it is one of the most popular libraries to enter into the Machine Learning world.

3. Natural Language Toolkit (NLTK):

Website: https://www.nltk.org/
Github Repository:https://github.com/nltk/nltk
Developed By: Team NLTK
Primary Purpose: Natural Language Processing

NLTK is the widely used library for Text Classification and Natural Language Processing. It performs word Stemming, Lemmatizing, Tokenization, and searching a keyword in documents.

The library can be further used for sentiment analysis, understanding movie reviews, food reviews, text-classifier, checking and censoring the vulgarised words from comments, text mining, and many other human language-related operations.

The wider scope of its uses includes AI-powered chatbots which need text processing to train their models to identify and also create sentences important for machine and human interaction in the upcoming future.

4.Pandas

Website: https://pandas.pydata.org/
Github Repository: https://github.com/pandas-dev/pandas
Developed By: Community Developed (Originally Authored by Wes McKinney)
Primary Purpose: Data Analysis and Manipulation

The Library is written in Python Web Framwork and is used for data manipulation for numerical data and time series. It uses data frames and series to define three-dimensional and two-dimensional data respectively. It also provides options for indexing large data for quick search in large datasets.

It is well known for the capabilities of data reshaping, pivoting on user-defined axis, handling missing data, merging and joining datasets, and the options for data filtrations. Pandas is very useful and very fast with large datasets. Its speed exceeds that of Numpy when the records are more than 50k.

It is the best library when it comes to data cleaning because it provides interactiveness like excel and speed like Numpy. It is also one of the few ML libraries that can deal with DateTime without any help from any external libraries and also with a bare minimum code with python code quality. As we all know the most significant part of data analysis and ML is the data cleaning, processing, and analyzing where Pandas helps very effectively.

5. Scikit-Learn:

Website: https://scikit-learn.org/
Github Repository: https://github.com/scikit-learn/scikit-learn
Developed By: SkLearn.org
Primary Purpose: Predictive Data Analysis and Data Modeling

Scikit-learn is mostly focused on various data modeling concepts like regression, classification, clustering, model selections, etc. The library is written on the top of Numpy, Scipy, and matplotlib. It is an open-source and commercially usable library that is also very easy to understand.

It has easy integrability which other ML libraries like Numpy and Pandas for analysis and Plotly for plotting the data in a graphical format for visualization purposes. This library helps both in supervised as well as unsupervised learnings.

6. Keras:

Website: https://keras.io/
Github Repository: https://github.com/keras-team/keras
Developed By: various Developers, initially by Francois Chollet
Primary purpose: Focused on Neural Networks

Keras provides a Python interface of Tensorflow Library especially focused on AI neural networks. The earlier versions also included many other backends like Theano, Microsoft cognitive platform, and PlaidMl.

Keras contains standard blocks of commonly used neural networks, and also the tools to make image and text processing faster and smoother. Apart from standard blocks of neural networks, it also provides re-occurring neural networks.

7. PyTorch:

Website: https://pytorch.org/
Github Repository: https://github.com/pytorch/pytorch
Developed By: Facebook AI Research lab (FAIR)
Primary purpose: Deep learning, Natural language Processing, and Computer Vision

Pytorch is a Facebook-developed ML library that is based on the Torch Library (an open-source ML library written in Lua Programming language). The project is written in Python Web Development, C++, and CUDA languages. Along with Python, PyTorch has extensions in both C and C++ languages.

It is a competitor to Tensorflow as both of these libraries use tensors but it is easier to learn and has better integrability with Python. Although it supports NLP, but the main focus of the library is only on developing and training deep learning models only.

8. MlPack:

Github Repository: https://github.com/mlpack/mlpack
Developed By: Community, supported by Georgia Institute of technology
Primary purpose: Multiple ML Models and Algorithms

MlPack is mostly C++-based ML library that has bindings to Python other languages including R programming, Julia, and GO. It is designed to support almost all famous ML algorithms and models like GMMs, K-means, least angle regression, Linear regression, etc.

The main emphasis while developing this library was on making it a fast, scalable, and easy-to-understand as well as an easy-to-use library so that even a coder new to programming can understand and use it without any problem. It comes under a BSD license making it approachable as both open source and also proprietary software as per the need.

9. OpenCV:

Website: https://opencv.org/
Github Repository: https://github.com/opencv/opencv
Developed By: initially by Intel Corporation
Primary purpose: Only focuses on Computer Vision
OpenCV

OpenCV is an open-source platform dedicated to computer vision and image processing. This library has more than 2500 algorithms dedicated to computer vision and ML. It can track human movements, detect moving objects, extract 3d models, stitch images together to create a high-resolution image, exploring the AR possibilities.

It is used in various CCTV monitoring activities by many governments, especially in China and Isreal. Also, the major camera companies in the world use OpenCv for making their technology smart and user-friendly.

10. Matplotlib:

Website: https://matplotlib.org/
Github Repository: https://github.com/matplotlib/matplotlib
Developed By: Micheal Droettboom, Community
Primary purpose: Data Visualization

Matplotlib is a library used in Python for graphical representation to understand the data before moving it to data-processing and training it for Machine learning purposes. It uses python GUI toolkits to produce graphs and plots using object-oriented APIs.

The Matplotlib also provides a MATLAB-like interface so that a user can do similar tasks as MATLAB. This library is free and open-source and has many extension interfaces that extend matplotlib API to various other libraries.

Conclusion:

In this blog, you learned about the best Python libraries for machine learning. Every library has its own positives and negatives. These aspects should be taken into account before selecting a library for the purpose of machine learning and the model’s accuracy should also be checked after training and testing the models so as to select the best model in the best library to do your task.

Provisioning RDS Instances using Terraform

Jay Baer — Tue, 31 Aug 2021 12:29:24 +0000

In this blog post, We will learn to provision RDS instances using Terraform - Infrastructure as Code

Table of Contents:

● What is Terraform?
● What is RDS?
● Installation of Terraform
● Installation of AWS CLI
● Configuring AWS CLI
● Create a Working directory for Terraform
● Understanding Terraform files
● Launching RDS instance from Snapshot
● Launching RDS instances

PreRequisites:

● Installation of Terraform
● Installation of AWS CLI
● IAM user Access key and Secret Key

What is Terraform?

● A tool to create resources, modify and delete them as required.
● Supporting clouds such as AWS, Azure, GCP, Digital Ocean, IBM cloud etc.

What is RDS?

RDS stands for Relational Database Services

Amazon RDS provides an interface to easily create and manage relational databases in the cloud.

It provides salient features such as replication, security, scalability, and high availability with auto-failover.

Amazon RDS provides DB engine types such as Amazon Aurora, PostgreSQL, MySQL, MariaDB, Oracle Database, and SQL Server.

With the help of DMS, you can migrate existing DB to RDS easily.

Installing Terraform:

Install terraform using one of the below-mentioned methods.

Using binary package (.zip)
Compiling from source

( https://learn.hashicorp.com/tutorials/terraform/install-cli )

From the above link, Download the respective terraform package and install it.

Run the below command for checking the installed version.

terraform -v

Installing AWS CLI:

A command-line program to create and manage AWS resources programmatically

Install AWS CLI using below provided command

sudo apt-get install AWS CLI

Run the below command to check the version of AWS cli

AWS Version

Configuring AWS CLI

A profile can be configured so that it can be used by the terraforming for authentication.

With programmatic access, users will be provided an AWS access key and Secret key.

Entire the key and region when asked while executing the below command.

AWS configure

Understanding Terraform Files
variables.tf:

A file that holds the access key, secret key, and the region of AWS.

What not to do with Access Keys?
Not to hard code the keys in a file

What should we do?
Use AWS CLI profile to pass the secret keys

Then we will add AWS keys to the /home/zenesys/.aws/credentials file.

Providers.tf:

A plugin will be installed using terraform to communicate with the respective providers.

Providers such as AWS, Azure and GCP, IBM, Oracle Cloud, Digital Ocean.

Main.tf
A template / file which contains a template to provision the resources.

A custom name can be used instead of main.tf

Launch an RDS Instance using a Snapshot

When there is a requirement to launch an RDS instance from the existing RDS instance,

In this case, We will create a snapshot of the existing RDS instance and use it to launch a New RDS Instance with the same data.

Let's assume you already have a snapshot in place for an RDS instance, Now we can go ahead and create a DB instance using it.

Here is the terraform script for it,

We are checking for the latest snapshot of the “dbinstance” DB instance.

data "aws_db_snapshot" "db_snapshot" {
most_recent = true
db_instance_identifier = "dbinstance"
}

Pass the snapshot_identifier in the template to launch the RDS instance from the snapshot.
Attached is the template below,

resource "aws_db_instance" "db_sample" {
instance_class = "db.t2.medium"
identifier = "sampledb"
username = "sample"
password = "Sample@#5832"
publicly_accessible = false
db_subnet_group_name = "${aws_db_subnet_group.db-subnet.name}"
snapshot_identifier = "${data.aws_db_snapshot.db_snapshot.id}"
vpc_security_group_ids = ["sg-00g52b79"]skip_final_snapshot = true
}

We can configure the template as required

Execute terraform apply the command to launch an RDS instance from the existing snapshot.

Launch RDS Instance from Scratch

If you’re launching an RDS Instance for the first time,

We need to create the following resources such as Subnet groups, Security Groups , Parameter groups,

If, you want to launch it in a desired VPC and Subnet group,

If not, Use the below terraform script to launch your first RDS instance using terraform.

resource "aws_db_instance" "default" {
allocated_storage = 50
identifier = "sampleinstance"
storage_type = "gp2"
engine = "mysql"
engine_version = "5.7"
instance_class = "db.m4.medium"
name = "sample"
username = "dbadmin"
password = "DBAdmin@5#41$32"
parameter_group_name = "default.mysql5.7"
}

aws_db_instance – RDS instance as a resource

identifier – A unique name for the DB Instance

engine_version – DB version to use

If you want to launch RDs instances in a custom VPC and subnet groups, You can create the same using Terraform.

The VPC where you want to create RDS Instance

resource "aws_vpc" "main" {
cidr_block = "10.0.0.0/16"
}

A subnet group (collection of subnets) is a minimum requirement before creating an RDS Instance.

Let's create subnets from different availability zones.

private subnet in AZ – A

resource "aws_subnet" "priv-subnet1" {
vpc_id = "${aws_vpc.main.id}"
cidr_block = "10.0.2.0/24"
availability_zone = "AZ-a of the Region"
}

private subnet in AZ – B

resource "aws_subnet" "priv-subnet2" {
vpc_id = "${aws_vpc.main.id}"
cidr_block = "10.0.3.0/24"
availability_zone = "AZ-b of the region"
}

Now We can create a subnet group using the above subnets A and B:

resource "aws_db_subnet_group" "db-subnet" {
name = "DB subnet group"
subnet_ids = ["${aws_subnet.priv-subnet1.id}", "${aws_subnet.priv-subnet2.id}"]}

And We must pass a DB subnet group parameter in the main script to use the subnet group which we have created.

db_subnet_group_name = "${aws_db_subnet_group.db-subnet.name}"

Once we have the terraform scripts ready, we can execute the following commands to launch the RDS instance.

terraform plan

terraform apply

We can create an RDS instance from Scratch using Terraform in a custom VPC.

10 Most Important Robotic Process Automation (RPA) Tools in Demand

Jay Baer — Thu, 26 Aug 2021 11:10:07 +0000

Robotic Process Automation is a practical answer to repetitive and time-consuming tasks. These are the task types that don’t require human intervention or strategic planning to conduct the task.

To accomplish these tasks, robotic process automation tools are available in the market. However, there are a lot of reasons as to why you should use RPA tools and which ones to use. The market is overwhelming when it comes to selecting the RPA tools.

This blog highlights the top ten tools in Robotic Process Automation and RPA tools comparison. Out of all the tools available in the market, we have highlighted some of the best RPA tools available for use.

Let us take a look:

1. Electroneek:

Electroneek is designed to handle challenging tasks that require automation on personal computers as well as servers. The interface of Electroneek is so user-friendly, that even the business owners who are non-tech savvy people can use Electroneek easily.

It has the following features that you can work with:

Drag and drop interface to add and manage workflows
Process recorder
A local bot scheduling system
Javascript and Python support
Powerful systems to handle errors in the system
It also comes with web-browser based automation

2. LaserFiche:

LaserFiche is another robotic process automation tool that is built to function for mid-sized and large-sized companies. This tool helps you eliminate manual operations and functions through powerful workflows, analytics, and automation. When it comes to handling the processes, LaserFiche does it all.

It has the following features:

LaserFiche comes with a process recorder that lets you build bots for the execution of repetitive operations and processes. It also interacts with third-party applications and systems.
When you have to handle edge cases, you can use the Bot Designer that comes with LaserFiche to edit the bots.
This tool lets you track the performance of the bots in a real-time environment.

3. UiPath:

UiPath provides end-to-end automation which is available for use on cloud platforms, hybrid cloud systems, or on-premises. The bots will execute the process automation. It comes with a simple canvas through which, anyone in the organization can build and use bots to handle processes.

UiPath comes with the following features:

UiPath comes with a pre-defined activity set that offers a range of process automation as well as application integration.
With a drag and drop interface, an employee of the organization can create a visual workflow.
With the recording and playback feature, you can record the actions and build an automated process sequence.
RPA UiPath eliminates the cost and improves the efficiency of the operations.

4. Blue Prism:

Blue Prism can be used to handle large-sized organizations. This tool offers a virtual workforce by deploying software robots. It provides automated business operations with agility and cost-efficiency. It is powered by Java programming language and comes with a graphical user interface. Such an interface allows anyone to build rpa bots using drag and drop functionality.

Features of Blue Prism:

You can execute any number of processes and practically there is no limit to the number of processes you introduce.
Blue Prism offers accuracy in all the operations and functions it carries out.
Blue Prism comes with load balance, encryption of the data, and end-to-end audit solutions.
With central management, blue prism rpa offers scalability. This paves a way for automated processes which can be tracked centrally.

5. Automation Anywhere:

Automation Anywhere can be targeted towards mid and large-sized organizations. The speed of executing the transactions is increased significantly with the implementation of Automation Anywhere. This removes human errors, saves time consumption issues, and costs.

Features of Automation Anywhere:

With Microsoft Automation Anywhere, you can build a bot through a drag and drop method. The rule-based automation is easy to create and can be pushed to the control room and can be deployed later.

It comes with a control room where the management of robots can be carried out. You can stop, pause or schedule the robot functions and operations.
Automation Anywhere can use third-party systems for optical character recognition.
Automation Anywhere can automate the Citrix environment through the use of UI objects.

6. Helpsystems Automate RPA:

Helpsystems Automate RPA can be used for handling RPA processes in mid-sized and large-sized companies and enterprises. It offers process automation that integrates the front-end and back-end automation workflows across the organization.

Features of Helpsystems Automate RPA:

It comes with a simple deployment process and has an intuitive interface that speeds up the streamlining process.
With Helpsystems Automate RPA, you can scale your basic automated processes to advanced automation of the processes easily.
It also comes with disaster management and high availability.
With prebuilt actions, common tasks can be easily accommodated and executed without a lot of human intervention.

7. Workfusion Intelligent Automation Cloud:

WorkFusion offers intelligent robotic process automation solutions for small-scale, mid-scale, and large-scale enterprises. It comes with packaged solutions, to automate processes designed for specific domains.

Features of Workfusion Intelligent Automation Cloud:

With intelligence-driven bots, they can process the documents with unstructured data and information. It digitizes, classifies, and organizes the information to derive pattern and make the decision.
Use Case Navigator lets you find the high-potential processes that you can automate.
Workfusion comes with pre-packaged APIs which can integrate with a lot of enterprise applications and pre-packaged connectors.

8. WinAutomation by SoftMotive:

For mid and large-sized enterprises and organizations, WinAutomation by Softmotive.

Features of WinAutomation by SoftMotive:

The ProcessRobot supports Java, HTML5, Microsoft .NET Silverlight, WPF, Citrix, and the majority of the web browsers.
You can build the robots through automation using a visual editor, customized automation.
You can also record workflow to build the bots to assign repetitive tasks to them.
The bots can be deployed according to a schedule as and when the requirement arises.

9. Pega Platform:

Pega Platform is suitable for use in mid-sized and large-sized enterprises and companies. Repetitive tasks like data processing, employee onboarding, along account reconciliation.

Features of Pega Platform:

Removes the complexity of business processes and operations through innovative bot deployment.
It offers enhanced scalability and adopts changes as per the changing needs and requirements of the business.
Comes with the ability to processes incoming emails through natural language processing.

10. Nintex RPA:

Nintex RPA can be targeted for use in mid-sized and large-sized companies. It automates workflows to build a collaborative work environment with teams and shareholders.

Features of Nintex RPA:

Easy graphics user interface and visual editor allow the non-technical employees to automate the work environment quickly.
Nintex RPA provides automation for around 300 actions that provide enhanced automation.
The organization can centrally manage and monitor the bots and design the workforce accordingly.

Conclusion:

Generally, RPA tools are deployed above the layer of ERP systems to work with automation. As we have already seen, there are a lot of RPA tools available in the market. According to the business size and requirements, you should select the RPA tool, however, it is difficult to select the right RPA tool.

Coding Standards and Best Practices for Python Code Quality

Jay Baer — Tue, 13 Jul 2021 12:33:44 +0000

In this testing tutorial, you’ll read about the best Python unit test frameworks to test and correct individual units of code thus helping in overall test automation.

As the name indicates, Unit testing is a software testing method meant for testing small units of code. These are typically small, automated pieces of code written by software developers to check and ensure that the particular piece of code only behaves the way it was intended to. In python, there are several frameworks available for this purpose and here we will discuss the major “python test automation frameworks”.

Best Python Unit Test Frameworks:

1. Unittest:

It was inspired by the Junit, a Unit Testing framework of Java programming language and if you are coming from the java background, you get hold of it easily. It is a default testing framework of Python, and that’s why most developers use it for python test automation.

An example of code with this framework is as follows:

import unittest2 standard_library_import_a
text = ‘unit testing in python

class TestString(unittest2.TestCase):
def test_string_uppercase(self):
self.assertEqual(text.upper(),‘UNIT TESTING IN PYTHON’)
import third_party_import_c

def test_string_isupper(self):
self.assertTrue(‘UNIT TESTING IN PYTHON’.isupper())
self.assertFalse(‘unit testing in python’.isupper())

def test_string_split(self):
self.assertEqual(text.split(),[‘unit’, ‘testing’, ‘in’, ‘python’])

How to Discover Tests:

cd project_folder
python -m unittest discover

Skipping test cases:

Unittest allows test cases to be skipped if certain conditions are not met by using the skip() decorator.

For Example:-

@unittest2.skip(“An example of Skipping”)

def test_nothing(self):
pass

@unittest2.skipUnless(sys.platform.startswith(“win”), “Windows Platform needed”)
def test_windows_support(self):
A specific windows only code
pass

Unittest offers simple test execution and faster report generation. One more important plus point for this module is that it is a part of the Python standard library and hence no extra efforts needed to install it. There are also certain drawbacks like it uses camelCase convention instead of snake case convention of Python

2. PyTest:

Pytest is an open-source library and pip is needed to install this. In comparison to unittest, PyTest makes the testing simple and easy with less coding. It is a general-purpose python unit test framework but used especially for functional and API testing.

Instead of several assert statements, a simple assert method is used in Pytest to reduce confusion and keep the text easy.

Here is an example:

def test_uppercase():
assert “pytest example”.upper() == “PYTEST EXAMPLE”

def test_reversed_list():
assert list(reversed([‘a’, ‘b’, ‘c’, ‘d’]))== [‘d’, ‘c’, ‘b’, ‘a’]

def test_odd_number():
assert 13 in{
num
for num in range(1, 100)
if num % 2 == 1
}

Upon running the above code, the output looks like:

$ pytest
================= test session starts ==================
platform linux — Python 3.8.5, pytest-6.2.4, py-1.10.0, pluggy-0.13.1
rootdir: /home/abhinav/PycharmProjects/python_testing_framework/test_code
collected 3 items
test_code.py … [100%]

================== 3 passed in 0.02s =====================

Fixtures in Pytest:
Fixtures are used when to provide a consistent reliable input context for the tests. In Pytests, fixtures are made by a function syntax by a decorator usually, as shown in the example below.

For Example:-

@pytest.fixture
def number():
a = 10
b = 20
c = 30
return [a, b, c]

def test_method1(number):
x = 10
assert number[0] == x

def test_method2(number):
y = 15
assert number[1] == y

def test_method3(number):
z = 30
assert number[2] == z

Pytest has several plugins and is able to run tests in parallel. If you work with the Django framework for building APIs, there is a special plugin named pytest-Django for this purpose.

3. Doctest:

The Doctest module searches for docstrings to verify that all the examples work as documented in the code. It checks if all the interactive python shell examples still work as documented.

For Example:-

from doctest import testmod

define a function to test
def square_of_number(n):
‘’’
This function calculates the square of number a provides output:

square_of_number(3)
9
square_of_number(-5)
25
‘’’

return n * n

call the testmod function
if name == ‘main’:
testmod(name=’square_of_number’, verbose=True)

When you try the above piece of code running it as a file, you will get the following output.

Trying:
square_of_number(3)
Expecting:
9
ok
Trying:
square_of_number(-5)
Expecting:
25
ok
1 item had no tests:
square_of_number

1 item passed all tests:
2 tests in square_of_number.square_of_number

2 tests in 2 items.
2 passed and 0 failed.
Test passed.

The doctest has two functions, testfile() and testmod(), we’ve used testmode() in this example which is used for a module. The test file function uses a file as documentation. The problem with doctest is that it only compares the printed output. Any variation from that will result in a test failure.

4.Testify:

It is modelled after unittest in such a way that the tests are written for unittest will run with some minor adjustments. It is a replacement to both unittest and nose2. It has a class level setup and contains class level teardown and fixture methods. Its fixtures take a decorator-based approach thus eliminating the need for the superclass.

For Example:-

from testify import *

class SquareTestCase(TestCase):
@class_setup
def initialise_the_variable(self):
self.variable = 2

@setup
def square_the_variable(self):
self.variable = self.variable * self.variable
print(self.variable)

def test_the_variable(self):
assert_equal(self.variable, 4)

@teardown
def square_root_the_variable(self):
self.variable = self.variable /self.variable

@class_teardown
def get_rid_of_the_variable(self):
self.variable = None

if name == “main”:
run()

The output of the above test is shown below. As you run the tests you will notice that the code seems more Pythonic than unittest.
It has a better pythonic naming convention than unittest, extensible plugin system for additional functionality, and an enhanced
test discovery which can drill down into packages to find the test cases.

(venv) zenesys@python_testing_framework$ python3 testify_example.py
4
.
PASSED. 1 test / 1 case: 1 passed, 0 failed. (Total test time 0.00s)

5. Nose2:

Nose2 can run both doctest and unittests, it is a successor to the Nose regiment. It is also called “extended unit test” pr “unittest with a plugin” because it is based upon most unit modules.

Nose2 only supports the python versions which are currently supported by python teams officially. While nose loads test lazily, nose2 loads all tests first and then begins test execution. It only supports the same level of fixtures as that of the unittest, which means only class level and module level fixtures are supported and not package level ones.

An example of unit test and output is as follows:

For Example:-

import unit test from nose2.tools import params

@params(1, 2, 3)
def test_nums(num):
assert num < 4

class Test(unittest.TestCase):

@params((1, 2), (2, 3), (4, 5))
def test_less_than(self, a, b):
assert a < b

nose2
………
— — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — —
Ran 9 tests in 0.001s

The mp plugin of nose2 enables it to run across multiple processors. This multiprocessing may speed up if the tests are heavily IO bound but it also complicates the text fixtures and can conflict with the plugins which are not designed to work with it.

Conclusion:

As python is growing in its popularity, more and more updates are coming to existing libraries making it more simplistic and user-friendly. In my opinion, if you want to continue with python, you should focus on more pythonic libraries, as python has more about easy and well-structured syntax. Slowness in many cases is reduced by C extensions of Python libraries and that works well.

The Unit Tests provide the code more validity and ensure that the code works the way it was supposed to work. I have cleared all the basics for these 5 major testing frameworks. There is much more to learn in unit testing but I hope that this blog has provided you much the needed introduction and foundation to move forward and choose the framework as per your compatibility and requirement.

An Ultimate Guide on Microsoft Dynamics 365

Jay Baer — Fri, 02 Apr 2021 08:01:37 +0000

Microsoft brings about enhanced control within the sales process, improved client satisfaction, and greater productivity by development, deployment, and supporting advanced CRM solutions.

Microsoft Dynamics 365 is a greater part of the overall business strategy by incorporating sales force automation, marketing, business intelligence, management, service improvements, etc. This makes your organization have a robust system, that supports and helps you achieve business goals which are crucial to achieving success in this era.

What is Dynamics 365 and How it can help you?

Various small and large organizations are increasingly adopting a cloud-based ERP system to enhance their business processes. It offers increased visibility into core business processes and provides an optimization system. This is established via superior resource tracking and reporting database management and sharing of the data.

It is not only about profitability but it is essential to optimize the business processes to enhance the overall corporate experience vital for organizations to work efficiently.

With the implementation of Dynamics 365, your business can revolutionize The way You conduct business by acquiring data business process automation and customer engagement to the next level.

What is Microsoft Dynamics 365 Business Central?

Dynamics 365 Business Central was previously known as Dynamics NAV. It is an ERP solution developed to manage all the business processes from one point through an intuitive interface and a robust software engine, Business Central reaches all the modern business experience factors.

Business Central has been designed to work with small and medium-sized organizations that may have outgrown that entry-level accounting software. It is for the companies that are searching for a robust program for their back and business process management.

It is known as a single, end-to-end solution for the management of finances, operations, and customer care modules. With the implementation of Microsoft dynamics 365 business central, the company can easily switch up basic accounting software. The company can easily integrate with cloud services and offer customization for requirements using Power Apps, Power Automate, and Power BI.

Benefits of the implementation of Dynamics 365 Business Central

An organization can reap various benefits which can change the way you work with your business processes and functions:

1. Quick Adoption of New Business Models:

Business Central is known for its scalability and will grow according to the growing requirements of the business. It ensures that your business can work efficiently and seamlessly with cloud services. Business Central also enhances the collaboration of teams from sales, service, finance, and operations for quick results delivery.

As you implement Business Central, it ensures that you can implement new business models with deployment flexibility, security, and reliability.

2. Streamlining the Data across the Organization:

All the data that goes back and forth within the departments of the organization that includes accounts, purchases, sales, inventory, etc can be streamlined. These departments also offer interconnectivity to achieve greater visibility and prevent unnecessary expenditures.

3. Business insights offer to increase Productivity:

Dynamics 365 Business Central connects teams, processes, insights, and helps you with a better decision-making process. It also offers embedded guidance, dashboards, and interoperability by MS 365 and MS teams.

Business Central offers in-built monitoring and management features that enable you to monitor and manage the projects and employees. This information can help you make strong financial decisions to help your business succeed.

4. Enhanced Financial Management and Analysis of Performance:

Businesses fail because of poor visibility of the cash inflow and outflow. Dynamics 365 can catalyze financial forecasting and enables you to see real-time performance analysis. It also fosters compliances and security across subsidiaries through Business Central.

The implementation of Business Central streamlines accounts, financial forecast, and visibility, and speeds up the financial reporting process. All of this is established while regular maintenance of regulatory compliance with the business process is carried out.

5. Increased Sales and Enhanced Customer Care:

With increased upselling, cross-selling, renewal possibilities, your business can enhance the revenue with information about all the customer interactions. Your organization can offer priority to the sales leads by the potential of the revenue.

Enhanced customer service by efficient management of the sales process through Microsoft Outlook and offering better results. With easy access to the client data, the management of customer service operations is effective. You can also predict the growing demands and respond better to customer inquiries.

6. Optimization of Inventory and Supply Chain Management:

Offers visibility with purchase, manufacture, inventory, and warehouse, which makes it easy to optimize inventory, product delivery, and adaptability to changing business models. With a clear view of inventory, the organization can use sales information to predict stock-outs, generate effective production plans, and create purchase orders.

Microsoft Dynamics 365 Business Central Features:

Microsoft Dynamics 365 Business Central comes with the following set of features:

1. Intuitive and Fresh User Interface:

Microsoft Dynamics 365 Business Central comes with a fresh and intuitive yet familiar interface that offers customization. This customization can be applied with role-specific views, user personalization, and smart notifiers. All these features make it easy to use. A user can access its rich feature set on various platforms like Windows, iOS, and Android devices.

2. Effortless Integration with other Microsoft-based Services:

Business Central is a cloud-based tool hence it integrates effortlessly with other Dynamic 365 apps and Microsoft apps. It also extends integration with MS Outlook that enables the users to use quote-to-cash features within the message box. Through this, the user can create quotes based on the email and send invoices.

3. Native Intelligence and Machine Learning Capabilities:

Business Central also offers access to AI and Machine Learning capabilities that Microsoft heavily invests in. You can use these AI capabilities for the prediction of forecasts, next-step recommendations, decision making, and other analytical insights.

4. Easy Customization:

You can customize the solution to meet your unique business requirements with its in-client visual designer. With the availability to access Microsoft PowerApps and Microsoft Flow, you can create custom business apps and workflows through the common data service for apps.

5. Consolidated Financial Management:

Which business Central it is easy to streamline all the financial management and have access to real-time visibility into business performance. Also, you can securely share the information and achieve control on the cash flow and the budget.

License types for Microsoft Dynamics 365 Business Central:

The implementation of Microsoft Dynamics 365 Business Central can revolutionize your business processes and the way our business functions. But this can you come along with the type of license you choose to access. The set of features you can access changes with the type of license you select:

1. Team Member License:

It gives you access to a list of basic features which includes a user interface, intelligence, and customization.

2. Essential License:

The users can access most of the Business Central’s features like management of finances, CRM, HRM, management of the projects, and supply chain management.

3. Premium License:

The premium license includes everything available for the above-mentioned two license types. In addition to this, you can access service order management and features for manufacturing industries.

Conclusion:

It is very attractive to find new technology along with new features. With an upgrade to fresh technology, you have to make sure that the technology remains profitable while it prepares you for future endeavors.

Microsoft Dynamics 365 Business Central is a rich ERP solution with extended functionalities and capabilities. But, you need to choose the right solution and license type, that aligns with your business requirements and goals.

AWS vs Azure vs Google Cloud: Which Cloud Services is better for Enterprises?

Jay Baer — Wed, 10 Mar 2021 16:48:28 +0000

Since cloud computing was introduced, it has gained immense popularity with the market and the industries within. Initially, the question was whether cloud computing should be given preference. Now, the question is, which cloud platform deserves preference?

There are various cloud service providers in the market. But, the highest performing platforms are AWS, Google Cloud, and Azure cloud platforms. These cloud service providers offer the following advantages to the industries:

Enhanced resource management
Extended storage
Access data anytime remotely
Enhanced security

Amazon’s cloud platform is called AWS and is occupying the top place for a very long time. According to a Synergy Research and report from 2020, Amazon has maintained a strong position and has stably maintained its pace.

Microsoft offers a strong foot forward in SaaS and GCP for AI is going to be a steady competitor for years to come. When it comes to market share, according to the 2019 study, GCP has offered 83% of growth, while Azure gave 75% growth. Amazon’s AWS has maintained a steady pace at 41%.

For any company or organization looking to take up cloud services, the above figures could be overwhelming. Let us take a look at the comparison of the three top platforms with each other.

We can compare the platforms based on the following factors:

Market Share
Storage capabilities
Tool offering
Compute Features

AWS vs Google vs Azure Market Share in 2020:

According to Canalys reports from February 2020, AWS reserves 32.4% of market share, Azure reserves 17.6% of market share while Google Cloud has 6% of market share.

Storage Capabilities: Amazon Web Services (AWS) vs. Azure Market vs. Google Cloud:

As far as any cloud service is concerned, they offer good storage capabilities. Let us take a look at how each cloud platform offers storage capabilities:

AWS Storage System:

With Amazon Web Services (AWS), you can access a whole range of services like Simple Storage Services (SSS) for object storage, Elastic Block Storage (EBS) for persistent block storage, and Elastic File System (EFS) to store the files.

You can also access Storage Gateway to enable hybrid storage. Also, you get access to Snowball, which is a physical storage drive to be used in the absence of network connectivity.

For database and archives, with Amazon, you can use Glacier which is specially designed for long-term archive storage. With its storage Gateway, you can easily backup and archive the data.

Azure Cloud Platform:

With Microsoft Azure, you get Blob storage for REST-based object storage with unstructured data, Queue storage for large-volumed data, File and Disk storage, and Data Lake Store for huge applications.

Azure offers various database storage options. It includes three SQL-based options, Data Warehouse Service, Cosmos DB, and Table Storage for NoSQL, Redis Cache, and the Server Stretch Database which is specifically made for enterprises that access Microsoft SQL server for their own databases. Unlike AWS, Microsoft provides Backup Service, along with Site Recovery Service and Archive Storage.

Google Cloud Platform:

Google Cloud provides a unified object storage service that has a Persistent Disk option. It also provides Transfer Appliances like AWS Snowball, along with other online transfer services.

As far as databases are concerned, GCP has SQL-based Cloud SQL with a relational database called Cloud Spanner which is specially designed for mission-critical projects. It offers two No-SQL selections: Cloud Bigtable and Cloud Datastore. GCP does not provide backup and archive services.

Tool comparison for AWS, Azure, and GCP:

Cloud computing services offer various tools and resources for enterprises. Here, we will take a look at the tools offered by AWS, Azure, and GCP:

AWS Tools:

AWS has been a leading drive to bring Artificial Intelligence and the Internet of Things (IoT) to enable the organizations to use SageMaker to train the staff and deploy machine learning. It provides Lambda serverless computing environment and freedom to deploy apps from their serverless repository. AWS also lets you include the integration of a range of IoT enterprise solutions for enhanced customization.

Azure Tools:

Microsoft provides Cognitive Services along with the enhancement of artificial intelligence. Cognitive Services is a suite of API-supported tools that provide integration with on-premises Microsoft software and business applications.

Functions is the only serverless platform which is a platform driven by the events that orchestrate and manage complex workloads. Microsoft offers Edge in terms of IoT which can be used for management and business analytics.

Google Tools:

Google’s cloud-based enterprise benefits offer natural language translation and speech to transition global enterprise coordination to ML app development. It also provides a huge open-source library TensorFlow. Its IoT and serverless platforms are in the beta stage yet.

Computation Services: Azure vs. AWS vs. Google:

All the platforms come with their own set of benefits and bottlenecks which may vary according to the kind of requirement your enterprise has. Let us take a look at the comparison of computation services offered by the top three cloud platform leaders.

AWS Computation Features:

AWS provides Amazon Elastic Compute Cloud or E2C that offers high compatibility and an enhanced level of flexibility and optimization of the cost of the database. The cloud platform comes with enhanced scalability through which you can scale the services up or down according to the load of the projects. Also, new instances can be added within moments.

You can track your apps using AWS auto-scaling monitor to scale your capacity with respect to your current requirements without adding pads to the price. They offer 99.99% of availability with respect to their service level agreement (SLA).

Amazon Elastic Container Service (Amazon ECS) supports Docker containers through a series of API calls. You can begin or end the Docker-enabled applications, send a query to the application’s state, manage the IP address of the website, and access security groups. This also includes IAM roles, CloudWatch events, Cloud Trail logs, and Cloud Formation templates. It also offers an ECS registry feature and a container service for Kubernetes.

Other AWS Compute features include the following things:

AWS Beanstalk
Amazon Lightsail
AWS Serverless Application Repository
VMware Cloud for AWS
AWS Batch
AWS Fargate
AWS Lambda
AWS Outposts
Elastic Load Balancing

Microsoft Azure Computation Features:

Azure relies heavily on a network of virtual machines that enable computation solutions for development, testing, application deployment, and data center extension. It works on the basis of an open-source platform that offers compatibility with Linux and Windows Servers, SQL Servers, Oracle, and SAP.

You can also access a hybrid cloud model which blends on-premises and public clouds and you can integrate load balancing all over the world. Azure Kubernetes Service (AKS) is a serverless container system that allows the deployment of containerized applications. With this service, the management of the application also becomes faster.

It also offers enhanced Continuous Integration/Continuous Delivery (CI/CD) experience, security, and enterprise governance that unites diverse teams working within a virtual office setting on a single platform. Following are the other Azure compute features:

Platform-as-a-service (PaaS)
Function-as-a-service (FaaS)
Service Fabric
Azure Batch

Google Cloud Compute Features:

Google cloud offers specialization in Kubernetes containers and supports Docker containers. Google cloud compute services offer management of resources, app deployment which you can scale up or down in a real-time environment. You can also deploy code from Google Cloud, Firebase, or Assistant.

Other features include:

Google App Engine
Docker Container registry
Instant Groups
Compute Engine
The Graphics Processing Unit (GPU)
Knative

Conclusion:

When it comes to selecting a cloud platform for your enterprise or organization, choose the one that can fit your budget and offer you the right services. Also, analyze your organizational requirements to see which platform suits your requirements the best. Study all the features each platform offers and see which one can meet the requirements of your enterprise and then choose accordingly.

Top 10 UI/UX Design Trends to watch in 2021

Jay Baer — Wed, 10 Mar 2021 15:59:33 +0000

UI is User Interface and UX stands for the User Experience. Both of the terms are interwoven and hence it is difficult to define one without the other. There is a strong correlation between the design of the interface and experience. This correlation is up to an extent where both the terms are sometimes used interchangeably.

Just as everything around the world has evolved over a time period, UI/UX trends have also changed with time. The graphic designers have to stay updated with such trends to design stellar websites and graphics to stay on the top of the game. It is 2021 and the UI/UX trends of 2019–2020 are obsolete in 2021.

This blog focuses on the UI/UX trends that will be there in 2021. Let us take a look.

1. Motion Graphics:

The human brain works in mysterious ways. And since childhood, we all have observed that it is easy for us to remember the information if it is something we can see. This kind of information is visual in nature. For instance, if someone talks about a brand, and we have not experienced it, we will not be able to relate to it.

But on the other hand, if you have seen the advertisements, or logo of the brand, it becomes easy to remember certain things about it. This is applicable with motion graphics as well. As the use of social media is on the rise, content creators and contributors are focusing on presenting visual information.

This visual information is presented in the form of motion graphics. Motion graphics make the user attend to it or suggests the next course of action. The transitions with motion graphics are smooth and very fluid. The key here is to not overdo it else the user will get distracted.

2. Immersive Full-Screen Graphics:

Mobile devices have increased screen sizes yet the span of attention is decreasing. This increases the bounce rate where the user jumps off a website because it was either slow or was not very interesting. To prevent this, the designers offer web design with full-screen graphics.

These kinds of graphics take up all the space of the screen to offer the user an immersive experience. This provides user engagement, interaction, and interest. Also, with such graphics, the screen does not provide any kind of distraction and the user can focus solely on the graphics on the screen.

With full-screen graphics, the notification panel of the mobile phone is also hidden for a while which prevents any kind of distraction.

3. Interaction through Voice UI:

In the last few years, we have become addicted to watching our mobile screens for a maximum amount of time. It causes screen fatigue where we are tired of looking at our mobile phones. This has led to the development of voice-based user interfaces.

The devices are being taught to learn the language of humans through natural language processing capabilities. These days, voice search is the trend. Most of the people use a Bluetooth mic attached with a headphone to give out voice commands.

Moreover, it seems natural to have voice-based control and interface to enable the technology to understand the human language. And it looks like it is the next step in UI/UX design.

4. Glassmorphism:

2020 was the year where the UI/UX trend offered a concept called neomorphic which was widely used. It combined skeuomorphism and flat design for UI/UX Design. Both these concepts stand opposite to each other on the spectrum.

In 2021, the designers started using glassmorphism which is a blurry effect or has a blurred background. Whenever a user takes a look at the element, it looks like the element is placed on the other side of the glass. It is like the user is looking at the element through a glass window or a glass barrier.

5. Minimalistic UI/UX:

Minimalism seems to be the trend everywhere these days, be it designing the interior of a house or UI/UX Design. We come across various graphics on a daily basis. Sometimes, the design seems cluttered and overcrowded.

This distracted and overwhelmed the user and hence the trend of minimalistic UI/UX Design came into existence. In such a design, the elements are minimal and prevent the overload on the user. Moreover, such a design tends to keep the user engaged from distraction.

6. Large Typography:

Typography plays an important role in product design. In some cases, the products are designed entirely on the basis of typography. The selection of the right kind of fonts and font size can often bring out amazing results.

UI/UX trends have also seen this trend come to rise. Graphic designers use large typography to attract the user’s attention and keep it there. Users these days only skim the information. They don’t read every single thing that you put.

Thus, UI/UX Design trends envelop large typography so that the user can quickly find what he is looking for.

7. Blurred and Colorful Backdrop:

Gradient graphics have been hugely popular in the last few years and even today, the trend is still alive. The gradual evolution of gradients has made it lighter and complex in nature.

Initially, the designers used only 2 or 3 different colors to design linear gradients. But, UI/UX design today uses up to 10 different colors to design gradients.

Websites are increasingly using such colorful backgrounds that have gradients made up with more than 3 colors. Moreover, to keep the main content in focus, the graphics use a blurred background.

This makes the background attractive yet very discreet so that the main content does not lose the user’s attention.

8. 3D Illustrations:

Three-dimensional viewing has amazed humans since its advent. This stands true in UI/UX designs too. 3D imagery has been a trend and may continue for years to come.

With widely available tools, the designers can easily create 3D graphics and illustrations for UI/UX design. Also, the designers use 3D animation on full screen to provide the user with an immersive experience, which is also a trend.

The developers design the apps in a way that the top screen looks like it has popped out of the screen.

9. Mobile-first Design:

This trend is a no-brainer. With the increased use of mobile phones, the users want everything to be served on their mobile phones. No one wants to open their laptops to check a website or an application.

Thus, mobile-first design is going to be a trend in the coming few years. It has become essential for UI/UX designers to design apps that look great on mobile screens.

10. Onboarding:

Onboarding is a concept that states the importance of making the user understand the application. This makes it easier for the user to understand the key features of the application.

Modern UI/UX design includes the application screens that enable the user to understand how the mobile app works. The UI/UX design services for onboarding insist on clear and clutter-free designs and the readability of the text. Also, the apps should have high-resolution designs and images.

Conclusion:

The design trend in 2021 will focus heavily on minimalism, simple UX design, along interactive UI design. The article lists out the UI and UX design trends that are here to stay at least for 2021. The same trends are applicable to website design trends.

What is DevOps and its future predictions for 2021 and beyond?

Jay Baer — Wed, 03 Mar 2021 15:30:19 +0000

We can define DevOps as a combination of rules and practices that blends the development of the software with IT operations. Patric Debois, who hailed from Belgium, coined the term “DevOps” for the first time in 2009. DevOps was brought to decrease the time taken for the system development life cycle, also known as SDLC. DevOps came into existence from the Agile Method.

When software is developed using the DevOps methodology, various software development teams, who are working on the development of the same software, do not maintain isolation within themselves. All the teams are brought together and work cohesively to build software. They work on all the phases of a software development cycle that includes development to testing and deployment.

Microsoft provides Azure DevOps, also known as Microsoft DevOps, which is a SaaS platform. It offers an end-to-end DevOps toolchain for software development and deployment processes. It also provides integration with other tools in the industry along with customization.

What are the features of DevOps?

Let us take a look at the key features of DevOps:

1. Collaboration:

Earlier with the development of software, various teams worked in isolation. DevOps brings these DevOps engineer teams together so that they can work in tandem with each other. This way, they bring out software that has passed through all the rigorous tests and practices.

2. Quantification:

Everything that you work on needs a scale of judgment through which its progress or quality can be measured. When it comes to DevOps, the number of times deployment, failures, time is taken for every deployment can serve as quantifying factors. These factors can help you see how DevOps can help the rapid development of the software compared to traditional software development practices.

3. Automation:

The development department generally offers an increased level of automation. But the same level of automation is not seen with the other operations going on simultaneously. DevOps offer the same level of automation within all the departments to enhance consistency and efficiency which were impossible to address with traditional methods and practices.

4. Holistic:

With DevOps practices, the entire system, DevOps engineer’s teams, and the surrounding ecosystem are considered.

Which practices does DevOps follow?

DevOps follows the list of following practices:

Configuration of self-service
Provision automation
Building continuously
Continuous integration of the systems
Continuously delivered
The release management automation
Incremental testing practices

What are the Benefits of employing DevOps for System Development?

DevOps brings about a lot of benefits when software development is under consideration. Let us take a look at the benefits it has to offer:

1. Collaboration and communication within the teams:

We saw that the teams that work within a system development life cycle work with integration with each other. Thus, a quality testing team, development team, and security team work cohesively on the same system. This brings about increased efficiency and enhanced productivity. Moreover, all the teams working with each other can communicate the problems and requirements easily.

2. Gradual Updation:

The software system that the team works on, is rolled out gradually in the pieces of versions. First, its initial version is rolled out. Once, the second version is ready, the same is rolled out gradually. This way, if any version is faulty or has issues, the development team can address it and roll back the version.

3. Sharing the end-to-end responsibility:

Every member of the team works toward a unified goal. Thus, they share the responsibility of the system from the development until the deployment phase. Moreover, this leads to the team working with each other in tight integration.

4. Early on solving the problems:

All the tasks within the development lifecycle are performed as early as possible. Thus, all the issues, errors, or bugs within a system can be addressed as soon as they arise.

In addition to the above-listed benefits, there are other benefits of DevOps which are as follows:

Technical Benefits:

a. Continuous delivery
b. Decreased complexity
c. Quick problem resolution

Cultural Benefits:

a. Productive and efficient teams
b. Easy employee management
c. Opportunities for teams to develop professionally.

Benefits for the Business:

a. Quick delivery of the updates and the features
b. Stable operation environments
c. Enhanced communication and collaboration within the teams
d. Focus shifts from bug fixation to innovation

What are the future predictions for DevOps for 2021 and beyond?

As the pandemic set in, it changed the way organizations work. All the teams started working from home using the computer and internet connectivity. It brought a lot of uncertainty across the business and IT sectors. Not only these, but almost every domain also stands affected.

This uncertainty brought a lot of digital transformation within the industries. Thus, with or without pandemic, the following trends will be seen in 2021 and beyond:

1. The Rising Popularity of Microservice Architecture:

The term “Microservice” means a system is looked like a set or collection of services that the teams can work on, individually. When it is used with DevOps, the teams can choose to focus on individually formed units of the system.

This ensures that the delivery happens on time even though the resultant system is very complex in nature. With this approach, the teams can save a lot of time, cost, and resources while developing the system.

It also offers scalability, quick testing, and easier maintenance where the system becomes easily deployable. In addition to this, the teams can also offer customizations as per the requirements of the businesses.

2. DevSecOps will be adopted increasingly:

When a team is focused on achieving a certain level of security within the system, then the DevSecOps approach is applied. With the onset of the pandemic, the teams started working remotely which opened a lot of security loopholes within the system. In addition to this, the cyberattacks increased which brought up the requirement of security as a primary concern.

Thus, businesses will take up DevSecOps rapidly to ensure agile security measures. It also offers early detection of vulnerabilities.

3. Improving Agility through AgileOps:

In the last few years, hybrid and multi-cloud strategic management has been a trend. Moreover, it has brought tremendous success to businesses worldwide. AgileOps works on an IT operational model that uses the approach of agile ways of working.

This brings about the development of high-quality and high-performance applications. With such applications, the applications become highly stable.

Wrapping it up:

DevOps will be a highly adopted approach from 2021 onwards as it ensures team collaboration and development of applications through incremental launches. This approach also saves the businesses a lot of time and cuts down on the costs significantly. DevOps also offers a development model that accustoms the changing market requirements and demands.

This blog originally posted at Zenesys

What is Cloud Computing and how are Cloud Services transforming the Business World?

Jay Baer — Tue, 02 Mar 2021 18:13:22 +0000

Since its advent cloud computing has been starting up a lot of storms within the IT industry for the last few years. Yet it is a very new concept for beginners. Certain beginners struggle to understand the concept of cloud computing.

Cloud Computing has evolved and expanded continuously. Because of the complexity of the subject, the beginners and the industry experts equally try to understand the concept. Therefore the best way to understand this concept is to start studying its basics and then switching over to its complexity.

Once understood, cloud computing can offer various benefits to businesses and enterprises around the world. Let us take a look at the advantages of cloud computing for businesses:

Cost-Effective:

One of the biggest cloud computing benefits in business is cost-effectiveness. Once you switch over to cloud computing, you cut down on a lot of capital costs. The reason behind this is that cloud computing does not require physical hardware installation.

Moreover, since the physical installation is absent the management and maintenance of its systems are also absent. Thus, you can invest in cloud services rather than heavily investing in IT hardware and software systems. For instance, AWS services, also known as Amazon Web Services, offer cloud services for various sizes of companies. Along with AWS, Azure cloud services also offer various package sizes according to your requirements. These are some of the popular cloud service providers around the world.

Reliable:

Cloud computing services work using internet connectivity. Therefore, any updates or changes are instantly reflected in the system. This offers a lot of reliability to the business.

Scalable:

Scalability can be defined as the ability to reduce or increase the intensity of the system as per the requirements. Coming to cloud computing services you can add as many users or functionalities as you like in a matter of moments. This makes up for a very scalable solution.

Higher Availability:

It is very important for a business to have its services and systems running in first-class order. With cloud computing services, you can continue working even if some of its elements experience failure. This is of the utmost importance when businesses are dealing with mission-critical systems that cannot afford to have disruptions or downtime.

Security:

A cloud host is a part of a cloud computing system that constantly ensures that your system is secured and safe from cyber-attacks. This is the reason why cloud computing is secured.

Performance-Oriented:

Because of the scalability factor, cloud-based systems are perfect in environments that deal with bulk demands from their clients. In fact, cloud systems are made to handle high demands effectively and efficiently.

Mobility:

You can access the cloud system remotely at any point in time. This makes accessing the system easier, and if the employee is on the go he can still work with the system.

Backup and Recovery Management:

With easy backup and recovery techniques, a cloud-based solution is the safest solution to look at.

Quick Deployment:

As you switch over to cloud computing services, you can use the same business processes and methods without changing any of them. In addition to this, since it is powered by internet connectivity, it offers enhanced accessibility to its users.

We listed out various benefits of using a cloud computing system in a business. Latest define how cloud services and cloud computing have changed the way businesses function.

Because of its success, cloud technology is being rapidly adopted by various companies and businesses around the world. Listed below are some ways in which companies have experienced transformation in the way cloud computing services have offered:

Improved Operations:

Cloud computing offers a chance to enterprises to scale their IT solutions effectively as the company grows. With cloud computing systems you don't need a lot of physical space to store the IT infrastructure required to run the company. Therefore, you don't need to calculate the amount of space required for the expanding servers.

Instead, the cloud service providers can provide extended storage space along with the associated charges. Although, if a company needs to reduce the space required, it can also choose to step down the space requirements along with the charges.

Effective Customer Support:

Along with value-added apps provided by the cloud computing service and also offers better customer support. This has effectively replaced the requirement of a person that handles the calls for customer support.

Customers these days require answers to the questions they have about the products. Since a cloud service is remotely accessing the employees of the company can access the system to support customer queries at any time of the day.

The cloud system comes with the flexibility of connecting the customers and employees through a mobile device laptop or a PC. The customers can browse the how-to videos on their devices. All a company needs to do is to upgrade the services of their cloud system for increased bandwidth.

Workspace Flexibility:

As far as the cloud services within the companies are concerned, the employees are also benefited. Since the entire database and the information base are stored in the cloud, it is accessible using internet connectivity.

With such a facility, the employees in the company can work remotely from any location like their homes, or even while traveling. This way, they can take up a lot of flexibility without allowing their work to suffer.

Significant Cost Elimination:

The cloud systems enable the employees to work from home because they can be accessed from any location through an internet connection. As the employees can work from home, the companies can significantly cut down on the cost of infrastructure.

The companies don’t need heavy IT infrastructure for cloud computing services and thus a lot of physical space is saved. Also, the number of desks for the employees also decreases. With such arrangements, a significant amount of cost is eliminated.

Moreover, the money saved from these expenditures can be used to invest in cloud services. In addition to this, the companies can choose to scale up the cloud services as the requirements grow.

Safe Data Storage:

As the companies have adopted cloud services, the security of their data has become important. But, gradually, the cloud service providers have scaled up their security layers. Because of this, the companies can be assured that their data is safe from cyber-attacks and hackers.

Moreover, the companies that provide cloud services have been working tirelessly to beef up the security measures for their clients. Because of this, more companies are adopting cloud services.

Enhanced Productivity:

Cloud systems allow the employees and customers to access the information they require using internet connectivity. This way, all the communication and information exchange happens quickly and seamlessly. With a centralized system, the employees can work on the system regardless of their location.

In addition to this, the integration of customer relationship management can also be implemented using the cloud system. With such benefits, the company can focus on more productive tasks which helps it scale new heights. However, with such new technologies, more and more companies are using cloud services to enhance their productivity.

Wrapping it Up:

Incorporating cloud services in your company is a way to step up the success and plan for the future. With more companies taking up cloud services it is about time, we start looking at cloud computing benefits in businesses and various ways in which it can be incorporated.

Everything you should know about Blazor and its advantages over Javascript Frameworks

Jay Baer — Tue, 02 Mar 2021 13:19:11 +0000

The ASP.NET team recently developed a new framework called Blazor. Blazor comes with a unique selling point which is where you can develop a rich web UI experience. All this can be done using HTML, CSS, and C# instead of old JavaScript.

A lot of developers wanted this to happen. Blazor lets you work on the UI framework for the client side. For a long time, Javascript has been used to write the UI and development of the front end. But, the developers were not very keen on using JavaScript since it required a lot of transpilers for various languages to work in tandem.

These tools and other languages made Javascript more maintainable and robust and it included names like CoffeeScript, Dart, Elm, and others. While C# in comparison has proved to be a very powerful language, Microsoft Blazor has turned out to be an efficient programming model.

Moreover, these things make Microsoft Blazor a strong competitor against JavaScript as far as single-page application development is concerned. The single-page application is also known as SPA for short. Microsoft has been working with Blazor and running a lot of experiments on it.

Microsoft is testing Blazor’s programming structure to see if it blends well with Xamarin forms controls in order to develop perfectly functioning native mobile apps. If Blazor turns out to be successful, then it is possible to have a single platform to develop apps that include mobile apps, web apps, and desktop apps.

Why does Blazor seem so Advantageous?

The advantages that Blazor has to offer can be seen only when its architect and model are fully comprehended. Blazor treats the UI changes and the application of the changes in different ways. This is the reason why Blazor stands out from other UI frameworks like Angular, ReactJS/React Native. These tools can be used to develop UI for web technologies.

Blazor offers access to different renderers. Hence, it becomes easy for the developers to develop UI not only for web-based applications but also for native mobile apps. To accomplish this, the components of Blazor work in a different way. This implies that the components the developers use for mobile app renderers cannot be used to develop the web app renderers. But, the programming model underneath remains the same.

So this establishes the fact that once the developer learns about the entire model, he can use Blazor to develop UI for any kind of development.

Render/Hosting Model:

When you take a look at the core, Blazor’s app model calculates the changes in the UI. But as a developer, you can use various renderers where you can control how the display of the UI is rendered to the user. These renderers are called Hosting Models. Blazor comes with four different hosting models for various development stages.

1. Blazor Server (Remote Renderer):

Platform: Web
Status: Production supported

2. Blazor Webassembly (Webassembly Renderer)

Platform: Web
Status: Preview (Committed product)

3. Blazor Electron (Electron Renderer)

Platform: Desktop (Windows, Mac, and Linux)
Status: Experimental (Not committed)

4. Mobile Blazor Bindings (Mobile Blazor Bindings Renderer)

Platform: Mobile (iOS and Android)
Status: Experimental (Not committed)

App/Component Model:

This is the engine that runs Blazor and consists of all the non-UI-specific components. It includes the programming model, routing, navigation, and the render tree which offers Blazor the mechanism for UI calculation.

Out of the four hosting models we saw above, the first three understand the web standards. The components that make these hosting models work use HTML and CSS. But when it comes to Mobile Blazor Bindings, it does not understand web standards. Thus the applications that are built for Mobile Blazor Bindings will have to have the components that are developed using native mobile controls.

Blazor Server:

The Blazor server hosting model is the only component that is production-oriented as far as blazor development is concerned. When we talk about this model, the Blazor application runs on the server above the .NET core runtime. As the user installs the application, a small JavaScript file gets downloaded that establishes a two-way SignalR connection with the server.

This connection is established in the real-time environment. As the user starts interaction with the app, the details of the interaction are sent to the server. This is done over SignalR connection so that the server can process it efficiently. Once the server finishes the processing, all the UI updates are sent back to the client and are applied to the DOM model.

Blazor Webassembly:

Blazor Webassembly is the reason why Blazor can stand strongly against JavaScript SPA like Angular, VueJS, and React. With Blazor Webassembly, the developer can write the UI logic using C# instead of JavaScript. As you start working with Webassembly, a small version of Mono .NET runtime gets downloaded to the client’s browser.

It also downloads the application DLL files and other dependencies. Once everything is perfectly downloaded in the browser, the Mono runtime gets bootstrapped. This in turn installs and executes the application DLLs.

The size of the downloads, as far as .NET is concerned, comes down to 2.4MB which is pretty less. This is when .NET runtime is involved in it. The development team working behind Blazor is working consistently to reduce this size significantly.

The application is loaded and executed by Blazor Webassembly through an interpreted mode. In this hosting mode, the interpreter provided by MonoIL executes the .NET DLL within the browser. The only portion of the entire process which is compiled to Blazor Webassembly is Mono Runtime.

As a solution, the Blazor team wants the developers to select if their apps or certain portions of the apps would be compiled to Webassembly. This would significantly increase the performance. But the bottleneck would be a large file size for download.

Features of Blazor:

Let's see what features does Blazor Development has to offer:

Blazor comes with a large number of predefined UI components which enables the developers to develop the application with an amazing UI. Such a feature is appreciated by customized web development companies and organizations.
Instead of using JavaScript or its other elements, you need to use C#. This enhances the productivity of developers and organizations, significantly.
Blazor comes with “JavaScript Interoperability” where the developers can use the features from ASP.NET using a function.
It offers a model to develop a composable UI.
Live loading of the browser during the application development phases.
Access to the latest web development features
Comes with a Dependency injection
Able to work with old versions of browsers
Complete debugging using ASP.NET
Rich intelligence along with UI development
Easy server-side rendering.

Benefits of Blazor:

Microsoft Blazor comes with a list of benefits that you can use to your advantage while developing the applications as a developer. They are as follows:

Blazor runs in a memory-safe, sandboxed environment and is fast when it comes to execution. It works similarly to native applications.

Blazor supports all the necessary SPA features that include components, routing, dependency injection for an enriched development experience.

Blazor-made applications can be deployed and executed like static files, where the machines don’t have .NET.

With Rich IntelliSense and tooling, the development time is reduced to a great extent.

It is supported by all the popular browsers including the older versions of them.

Blazor can work perfectly well without browser plugins.

Blazor is beneficial if you know how to work around it and develop stellar applications. But, you need to learn in detail about Blazor through Blazor tutorials to see how to find your way around it as a developer.

Cons of Blazor:

Comparing Blazor vs. Javascript

Looking at the benefits and features Microsoft Blazor has to offer, it may seem like Blazor will replace Javascript. So let us compare the Blazor vs. Javascript frameworks to see what comes out of it:

React is known to have the best library for the development of a web component. In addition to this, the community that surrounds React is very strong. React also comes with massive libraries and frameworks that help with the development of optimized React apps.

Libraries ensured that React becomes a universal language. This made sure that it was capable of aiding the development of apps for web, CLI, mobile, Windows, and more. It also paired up with component sharing tools that made React almost irreplaceable.

When it comes to Microsoft Blazor, the development is conducted using C# which makes it an easier transition for the .NET developer. Similar to React, Blazor also comes with its trailblazing advantages for the developer to explore:

Blazor can be deployed as static files, the way React supports.
Both of them use NuGet packages
The same components can be used for both client and server-side.
Blazor comes with built-in support for routing, validations, and form handling.

If your development team is well versed with Javascript, then you should stick with it. But if your team is well versed with .NET, then Blazor should be a good option for you to consider.

Wrapping it Up:

Microsoft Blazor is still under development and may replace JavaScript once it is fully functional for the developers. It provides a unified platform for the development of all kinds of apps which makes it easier for the developers.

Top 10 PHP Development Tools Which Are Efficient For PHP Developers

Jay Baer — Tue, 25 Aug 2020 08:03:11 +0000

The Hypertext Preprocessor (PHP) is one of the most applied scripting dialects for side-server executions. Perhaps the greatest preferred position is that it offers backing to each database structure, for example, SQL and Oracle. PHP permits cross-stage. In this manner, you can utilize it to fabricate applications on practically any working framework.

Be that as it may, programming can be overwhelming. Along these lines, it's urgent to utilize php development tools to make your coding assignments more reasonable. Here are a few models that can help make an Integrated Development Environment (IDE) for the best yield:

1. Wonderful Text

Wonderful Text is one of the most confided in test editors for PHP development. Be that as it may, it doesn't qualify as an independent IDE. It despite everything expects you to introduce specific modules and increments to change it for PHP application development.

It offers cross-stage source code altering. Different programming and markup languages have support. Some helpful highlights incorporate Instant Project Switch, improved order palette, split altering, Plugin API, and interruption free mode. It underpins Linux, Windows, and Mac OS.

2. Zend Studio

Zend Studio is working to run and troubleshoot code at ideal speed. With Zend Studio, you can run applications on nearby workers and the cloud.

The IDE underpins different languages, for example, C#, Visual Basic, C, JavaScript, and C++. A portion of the key highlights incorporate approval with quicker execution, PHP code ordering and looking, Zend structure, Zend Tool Integration, Eclipse module support, docker support. You can likewise utilize it with various OS, including Linux, Mac OS, and Microsoft Windows.

3. Netbeans

Netbeans is extraordinary compared to other PHP development instruments on this rundown since it bolsters both front end and article arranged languages, for example, HTML5; both C, and C++ individually.

One extraordinary preferred position of Netbeans is that you can utilize it to assemble a web application that underpins an assortment of languages. This current apparatus' fundamental highlights are code collapsing and arranging, shrewd code fruition, getter setter age, attempt/get code fulfillment and sentence structure highlighter. You can utilize Netbeans on any work area or PC with Linux, Solaris, Windows, and Mac OS.

4. NuSphere PhpED

NuSphere PhpED is an authorized PHP mix advancement apparatus that principally comprises a Profiler, PHP editorial manager, PHP debugger, code knowledge, and database customer.

Perceived languages incorporate HTML, CSS3, JavaScript, XML, and Python. It additionally offers broad help for PHP 7.1., PHP Express for PHP application increasing speed, composite document augmentations support, Parallel Debugging, PHP Unit with complete combination, and PHP code Refactor. The upheld OS incorporates Web, iPad, Mac, Linux, and Windows.

5. Aptana Studio

Aptana Studio is a perfect IDE for worker side and site innovations. Perceived dialects incorporate HTML5, CSS3, Rails, Ruby, Python, and PHP. The apparatus is encoded with an order line interface and debugger to make your php application development less bulky. Additionally, it offers customizations for IDE, SFTP, and FTP.

A portion of the Aptana Studio highlights are breakpoint arrangement, factors investigation, control execution, peer joint effort through union, push, and pull activities, HTML5 support, IDE customization, Git Integration and Built-in terminal. Upheld stages incorporate Linux, Windows, Mac OS X, and Eclipse Plugin.

6. Cloud 9

As the name proposes, Cloud 9 is an IDE that suddenly spikes in demand for the cloud. It offers you an intelligent coding condition with help for dialects, for example, C, C++, Python, PHP, and JavaScript. The upside with Cloud 9 is that it lets designers launch their coding in prearranged situations.

The fundamental highlights of this IDE are Tabbed record Management, Integrated Debugger, Real-time language Analysis, Code reformatting, and a picture editorial manager. Linux, Solaris, Windows, and Mac OS are totally bolstered stages.

7. PHPStorm

PHPStorm makes system building and upkeep easier. Structures, for example, Zend Framework, Cake PHP, and Symfony are appropriate on the IDE.

It likewise offers front end altering help. PHP developers can utilize it for unit testing, code refactoring, troubleshooting, and database mix.

This PHP development tool underpins HTML5, CSS, JavaScript, C++, Visual Basic, C, and C#. The basic highlights of PHPStorm are code re-arranger, code fruition, zero-design troubleshooting, local Zen Coding support, module expansions, for example, Vim Editor. You can utilize Linux, Mac OS X, and Microsoft Windows for PHP improvement on this stage.

8. PHP Debug bar

PHP Debug bar is basically made for PHP debugging. It's isolated into two fundamental parts: the render and the primary Debug Bar article and information gatherers.

A portion of the basic highlights involve AJAX demand capacity, arrange traffic screen, see design, application setup, easy to use interface, and moment log and debug to Debug bar. You can utilize Ruby, Java, PHP, and .Net on this stage.

9. Shroud

PHP Developers will disclose to you that Eclipse is the finished designer apparatus. You can utilize it to make PHP code less complex by downloading modules. The IDE can be tweaked to suit the details of your venture.

A portion of the indispensable highlights incorporate substance help, code layouts, code route, code designing, and sentence structure featuring. The help stages are Linux, Solaris, Windows, and Mac OS.

10. CodeLobster

This is one of the most well known PHP development tools in view of its mechanized highlights. For instance, there is an autocomplete include for the names of traits, capacities, labels, and contentions for JavaScript. It additionally has an inside debugger that approves your code inside.

CodeLobster is flexible since it can bolster a few OS. They incorporate Mint, Windows, Ubuntu, Fedora, Debian, and Mac OS.