Approaches and Difficulties in Transitioning ASP.NET Applications to .NET Core 7

The introduction of .NET Core 7 has ushered in a host of enhancements and features, prompting numerous organizations to contemplate the upgrade of their current ASP.NET applications to this iteration.

Consequently, the migration journey has a range of tactics but also comes with numerous obstacles that development firms must surmount to accomplish a seamless transition.

In this piece, we’ll look at the distinctions in architecture between ASP.NET and ASP.NET Core, dissect the transformative alterations that developers may encounter during the migration process, and even highlight the reasons compelling developers to embrace this shift.

The Architectural Contrasts Between ASP.NET and .NET Core

Though the syntax and programming model are somewhat alike, ASP.NET and .NET Core differ significantly in their underlying architecture. ASP.NET Core stands as a versatile, modular, and lightweight open-source framework, renowned for its performance and scalability.

In contrast to ASP.NET's heavy reliance on System.Web.dll and its close integration with IIS, ASP.NET Core generally adopts the Kestrel web server and boasts the flexibility to be hosted on diverse platforms, including macOS and Linux.

ASP.NET Core applications can also leverage IIS, specifically on Windows systems, unlocking advantages such as Kernel Mode Windows Authentication and direct file transmission. 

Another key distinction is the middleware pipeline. In ASP.NET Core, this pipeline is fully customizable, empowering developers to fine-tune individual middleware components according to their specific needs.

Converting Web Forms

Trying to convert ASP.NET Web Forms applications which are closely integrated with System.Web.dll and rely on IIS, into ASP.NET Core is a common pain point. To complete this migration, you’ll need a full-scale redevelopment of the application within the ASP.NET Core framework. This will take your time and money fast, especially if you don’t give it enough attention, so you’ll want to make sure you’ve got an experienced team on your side. 

To address this issue, you’ll want to pinpoint the most important parts of the application and prioritize their conversion. Another way you could solve it is by separating the business logic and other various aspects from the Web Forms pages, streamlining the code within the pages and simplifying the migration

URI Decoding Differences

ASP.NET Core and ASP.NET Framework have differences in URI decoding. In ASP.NET Core, when decoding %2F, the entire path is unescaped except for %2F itself, since converting it to '/' would alter the path structure. For that reason, it can only be decoded after splitting the path into segments. 

As Microsoft outlined, to get the HttpRequest value.Url in ASP.NET Core 7, you should use "new Uri(this.AspNetCoreHttpRequest.GetEncodedUrl());" to prevent the Uri from misinterpreting the values. This is necessary to handle URI decoding discrepancies between the two frameworks.

Transition Strategies for Migrating ASP.NET Applications to .NET Core 7

The migration of ASP.NET applications to .NET introduces several challenges. Here’s how they can be solved:

1) Validate Integration Tests Involving Application Layer Protocols:

During the migration process, you’ll want to execute integration tests to validate the continued functionality of application layer protocols like HTTP or FTP. These tests help uncover any compatibility issues that might arise because of changes in the underlying framework or libraries. For instance, when migrating HTTP-based APIs, rigorous testing should cover endpoint functionality, request handling, and response formats. Similarly, for applications employing FTP for file transfers, integration tests should confirm the seamless operation of file uploads and downloads.

2) Choose the Appropriate Migration Approach within the Development Process:

When thinking about migrating to .NET Core, development teams have two primary options:

• Slice-by-Slice Migration: Dividing the application into smaller slices, each incrementally migrated. It’s a gradual transition and simplifies the problem-solving process.

• Layer-by-Layer Migration: In this method, entire application layers are migrated one at a time. It’s good for applications with minimal interdependencies and well-defined layers. 

Choosing between these approaches depends on how complex your project is, how proficient the team is, and the organization's risk tolerance. In some cases, a hybrid approach combining both methods may expedite the migration process.

3) Refactor the Application in the Current Development Branch:

Before migration, it’s best to refactor the application within the current development branch. This involves code cleanup, the removal of deprecated APIs, and addressing design flaws. 

4) Keep the Code Structure for Branch Comparisons:

Maintaining the application's code structure throughout development is essential for streamlining the migration process. This makes it easy to identify issues that stem from code changes. Developers can leverage version control practices to create feature branches aligned with the existing code structure, facilitating tracking and review before merging into the main branch.

5) Thoroughly Test the Migration Across Various Dimensions:

Comprehensive testing is paramount during the migration process, encompassing:

• Performance Testing: Evaluate application performance under a range of workloads to confirm it meets performance expectations post-migration.

• User Acceptance Testing: Have stakeholders validate the application's behaviour from their perspective, aligning the migrated application with business objectives and user expectations.

• Integration Testing: Assess the interaction between different components to detect issues arising from changes in interdependencies.

• Unit Testing: Validate individual components to ensure their functionality remains intact.

The Takeaway

Moving to .NET Core 7 is one part of a major evolution in the world of web development. While there are a ton of benefits for those undergoing the transition, it demands careful planning, skilled development teams, and a systematic approach to overcome the challenges. By following the outlined strategies and best practices, businesses can migrate successfully, ultimately reaping the rewards of a more modern and adaptable development framework.

Written By Ben Brown

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ISU Corp is an award-winning software development company, with over 17 years of experience in multiple industries, providing cost-effective custom software development, technology management, and IT outsourcing.

Our unique owners’ mindset reduces development costs and fast-tracks timelines. We help craft the specifications of your project based on your company's needs, to produce the best ROI. Find out why startups, all the way to Fortune 500 companies like General Electric, Heinz, and many others have trusted us with their projects. Contact us here.

Introducing Microsoft Dynamics 365 Copilot: The Next-Generation AI for Business Applications

Microsoft Dynamics 365 Copilot is a new AI-powered feature that brings the next gen of AI and natural language processing to Dynamics 365. This is a direct byproduct of Microsoft's acquisition of OpenAI, which, since then, they have been working together on various AI projects. 

Copilot is based on the same language-learning model as ChatGPT, and It’s designed to work alongside businesses to help them create ideas and content faster. It does so by handling tedious tasks, providing insights, and the next best steps just by the user describing what’s needed. Copilot is the world’s first AI copilot natively built-in to both CRM and ERP applications.

Copilot uses natural language processing to understand what the user is trying to accomplish and provides suggestions and recommendations based on that understanding. Copilot works across all Dynamics 365 applications, including Sales, Customer Service, Field Service, Finance, Supply Chain Management, and Commerce.

3 Key Features of Copilot:

• Natural Language Processing: Copilot uses NLP to understand what the user is trying to accomplish and then gives suggestions and recommendations based on that understanding.

• Contextual Answers: Copilot in Dynamics 365 Customer Service is an awesome tool for agents. Copilot drafts contextual answers to queries in both chat and email, as well as providing an interactive chat experience over knowledge bases and case history so this AI-powered expertise is always available. 

• AI-Assisted Content: Copilot in Dynamics 365 Sales helps sellers with customer follow-up by generating AI-assisted content and recommendations, such as contextual emails based on the customer’s interests and preferences.

How Developers Can Use Copilot

With its machine-learning algorithms, Copilot has a lot to offer to developers, specifically when it comes to coding. Copilot works well with JavaScript, TypeScript, Python, Ruby, and Go, and it can analyze code - and then provide suggestions for the next line. That’s still just surface level, this is a more in-depth look at what Copilot can do:

Documentation:

• It can create code comments, write a function or class descriptions, and explain code segments.

• Developers can ask Copilot to generate documentation for specific functions, classes, or code blocks, saving them time in the long run. 

Troubleshooting:

• When developers encounter issues or error messages, Copilot can help with troubleshooting. It will give suggestions for debugging, recommend potential solutions, and explain the more common programming errors.

• Developers can also describe the problem they're facing, and Copilot can guide them on how to address it.

Code Formatting:

• Copilot can help developers adhere to the guidelines for standards and formatting. It will suggest things like formatting options, style improvements, and best practices.

• Developers can use Copilot to automatically format their code or make it consistent with their preferred coding style.

Code Review:

• During code reviews, Copilot helps by suggesting improvements and identifying potential issues, and even offering alternative coding approaches.

• Developers can work with Copilot to make sure the code quality meets the standards.

Code Snippets:

• Copilot can supply code examples and snippets for common programming tasks, algorithms, and even libraries. Developers can request code samples for specific functionalities, which inevitably will save them the effort of searching for examples online.

Integrations:

• Developers can integrate Copilot into their preferred development environments, such as code editors or integrated development environments (IDEs). This allows them to access Copilot's assistance seamlessly while coding.

Customization:

• Developers may have the option to customize Copilot's behavior and preferences based on their specific coding requirements and coding standards.

Learning:

• Developers, especially those learning to code or exploring new languages, can use Copilot as a learning tool. It’ll provide explanations, code samples, and insights into programming concepts.

Use Cases

Microsoft claims that more than 63,000 organizations have used Copilot's AI features, the draw is that it can integrate AI and ML across business functions. The reason a company would turn to Copilot in 2023 is because this is where the potential to normalize AI lies for Microsoft users. 

Imagine the Chat GPT responsiveness integrated into every form of customer service, sales, informational sessions, email chains, supply chain management, and operations. When people say “AI will take over”, the underlying fear there is that it’s going to increase productivity and innovation to a point people couldn’t even conceive. 

The Takeaway

Microsoft Dynamics 365 Copilot represents a significant leap in the integration of AI and natural language processing within business applications. Copilot is engineered to empower businesses by streamlining processes, which can either paint it as a public enemy or a trusted ally, depending on how it's embraced and leveraged.

Written By Ben Brown

—

ISU Corp is an award-winning software development company, with over 17 years of experience in multiple industries, providing cost-effective custom software development, technology management, and IT outsourcing.

Our unique owners’ mindset reduces development costs and fast-tracks timelines. We help craft the specifications of your project based on your company's needs, to produce the best ROI. Find out why startups, all the way to Fortune 500 companies like General Electric, Heinz, and many others have trusted us with their projects. Contact us here.

Best AI Cross-platform Development Frameworks

It’s a lot more than task automation with AI in cross-platform development. For the frameworks that leverage it, developers can develop versatile - efficient applications. The popularity of cross-platform app development stems from its unique advantages. As its influence grows, so do tools and frameworks for cross-platform development in the market. This surge initially happened gradually and then suddenly, tons of mobile app development companies became eager to explore what it could do for them. 

The Trajectory of Cross-Platform Apps

Internet service started in the 1980s. Back then, you needed a PC to access the web. But as technology developed, mobility became one of the most important aspects of the user experience. Users started to experience the temptation to use the internet while on the go. This impulse was increased by the introduction of smartphones and tablets in 2012. Today, your phone provides 100x the experience a PC would have back then.

According to Statista's analysis of internet accessibility, mobile users account for more than 55% of all online traffic. This information was sufficient to support a change in the way native mobile apps are developed. Mobile app development and mobile apps started to take precedence over other factors. The original response was to create distinct desktop and mobile applications. However, it didn't take long for developers to realize that this approach was not only lengthy but also expensive. As a result, cross-platform app development gained momentum.

Enter AI

AI’s role in cross-platform development frameworks is consistent when it comes to developing apps and optimizing their performance. But the true potential of AI becomes most apparent when it's integrated into the development cycle. AI in cross-platform development isn't just about keeping up with the trend; it's about pushing the boundaries of what's achievable. In the development cycle, AI does a few things; fine-tunes algorithms, automates coding tasks, predicts user behavior, analyzes data, and personalizes the user experience.

To get the most out of these features, developers need the right framework and AI/ML expertise. With that said, here are some ideal options:

For integrating AI:

TensorFlow: Best suited for tasks like image or speech recognition, natural language processing, and more complex AI tasks.

PyTorch: Ideal for developing AI-driven features within cross-platform apps. Its got a dynamic computation graph and user-friendly interface which is best for tasks demanding neural network implementation.

Keras: A high-level neural networks API that simplifies AI model integration. Great for tasks like image classification, text generation, and recommendation systems.

For Cross-Platform Development with AI:

React Native: Excellent for delivering consistent, AI-enhanced user experiences across iOS, Android, and the web.

Flutter: Offers a single codebase approach and customizable UI components, which is ideal for creating visually appealing, AI-powered cross-platform apps that prioritize performance.

Xamarin: Focuses on code reusability and allows AI functionalities in cross-platform apps. Good for developers with C# skills aiming for a smooth development experience.

For User-Friendly AI Integration:

Ionic: Great for creating aesthetic mobile apps with integrated AI features for iOS and Android.

Kotlin Multiplatform Mobile: Facilitates code sharing across iOS and Android platforms, great for tasks requiring consistent AI features across devices with native-like performance.

The Age of Personalization

Many brands struggle with personalized customer experiences, which was evident in a Gartner report that revealed the struggle in 63% of digital marketing teams. Interestingly enough, less than 20% of them have used AI or ML throughout their operations.

What machine learning does in the context of cross-platform development is make software that not only accommodates user choices but also adapts to and picks up on user behaviour. Machine learning makes judgements based on data analysis. It anticipates user behaviour and fine-tunes algorithms to maintain a customized user experience. 

Again, tools like TensorFlow, PyTorch, and Keras are great because they enable features like natural language processing and predictive analytics. These technologies allow programmers to produce dynamic and adaptable applications that take into account user preferences and actions, ushering in a new era in which software not only meets user demands but also develops along with them. Machine learning is the future of cross-platform development, its ability to completely change the user experience is enough to lock that claim in for most developers.

Moving Forward

This year, mobile apps are projected to do almost a trillion dollars in revenue. With that in mind, it begs the question; What frameworks should you choose? The simple reply is that it depends on the company and the functional specifications of the app. If you want the best advice, reach out to a qualified and reputable provider who will not only put you on a path to success but also limit the headaches of getting started.

Written By Ben Brown

—

ISU Corp is an award-winning software development company, with over 17 years of experience in multiple industries, providing cost-effective custom software development, technology management, and IT outsourcing.

Our unique owners’ mindset reduces development costs and fast-tracks timelines. We help craft the specifications of your project based on your company's needs, to produce the best ROI. Find out why startups, all the way to Fortune 500 companies like General Electric, Heinz, and many others have trusted us with their projects. Contact us here.