The 5 Key Types of IT Project Outsourcing

In today's fast-paced and evolving business landscape, outsourcing has become a go-to strategy for organizations to meet their goals. It’s difficult to imagine a business that’s succeeded long-term through dramatic changes such as the introduction of computers, the internet, and the global marketplace without leveraging some form of IT outsourcing or consultancy. 

This is not to say it can’t be done, but there is no question that businesses would have faced major challenges and been at an overall competitive disadvantage without the added support and expertise. We are now in a time frame where artificial intelligence is creating a new era of significant change for service delivery models and business operations in general. That means it’s yet another time when companies are going to be re-evaluating their strategies and likely looking for professional help in the form of outsourcing. 

What IT Projects Are Most Commonly Outsourced?

The big question for companies today is “When is it best for us to utilize outsourcing over in-house software development?” To be honest, there is no one right answer. Generally, businesses tend to outsource IT projects that require specialized skills or expertise that they simply don't have in-house or projects that are temporary and don't warrant the hiring of a full-time staff. 

Some of the most commonly outsourced IT projects include software development, web design, database management, cybersecurity, and process automation. Let’s take a closer look at each one:

What’s The Difference Between IT Projects and Software Development?

IT is a broad term that “software development” simply falls under the umbrella of, which is important to know because although IT specialists often still possess the necessary skills to build software systems, software developers may be more equipped to handle the demands of enterprise software. 

IT encompasses all aspects of managing and processing information, including hardware/software, networks, data storage, and cybersecurity. Software development involves the fundamental building blocks which involve the design, creation, testing, and maintenance of the software that runs on these systems, which are all essential components of a business's infrastructure.

When companies look to outsource software development, they’re not just looking for advice, they’re looking for a team of experts who can take their vision and ideas and bring them to life. 

Why Outsource Web Development/Design?

Web presence, whether it’s in the form of a website or web application is one of the most crucial aspects of running a business today. Brands can establish themselves in the marketplace, showcase their products and services, and most importantly, engage with their customers through an effective web strategy.

Now, developing and designing a website or web app is very complex and would require sufficient expertise in areas such as UI/UX design, front-end, and back-end development, server administration, database management, and cybersecurity. For this reason, companies outsource and save the time and resources it would take to bring on in-house staff to handle these tasks.

Increasing Popularity of Outsourcing Database Management 

Businesses worldwide are regularly looking to third-party providers for database management for a handful of reasons including:

• Skills shortage

• Being able to focus on other aspects of the business

• Cost 

Database management can be a tedious task that requires skills and knowledge from software experts and can certainly be expensive. By outsourcing database management, businesses can tap into this required level of expertise from professionals who can ensure that data is readily available but at the same time stored securely. For small and medium-sized businesses, this is a great option, especially for those that simply don’t have the time or budget to manage their own database in-house.

Why Should You Outsource Cybersecurity?

In today's digital age, cybersecurity has become a critical concern for businesses of all sizes. Outsourcing cybersecurity can be a great move for businesses that want to ensure their systems and data are protected against these threats whereas if they don’t, there are serious risks at stake. 

Third-party providers can offer a range of services when it comes to cybersecurity including risk assessment, threat monitoring, incident response, and security audits. They can also help businesses comply with regulatory requirements related to data protection and privacy. 

Outsourcing process automation

Process automation is a big topic in today’s world thanks to revelations from artificial intelligence. “Automating repetitive tasks” and “streamlining business operations” are the key phrases as they are what’s changing the way businesses function and how they will continue to function if they strategize with technology accordingly. 

Outsourcing process automation can be the separating factor between a business that closes its doors in 2030 and the startup from 7 years ago taking over all of its clientele. 

Third-party providers for process automation services can offer a range of solutions including software development, process mapping, and system integration. They will typically work with businesses to identify opportunities for processes that can be automated, designing and implementing solutions for those processes, and then providing ongoing support and maintenance after they’ve solved the issue.

What Companies Will Find in Years to Come

There are very few reasons that a company would choose not to outsource in 2023. Advancements in technology today (with an emphasis on Artificial Intelligence) and globalization have made it easier and more cost-effective for businesses to outsource various workflows, which include (but are not limited to) manufacturing, customer service, and IT support.

By outsourcing, companies can tap into a global pool of talent, access specialized expertise, and reduce operational costs. Outsourcing also allows businesses to focus on their core competencies and strategic goals, while leaving non-core functions to third-party providers which is something we’ve emphasized in previous articles but is certainly worth reiterating. 

Again, evaluating the end goal is the first step as that will dictate the necessary actions which businesses take to not only survive the new business landscape but to separate themselves from the competition so much that they cannot be replaced.

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.

5 of The Best Debugging Techniques

Your application, platform, or website relies on error-free code to ensure optimal performance and to provide an overall higher-quality end-user experience. If you neglect this, bugs will wreak havoc on your product and turn users off from it altogether. Though quality assurance testing is common practice during software development, developers still play a vital role in the debugging process. 

Debugging techniques vary by language and tool, yet there are many straightforward methods for developers when approaching the debugging process that can be applied to almost any software. In this article, we'll explore some of the most practical debugging techniques that programmers can use to enhance their software simply and effectively. In addition to this, we’ll look at 5 specific debuggers and what exactly they’re good for. 

How Can I Debug Easily?

When a programmer begins debugging, they are simply identifying and removing any defective code within the program. Although finding bugs is a crucial element of QA testing, it’s still just one part of a broader phase that entails verifying other aspects of quality, including usability and overall performance.

The reality of debugging “easily” is to think about the problem less from a technical aspect and more from a systematic approach. With that being said, here are 5 ways to get started:

1) Break The Issue Down Into Simple Questions:

The first step to debugging effectively is to define the issue at hand and ask yourself the simple yet important questions related to it. For example:

• What is the desired outcome of your program?

• How is your program currently functioning?

• What errors are you encountering?

• What past experiences have you had with similar problems? And what solutions from then may apply now?

• How many possible causes and locations of the bugs can you list?

Questions of this nature will lead the developer to form a theory about where to begin debugging and how to approach it logically.

2) How Do I Deal With Error Messages?

Though there is no feeling more gut-wrenching for a software developer than seeing an error message appear for the 3rd time, it’s the only way for them to realize what’s going wrong. So with that said, anytime an error message does appear, make sure you write down what’s wrong. By the same token, you can give it to Chat GPT, Visual Studio IntelliCode, or CodeSpace to get suggestions on how to solve the issue.

The fact remains that developers cannot ignore error messages or just hand them over to an AI to solve them. Getting suggestions from resources is a great first step and can speed up the debugging process - but attention to detail during software development is essential. 

3) Keep a Log

Branching off the previous point regarding writing down error messages, the key benefit of this method is that it’s great at identifying patterns/recurring issues. For example, take a developer who is integrating a REST API for a weather app but keeps getting the error message "404 Not Found" when trying to access the API endpoint to retrieve current weather data. 

The cause of this issue could be an incorrect endpoint URL or the API is simply unavailable or down. Either way, documenting the error and its details will make it easier for the developer to identify and address the problem. For instance, verifying the endpoint URL or seeking support from the API provider could be the best options when trying to resolve this issue. By logging that, the developer will be prepared should the issue happen again.

4) What About Debuggers?

A debugger can aid in pinpointing and fixing bugs in your code. These tools are also referred to as “debugging mode" or “debugging tool”. To take full advantage of a debugger, developers need to execute programming within it. This allows software developers to monitor it in real time and observe errors as they occur. By pausing the program while it's running, developers can identify and investigate the issues that are causing errors and then analyze the code line by line.

Some good debuggers include:

Visual Studio Debugger: This is a powerful and comprehensive debugger that is included with the Visual Studio IDE (Integrated Development Environment). It supports a variety of programming languages, including C++, C#, and Python, and even includes features such as step-by-step debugging, breakpoints, and data visualization.

GDB: This is a command-line debugger that is widely used in the Linux and Unix world. It supports a wide range of programming languages, including C, C++, and Fortran, and provides features such as breakpoints, watchpoints, as well as remote debugging.

Xcode Debugger: This is the debugger that is included with Apple's Xcode IDE. It supports programming languages such as Objective-C and Swift and also provides features such as source-level debugging, stack traces, and breakpoints (just as the last two do as well).

Eclipse Debugger: This is a debugger that is included with the Eclipse IDE. It supports multiple programming languages, including Java, C++, and Python, and offers features such as conditional breakpoints, expression evaluation, and remote debugging.

PyCharm Debugger: This is a debugger that is included with the PyCharm IDE for Python. It provides features such as step-by-step debugging, variable inspection, and remote debugging.

5) How Can a Developer Approach Debugging Logically?

It’s not unheard of for software developers to run into “analysis paralysis” when encountering issues with their code. For this reason, localizing the problem (line-by-line removal of code until the issue is found) is a great tool. Though it tends to be a tedious process, it can be the most efficient and effective way to solve the problem in some cases. 

Software testing, detecting, and addressing bugs before they disrupt the application is the foundation for a “logical” approach to debugging. While the QA team is responsible for thoroughly checking the product, developers should always perform simple tests during the development phase, such as unit testing, which may involve testing individual parts of the code, or units. 

Whatever the case may be, having a toolkit of simple debugging techniques is essential for creating and refining software, which ultimately leads to better products. Now, depending on the specific issues and situations encountered, some techniques may just be more suitable than others. However, top professionals would recommend that developers familiarize themselves with all of them to have a variety of tools available.

Summarizing Everything

Debugging is an essential part of building a sustainable software architecture. There are a variety of tools available to software developers today that can make this process much more efficient and effective. Software developers without debugging techniques are like a mechanic without a wrench. No matter how experienced or well-trained a software developer is, they will always run into errors and issues in their code which will lead to an unreliable and unsustainable software system. In a rapidly evolving digital landscape, debugging is paramount to ensuring that software systems are functioning as intended, and to prevent any issues that should arise from becoming bigger problems.

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.

10 Machine Learning Tools For API Integration

API integration sets up web services to process data in ways that benefit the UI/UX of an application or platform. It does so by allowing developers to leverage external APIs and Machine Learning (ML) techniques to enhance the functionality and usability of the software system. If/when they are leveraged, the software system will respond extremely well.

When examining the role that Machine Learning plays in API development - the key area to focus on is analytics and how applications use this to speed up product development. Machine Learning consists of algorithms and models that, when leveraged during API development, create a high-functioning data management and automation system. Now, the key variable to keep in mind here is the quality and quantity of data that the system has access to.

Processing Data

API development and integration are common practices when building a platform's back end, however, Machine Learning is still on the rise in terms of adoption. With that in mind, here are some of the benefits you can expect when combining ML algorithms with APIs:

• API provides a clean and well-defined interface for analytics

• API integrates easily with any application with a simple cURL command

• API endpoint remains the same even if the algorithm or input data changes

• API checks data and requests at the door for anything not corresponding to the specification, resulting in an error

• API separates the iterative world of data science from the world of IT and software

• Algorithms need frequent updates, software needs to be stable, reliable, and robust

• Data scientists can focus on building models without worrying about infrastructure

Many businesses run into problems when managing their data which include anything from quality issues with the data itself to errors when processing large quantities of data. This is where API and ML integration can be the saving grace - when automating data management processes, it results in the following:

• Cleaner and more structured data 

• The ability to predict and detect anomalies

• Provides personalized recommendations

• Automates repetitive tasks

• Manages large volumes of data with ease

Tools That Integrate Machine Learning Techniques 

We’ve looked at a few of the tools on this list but seldom have we taken a closer look at how they assist Machine Learning integration. Here are 10 tools that are great for this process:

1. H2O.ai: A Machine Learning platform that enables programmers to build and use large-scale Machine Learning models.

2. RapidMiner: A platform that allows developers to build predictive models and perform data analysis using Machine Learning algorithms.

3. Google Cloud AI Platform: A cloud-based platform that provides developers with tools to build, train, and deploy Machine Learning models.

4. TensorFlow: A Google-developed open-source platform that enables Machine Learning model creation and training.

5. Scikit-learn: A Python package that offers various data mining and analysis features, including Machine Learning techniques.

6. Keras: An advanced neural network API created in Python that can be used alongside TensorFlow.

7. PyTorch: A neural network development and training library that is open-source and based on the Torch library.

8. Microsoft Azure Machine Learning Studio: A cloud-based platform that allows developers to build, train, and deploy Machine Learning models.

9. Amazon SageMaker: A fully-managed platform that provides developers with the tools to build, train, and deploy Machine Learning models.

10. IBM Watson Studio: A cloud-based platform that also allows developers to build, train, and deploy Machine Learning models using various tools and services.

The main priority in mind when software developers integrate Machine Learning techniques with APIs is the flexibility and ease of integration on the back end. What this means is that the platform will be highly scalable, able to handle various data formats, and easily integrate with different programming languages as well as existing software frameworks. 

Developers often experience the temptation to expose an endpoint of the API to the code of the ML model but this does incur risk. When you maintain the separation of your model's code from that of the infrastructure, it allows the application to function in a more secure, reliable, and scalable manner. Whereas exposing endpoints can lead to error responses to requests and downtime of the endpoint. 

Going Forward With MLaaS (Machine Learning as a Service)

APIs provide programmers with a clear interface that organizes analytics and the application utilizing them which in turn speeds up the product development process and allows ML models to be used and reused across a variety of applications. With this, companies can expect to see a lot of change in their industry as the gold standard today calls for a strong digital strategy. In order to get ahead, businesses need to remain aware and begin strategizing before taking action.

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.