The Difference between Software Architecture and Design

The difference between software architecture and software design is not really known to most of the people. Even for developers, the line is often shadowy and they might mix up elements of software architecture patterns and design patterns. In this blog, I would like to simplify these concepts and explain the differences between software design and software architecture. In addition, I will show you why it is important for a developer to know about software architecture and software design.

The Definition of Software Architecture

In simple words, software architecture is the process of converting software characteristics such as flexibility, scalability, feasibility, reusability, and security into a structured solution that meets the technical and the business expectations. This definition leads us to ask about the characteristics of a software that can affect a software architecture design. There is a long list of characteristics which mainly represent the business, functional & non-functional or the operational requirements, in addition to the technical requirements.

The Characteristics of Software Architecture

As explained, software characteristics describe the requirements and the expectations of a software in operational and technical levels. Thus, when a product owner says they are competing in a rapidly changing markets, and they should adapt their business model quickly. The software should be “extendable, modular and maintainable” if a business deals with urgent requests that need to be completed successfully in the matter of time. As a software architect, you should note that the performance and low fault tolerance, scalability and reliability are your key characteristics. Now, after defining the previous characteristics the business owner tells you that they have a limited budget for that project, another characteristic comes up here which is “the feasibility”.

Software Design

While software architecture is responsible for the skeleton and the high-level infrastructure of a software, the software design is responsible for the code level design such as, what each module is doing, the classes scope, and the functions purposes, etc.

If you are a developer, it is important for you to know what the SOLID principles is and how a design pattern should solve regular problems.

Single Responsibility Principle: means that each class has to have one single purpose, a responsibility and a reason to change.

Open Closed Principle: a class should be open for extension, but closed for modification. In simple words, you should be able to add more functionality to the class but do not edit current functions in a way that breaks existing code that uses it.

Liskov substitution Principle: this principle guides the developer to use inheritance in a way that will not break the application logic at any point. Thus, if a child class called “XyClass” inherits from a parent class “AbClass”, the child class shall not replicate a functionality of the parent class in a way that change the behavior parent class. So you can easily use the object of XyClass instead of the object of AbClass without breaking the application logic.

Interface Segregation Principle: Simply, since a class can implement multiple interfaces, then structure your code in a way that a class will never be forced to implement a function that is not important to its purpose. So, categorize your interfaces.

Dependency Inversion Principle: If you ever followed TDD for your application development, then you know how decoupling your code is important for testability and modularity. In other words, If a certain Class “ex: Purchase” depends on “Users” Class then the User object instantiation should come from outside the “Purchase” class.

Remember there is a difference between a software architect and a software developer. Software architects have usually experienced team leaders, who have good knowledge about existing solutions which help them make right decisions in the planning phase. A software developer should know more about software design and enough about software architecture to make internal communication easier within the team.

Microservices Patterns

What are microservices?

Microservices – also known as the microservice architecture – is an architectural style that structures an application as a collection of services that are

  • Highly maintainable and testable
  • Loosely coupled
  • Independently deployable
  • Organized around business capabilities
  • Owned by a small team
  • Design Patterns for Microservices

Microservice architecture has become the de facto choice for modern application development. Though it solves certain problems, it is not a silver bullet. It has several drawbacks and when using this architecture, there are numerous issues that must be addressed. This brings about the need to learn common patterns in these problems and solve them with reusable solutions. Thus, design patterns for microservices need to be discussed. Before we dive into the design patterns, we need to understand on what principles microservice architecture has been built:

  • Scalability
  • Availability
  • Resiliency
  • Independent, autonomous
  • Decentralized governance
  • Failure isolation
  • Auto-Provisioning
  • Continuous delivery through DevOps

The microservice architecture is not a silver bullet. It has several drawbacks. Moreover, when using this architecture there are numerous issues that you must address.

The microservice architecture pattern language is a collection of patterns for applying the microservice architecture. It has two goals:

  • The pattern language enables you to decide whether microservices are a good fit for your application.
  • The pattern language enables you to use the microservice architecture successfully.

Applying all these principles brings several challenges and issues. Let’s discuss those problems and their solutions.

Application architecture patterns

1. Decomposition

How to decompose an application into services?

  • Decompose by business capability – define services corresponding to business capabilities
  • Decompose by subdomain – define services corresponding to DDD subdomains
  • Self-contained Service – design services to handle synchronous requests without waiting for other services to respond
  • Service per team – Each service is owned by a team, which has sole responsibility for making changes.

2. Data management

How to maintain data consistency and implement queries?

  • Database per Service – each service has its own private database
  • Shared database – services share a database
  • Saga – use sagas, which a sequences of local transactions, to maintain data consistency across services
  • API Composition – implement queries by invoking the services that own the data and performing an in-memory join
  • CQRS – implement queries by maintaining one or more materialized views that can be efficiently queried
  • Domain event – publish an event whenever data changes
  • Event sourcing – persist aggregates as a sequence of events

3. Transactional messaging

How to publish messages as part of a database transaction?

  • Transactional outbox
  • Transaction log tailing
  • Polling publisher

4. Testing

How to make testing easier?

  • Consumer-driven contract test – a test suite for a service that is written by the developers of another service that consumes it
  • Consumer-side contract test – a test suite for a service client (e.g. another service) that verifies that it can communicate with the service
  • Service component test – a test suite that tests a service in isolation using test doubles for any services that it invokes

5. Deployment patterns

How to deploy an application’s services?

  • Multiple service instances per host – deploy multiple service instances on a single host
  • Service instance per host – deploy each service instance in its own host
  • Service instance per VM – deploy each service instance in its VM
  • Service instance per Container – deploy each service instance in its container
  • Serverless deployment – deploy a service using serverless deployment platform
  • Service deployment platform – deploy services using a highly automated deployment platform that provides a service abstraction

6. Cross cutting concerns

How to handle cross cutting concerns?

  • Microservice chassis – a framework that handles cross-cutting concerns and simplifies the development of services
  • Externalized configuration – externalize all configuration such as database location and credentials

Communication patterns

1. Style

Which communication mechanisms do services use to communicate with each other and their external clients?

  • Remote Procedure Invocation – use an RPI-based protocol for inter-service communication
  • Messaging – use asynchronous messaging for inter-service communication
  • Domain-specific protocol – use a domain-specific protocol

2. External API

How do external clients communicate with the services?

  • API gateway – a service that provides each client with unified interface to services
  • Backend for front-end – a separate API gateway for each kind of client

3. Service discovery

How does the client of an RPI-based service discover the network location of a service instance?

  • Client-side discovery – client queries a service registry to discover the locations of service instances
  • Server-side discovery – router queries a service registry to discover the locations of service instances
  • Service registry – a database of service instance locations
  • Self-registration – service instance registers itself with the service registry
  • 3rd party registration – a 3rd party registers a service instance with the service registry

4. Reliability

How to prevent a network or service failure from cascading to other services?

  • Circuit Breaker – invoke a remote service via a proxy that fails immediately when the failure rate of the remote call exceeds a threshold

5. Security

How to communicate the identity of the requestor to the services that handle the request?

  • Access Token – a token that securely stores information about user that is exchanged between services

6. Observability

How to understand the behavior of an application and troubleshoot problems?

  • Log aggregation – aggregate application logs
  • Application metrics – instrument a service’s code to gather statistics about operations
  • Audit logging – record user activity in a database
  • Distributed tracing – instrument services with code that assigns each external request an unique identifier that is passed between services. Record information (e.g. start time, end time) about the work (e.g. service requests) performed when handling the external request in a centralized service
  • Exception tracking – report all exceptions to a centralized exception tracking service that aggregates and tracks exceptions and notifies developers.
  • Health check API – service API (e.g. HTTP endpoint) that returns the health of the service and can be pinged, for example, by a monitoring service
  • Log deployments and changes

UI patterns

How to implement a UI screen or page that displays data from multiple services?

  • Server-side page fragment composition – build a webpage on the server by composing HTML fragments generated by multiple, business capability/subdomain-specific web applications
  • Client-side UI composition – Build a UI on the client by composing UI fragments rendered by multiple, business capability/subdomain-specific UI components

Great Architecture in Azure

A great architecture helps guide you to design, build, and continuously improve a secure, reliable, and efficient application.  In this post, we’ll introduce you to the pillars and principles that are essential to a great Azure architecture. The cloud has changed the way organizations solve their business challenges, and how applications and systems are designed. The role of a solution architect is not only to deliver business value through the functional requirements of the application, but to ensure the solution is designed in ways that are scalable, resilient, efficient and secure. Solution architecture is concerned with the planning, design, implementation, and ongoing improvement of a technology system. The architecture of a system must balance and align the business requirements with the technical capabilities needed to execute those requirements. It includes an evaluation of risk, cost, and capability throughout the system and its components.

Design

While there is no one-size-fits-all approach to designing an architecture, there are some universal concepts that will apply regardless of the architecture, technology, or cloud provider. While these are not all-inclusive, focusing on these concepts will help you build a reliable, secure, and flexible foundation for your application.

A great architecture starts with a solid foundation built on four pillars:

  • Security
  • Performance and scalability
  • Availability and recoverability
  • Efficiency and operations

Great Architecture

SECURTIY


Data is the most valuable piece of your organization’s technical footprint. In this pillar, you’ll be focused on securing access to your architecture through authentication and protecting your application and data from network vulnerabilities. The integrity of your data should be protected as well, using tools like encryption. You must think about security throughout the entire lifecycle of your application, from design and implementation to deployment and operations. The cloud provides protections against a variety of threats, such as network intrusion and DDoS attacks, but you still need to build security into your application, processes, and organizational culture.


Great Architecture

PERFORMANCE & SCALABILITY


For an architecture to perform well and be scalable, it should properly match resource capacity to demand. Traditionally, cloud architectures do so by scaling applications dynamically based on activity in the application. Demand for services change, so it’s important for your architecture to have the ability to adjust to demand as well. By designing your architecture with performance and scalability in mind, you’ll provide a great experience for your customers while being cost-effective.


Great Architecture

AVAILABILITY AND RECOVERABILITY


Every architect’s worst fear is having your architecture go down with no way to recover it. A successful cloud environment is designed in a way that anticipates failure at all levels. Part of anticipating these failures is designing a system that can recover from the failure, within the time required by your stakeholders and customers.


Great Architecture

EFFICIENCY AND OPERATIONS


You will want to design your cloud environment so that it’s cost-effective to operate and develop against. Inefficiency and waste in cloud spending should be identified to ensure you’re spending money where we can make the greatest use of it. You need to have a good monitoring architecture in place so that you can detect failures and problems before they happen or, at a minimum, before your customers notice. You also need to have some visibility in to how your application is using its available resources, through a robust monitoring framework.


Great Architecture

SHARED RESPONSIBILITY


Moving to the cloud introduces a model of shared responsibility. In this model, your cloud provider will manage certain aspects of your application, leaving you with the remaining responsibility. In an on-premises environment you are responsible for everything. As you move to infrastructure as a service (IaaS), then to platform as a service (PaaS) and software as a service (SaaS), your cloud provider will take on more of this responsibility. This shared responsibility will play a role in your architectural decisions, as they can have implications on cost, operational capabilities, security, and the technical capabilities of your application. By shifting these responsibilities to your provider you can focus on bringing value to your business and move away from activities that aren’t a core business function.


Great Architecture

SUMMARY


Architecture is the foundation of your application’s design. A great architecture will give you the confidence that your app can sustainably meet the needs of your customers both now and in the future. The architectural priorities and needs of every app are different, but the four pillars of architecture are an excellent guidepost you can use to make sure that you have given enough attention to every aspect of your application:

  • Security: Safeguarding access and data integrity and meeting regulatory requirements
  • Performance and scalability: Efficiently meeting demand in every scenario
  • Availability and recoverability: Minimizing downtime and avoiding permanent data loss
  • Efficiency and operations: Maximizing maintainability and ensuring requirements are met with monitoring

Focusing on these pillars when designing your architecture will ensure you’re laying a solid foundation for your applications in the cloud. With a solid foundation, you’ll be able to drive innovation through your environment, build solutions that your users will love, and foster the trust of your customers.

Serverless Computing – Pros and Cons

Serverless computing is the fastest-growing cloud service model right now, with an annual growth rate of 75%, according to RightScale’s Cloud report. That’s hardly surprising, given the technology’s ability to lower costs, reduce operational complexity, and increase DevOps efficiencies.

So, as the calendar was poised to turn to a new year, we asked several experts what to expect next from this rising technology. While we received a wide range of answers, everyone agreed that serverless will mature and see even greater adoption rates in 2020.

Why use Serverless computing?

Serverless computing offers a number of advantages over traditional cloud-based or server-centric infrastructure. For many developers, serverless architectures offer greater scalability, more flexibility, and quicker time to release, all at a reduced cost. With serverless architectures, developers do not need to worry about purchasing, provisioning, and managing backend servers. However, serverless computing is not a magic bullet for all web application developers.

What are the advantages of serverless computing?

No server management is necessary

Although ‘serverless’ computing does actually take place on servers, developers never have to deal with the servers. They are managed by the vendor. This can reduce the investment necessary in DevOps, which lowers expenses, and it also frees up developers to create and expand their applications without being constrained by server capacity.

Developers are only charged for the server space they use, reducing cost

As in a ‘pay-as-you-go’ phone plan, developers are only charged for what they use. Code only runs when backend functions are needed by the serverless application, and the code automatically scales up as needed. Provisioning is dynamic, precise, and real-time. Some services are so exact that they break their charges down into 100-millisecond increments. In contrast, in a traditional ‘server-full’ architecture, developers have to project in advance how much server capacity they will need and then purchase that capacity, whether they end up using it or not.

Serverless architectures are inherently scalable

Imagine if the post office could somehow magically add and decommission delivery trucks at will, increasing the size of its fleet as the amount of mail spikes (say, just before Mother’s Day) and decreasing its fleet for times when fewer deliveries are necessary. That’s essentially what serverless applications are able to do.
Applications built with a serverless infrastructure will scale automatically as the user base grows or usage increases. If a function needs to be run in multiple instances, the vendor’s servers will start up, run, and end them as they are needed, often using containers (the functions start up more quickly if they have been run recently – see ‘Performance may be affected’ below). As a result, a serverless application will be able to handle an unusually high number of requests just as well as it can process a single request from a single user. A traditionally structured application with a fixed amount of server space can be overwhelmed by a sudden increase in usage.

Quick deployments and updates are possible

Using a serverless infrastructure, there is no need to upload code to servers or do any backend configuration in order to release a working version of an application. Developers can very quickly upload bits of code and release a new product. They can upload code all at once or one function at a time, since the application is not a single monolithic stack but rather a collection of functions provisioned by the vendor.
This also makes it possible to quickly update, patch, fix, or add new features to an application. It is not necessary to make changes to the whole application; instead, developers can update the application one function at a time.

Code can run closer to the end user, decreasing latency

Because the application is not hosted on an origin server, its code can be run from anywhere. It is therefore possible, depending on the vendor used, to run application functions on servers that are close to the end user. This reduces latency because requests from the user no longer have to travel all the way to an origin server.

What are the disadvantages of serverless computing?

Testing and debugging become more challenging

It is difficult to replicate the serverless environment in order to see how code will actually perform once deployed. Debugging is more complicated because developers do not have visibility into backend processes, and because the application is broken up into separate, smaller functions.

Serverless computing introduces new security concerns

When vendors run the entire backend, it may not be possible to fully vet their security, which can especially be a problem for applications that handle personal or sensitive data.
Because companies are not assigned their own discrete physical servers, serverless providers will often be running code from several of their customers on a single server at any given time. This issue of sharing machinery with other parties is known as ‘multi-tenancy’ – think of several companies trying to lease and work in a single office at the same time. Multi-tenancy can affect application performance and, if the multi-tenant servers are not configured properly, could result in data exposure. Multi-tenancy has little to no impact for networks that sandbox functions correctly and have powerful enough infrastructure.

Serverless architectures are not built for long-running processes

This limits the kinds of applications that can cost-effectively run in a serverless architecture. Because serverless providers charge for the amount of time code is running, it may cost more to run an application with long-running processes in a serverless infrastructure compared to a traditional one.

Performance may be affected

Because it’s not constantly running, serverless code may need to ‘boot up’ when it is used. This startup time may degrade performance. However, if a piece of code is used regularly, the serverless provider will keep it ready to be activated – a request for this ready-to-go code is called a ‘warm start.’ A request for code that hasn’t been used in a while is called a ‘cold start.’

Vendor lock-in is a risk

Allowing a vendor to provide all backend services for an application inevitably increases reliance on that vendor. Setting up a serverless architecture with one vendor can make it difficult to switch vendors if necessary, especially since each vendor offers slightly different features and workflows

Who should use a serverless architecture?

Developers who want to decrease their go-to-market time and build lightweight, flexible applications that can be expanded or updated quickly may benefit greatly from serverless computing.
Serverless architectures will reduce costs for applications that see inconsistent usage, with peak periods alternating with times of little to no traffic. For such applications, purchasing a server or a block of servers that are constantly running and always available, even when unused, may be a waste of resources. A serverless setup will respond instantly when needed and will not incur costs when at rest.
Also, developers who want to push some or all of their application functions close to end users for reduced latency will require at least a partially serverless architecture, since doing so necessitates moving some processes out of the origin server.

When should developers avoid using a serverless architecture?

There are cases when it makes more sense, both from a cost perspective and from a system architecture perspective, to use dedicated servers that are either self-managed or offered as a service. For instance, large applications with a fairly constant, predictable workload may require a traditional setup, and in such cases the traditional setup is probably less expensive. Additionally, it may be prohibitively difficult to migrate legacy applications to a new infrastructure with an entirely different architecture.

The Reliability of Artificial Intelligence

Cognition is “the mental action or human intelligence processes of acquiring knowledge and understanding through thought, experience, and the senses”. Artificial Intelligence, therefore, can be defined as the simulation and automation of cognition using computers. Specifically applications of AI include expert systems, speech recognition and machine vision.

Today, self-learning systems, otherwise known as artificial intelligence or ‘AI’, are changing the way architecture is practiced, as they do our daily lives, whether or not we realize it. If you are reading this on a laptop or tablet or mobile, then you are directly engaging with a number of integrated AI systems, now so embedded in our the way we use technology, they often go unnoticed.

As an industry, AI is growing at an exponential rate, now understood to be on track to be worth $70bn globally by 2020. This is in part due to constant innovation in the speed of microprocessors, which in turn increases the volume of data that can be gathered and stored.

The following diagram depicts typical AI System workflow, AI frameworks provide the building blocks for data scientists and developers to design, train and validate AI models through a high-level programming interface and without getting into the nitty-gritty of the underlying algorithms. So, the reliability of AI is critically bound to two aspects – Data (sources & preparation ) and Inference (Training & Algorithms)

Perhaps, AI brings impressive applications, with remarkable benefits for all of us; but there are notable unanswered questions with social, political or ethical facets.

Even though the hype around AI is sky high, has the technology proven to be useful for enterprises?

As AI enables companies to move from experimental phase to new business models, a new study indicates errors can be reduced through careful regulation of human organizations, systems and enterprises.

This recent study by Thomas G Dietterich of Oregon State University reviews what are the properties of highly reliable organizations and how enterprises can modify or regulate the scale of AI? The researcher says, “The more powerful technology becomes, the more it magnifies design errors and human failures.”

And the responsibility lies with tech behemoths, the new High-Reliability Organizations (HROs) that are piloting AI applications to minimize risks. Most of the bias and errors in AI systems are built in by humans and as companies across the globe build great AI applications in various fields, the potential for human errors will also increase.

High-End Technology and Its Consequences

As AI technologies automate existing applications and create new opportunities and breakthroughs that never existed before, it also comes with its own set of risks, which are inevitable. The study cites Charles Perrow’s book Normal Accidents, written after a massive nuclear accident that delved into organizations which worked on advanced technologies like nuclear power plants, aircraft carriers, and electrical power grid among others. The team summarized five features of High-Reliability Organizations (HRO):

Preoccupation with failure: HROs know and understand that there exist new failure modes that they have not yet known or observed.

Reluctance to simplify interpretations: HROs build an ensemble of expertise and people so multiple interpretations can be generated for any event.

Sensitivity to operations: HROs maintains human resources who have deep situational awareness.

Commitment to resilience: Great enterprises and teams practice recombining existing actions. They have great procedures and acquire high skills very fast.

Under-specification of structures: HROs give power to each and every team member to make important decisions related to their expertise.

AI Systems and Human Organizations

There are some lessons that the researchers draw from many circles where advanced technology was deployed. Traditionally, AI history has been peppered with peaks and valleys and currently, the technology is seeing an exuberant time, as noted by a senior executive. As enterprises move to bridge the gap between hype and reality by developing cutting-edge applications, here’s a primer for organizations to dial down the risks associated with AI.

The goal of human organizations should be to create combined human-machine systems that become high-reliability organizations quickly. The researcher says AI systems must continuously monitor their own behavior, the behavior of the human team, and the behavior of the environment to check for anomalies, near misses, and unanticipated side effects of actions.

Organizations should avoid deploying AI technology where human organizations cannot be trusted to achieve high reliability.

AI systems should be continuously monitoring the functioning of the human organization. This monitoring should be done to check for threats to high reliability of the human organizations.

In summary, as with previous technological advances, AI technology increases the risk that failures in human organizations and actions will be magnified by the technology with devastating consequences. To avoid such catastrophic failures, the combined human and AI organization must achieve high reliability.

Benefits of Corporate Training

In the days before digital, corporate training often conjured up images of boring one-sided presentations and disengaged audiences. Now that the digital era has arrived, trainers must learn to leverage new methods and technologies to make corporate training more effective—achieving enhanced learning outcomes by engaging and inspiring learners.
The world of corporate training is changing, just as the work environment is changing. With staff no longer situated at one location, and with an increasing dependence on online resources, companies need to adapt the way they train to meet these new challenges. Companies, such as AxEdge Consulting, are developing a range of options to provide training that works around both the needs of the employer and the needs of the employee. Flexibility is key, as everyone is an individual and every business has a different culture. Effective learning materials and hands-on exercises will provide employees with a more conducive studying environment that fits around their normal habits but, at the same time, the use of face-to-face training, drawn from the more traditional forms of instruction, will help employees to utilize their learning effectively.

Face to Face
While many things can be done virtually in the digital age, physical interaction remains one of the best ways to learn. Communicating and developing relationships through personal interaction is one of the key reasons face-to-face learning continues to be a preferred methodology. Learners gain from the depth of information and experience that is imparted to them by the tutor. Tutors will have many years of experience in their field, which will enrich their tutorials in a way online learning cannot. This personal element allows learners to ask questions and receive an immediate response in the verbal language and style that they are comfortable with, therefore avoiding any problems of miscommunication or misinterpretation.
In search of new and better training tools, many corporate trainers have turned their attention to interactivity—the dialog that takes place between humans and computer software. By merging serious game-design thinking with interactive software, trainers are now able to leverage interactivity to create immersive, engaging and highly effective learning experiences for their employees.
If you’re looking for new tools and solutions to take employee learning and training to a whole new level, consider these six benefits of integrating interactivity in a corporate training strategy.

Enhanced Learning Environment
Interactivity strategies utilize interactive training software to allow employees to explore their learning environment—in their own way and at their own pace. In this environment employees will also be shown directly how to do things, a learning tactic that brings far better results than telling employees what to do.
The most successful training companies use graphical environments that are similar to the daily life situations—office, factory, etc.—of the employee learners. They also integrate visual components that make the content more eye-catching and encourage exploration of the training module by embedding hyperlinks to other pages that learners might find interesting. The net result of this enhanced environment is a better overall learning experience.

Improved Decision-Making
Through the use of scenario questions and simulations, interactivity allows employee learners to apply knowledge and make decisions in a risk-free non-judgmental environment. By removing the fear of failure, learners are free to formulate action plans by exploring unpredictable paths that lead to unknown outcomes. This type of experiential learning can help individuals gain valuable insights, from both their successes and failures—insights that invariably lead to better on-the-job decision-making and the performance of complex tasks.

Reinforcement through Feedback
An interactive training/learning platform requires employees to respond to what they are learning. This forces them to integrate the learning content with their own unique way of thinking as they stop to reflect on the answer they should give or the path they should choose. Once the choice is made, the learner receives feedback to help them recognize what they know versus what they should know. At the same time, interactive software gives trainers the ability to assess the performance of individual learners spontaneously, and in real time.
As an employee moves through the learning process, immediate feedback reinforces what they have learned and helps to steer them toward making better choices without compelling them to do so, as is often the case with traditional training and learning techniques.

Higher Levels of Engagement
Interactivity software integrated with serious game-design thinking doesn’t just present learning content. It immerses learners in the content and gives them control over the learning process. As a result, learning experiences become more vivid, stories more powerful, and questions more provocative. That all adds up to high levels of engagement than could never be achieved in a traditional classroom setting. Better engagement translates into better learning outcomes.

Greater Retention Rates
Studies show that a higher level of engagement during training activities results in greater retention and recall of knowledge on the part of the learner. And interactivity strategies such as the use of multimedia elements, real-world scenarios, and even basic achievement levels and badges can help to transform the most mundane training modules into engaging, thought-provoking and memorable learning experiences.
Corporate Training is important for both employees as well as corporate.
Some of the benefits of corporate training are:
Improved employee performance

  • The employee who undergoes the necessary training is more competent to perform in their job.
  • The training will give the employees a greater understanding of their responsibilities within the corporate.
  • The confidence which they will gain would enhance their overall performance which will benefit the company in the long run.

Improved employee satisfaction and morale
  • The investment in training that a corporate make shows the employee that they are valued.
  • Employees who feel appreciated through training opportunities may feel more satisfaction toward the jobs they are undertaking.