Curated by: Sergio A. Martínez

This complexity is such, that according to Flexera’s 2021 State of IT Visibility report, “less than 25% of IT leaders have complete visibility into their IT estates”, which is a mind-blowing fact once we digest it properly; it means that up to 75% of our current IT environments have unknown areas that pose a challenge to the development and implementation of many software solutions.

But why does this happen? 

The truth is, organizations today are under the pressure to drive more value from IT investments, and as a result, leaders are always looking for ways to optimize their IT estates, creating a very specific challenge in today’s software development, creating a situation where a company has to choose between optimizing for licensing and optimizing for performance. And this is key for the success of any project.

Performance Vs. Licensing

“As leaders look for ways to optimize their IT estates, they are challenged with choosing between optimizing for licensing and optimizing for performance. Each one has implications for the other, and without a holistic approach, organizations must choose where to focus their efforts”, explains this article published by IBM. In short, an organization should look to integrate applications (that is, “optimizing for performance”); however, since most third-party software charges a licensing fee to use them at business level, carefully weighing options that fit within budget (or “optimizing for licensing”) could make or break a project.  

So while it is important to optimize your software options for performance, choosing the applications, platforms, or software that best suit your needs it’s also important, and a balance must be struck between the two, understanding the advantages and disadvantages they bring. On one hand, when optimizing for licensing, leaders need to consider the type of license that is best suited for their business needs, how many licenses they need, and how they can get the most from them. A license from a big corporation like Oracle, for example, can charge up to 22% of the total price in licensing, so having multiple ones without careful consideration can be quite a hit to the bank account.

On the other hand, when optimizing for performance, leaders need to focus on how they can improve the efficiency of their systems and make them more effective, making financial considerations less of a priority, although it’s rare when an organization can do this without immediate concerns. So to make the best decision, leaders need to carefully weigh options and choose the path that will help them meet their goals.

Controlling your IT states

“Traditional Software Asset Management (SAM) and IT Asset Management (ITAM) help organizations to understand where licenses are deployed, how software is being used, what versions of software are deployed, and if license use is compliant. This approach yields substantial benefits, but does not provide mechanisms to optimize on a continuous basis”, continues the aforementioned IBM article about some solutions currently implemented.

The thing is, current IT environments are so complex, that manual intervention is often required to understand a system holistically, especially when critical data gets ‘siloed’ in specific IT states, making it unlikely to have a complete view of the organization. After all, it’s easy for a growing company to look for solutions in the short term, and end with critical data concentrated in an external platform, creating issues to distribute it properly if it doesn’t play well with the rest of the IT environment. For example, cloud technology that might be challenging to troubleshoot if errors or other issues occur.

“What many [companies] don’t realize is that a software usage metering tool is just the first step, not the end-all and be-all, of managing these expensive software assets. The wide array of features and functionalities of software usage metering tools are only valuable if you know how to properly use them to accomplish your software license optimization goals.”

So to facilitate the task of implementing better automation into a processes, organizations need to be very smart about the tools, platforms, and systems they adopt into their IT environments, giving weight to the pros and cons of licensing a more uniform product, what the company is trying to accomplish product and/or service-wise, and the best way to achieve a good outcome.

“Combining license asset data and application performance data with intelligent automation gives IT leaders the visibility needed to optimize their IT estates while ensuring they remain in compliance”, concludes the IBM blog.

A solution in smart collaboration

As more and more organizations are outsourcing their IT needs to remain competitive, looking to optimize their spending and remain compliant with the license contracts without losing visibility into the entire IT estate, an answer can be found in Nearshore collaboration. With a Nearshore partner, an organization can gain visibility into their IT estate while optimizing their technology investments, getting the best of both worlds: the ability to remain compliant and the flexibility to optimize your technology investments.

This kind of collaboration can help simplify this systemic complexity by providing a single point of contact for all of their IT challenges by developing applications and products suited for their own context. The reason is that Nearshore development enables better collaboration between teams thanks to a close geographical location, and as a result, it’s a great way to combat the complexity of today’s IT environments. 

By working with a Nearshore partner, you can get the benefit of their expertise in managing complex deployments by making it easier to coordinate and manage projects, a great solution for companies that are looking to simplify their IT environment. The reality is that, as traditional workforces evolve, organizations to start investing in digital transformation efforts to keep up, and while the balance between licensing and performance is still an important consideration, choosing to develop internal tools and applications to reach a digital workplace is becoming more feasible thanks to the Nearshore model, which can help organizations fill skills gaps and reduce costs, 

However, it’s important to choose a partner that understands your culture and values, so while collaboration tools can help remote teams stay connected and aligned, they need to be used effectively. In other words, the workplace (as well as the IT environments that come along with it) is changing, and organizations need to be ready for it. So if you’re looking for a way to stay competitive in today’s digital world, and considering your options between optimizing and licensing, maybe Nearshore outsourcing is the answer you are looking for.

The Key Takeaways

• Choosing a software application to implement in your organization requires a careful balance between optimizing for performance and optimizing for licensing.
• Many of the bigger cloud-based service platforms can offer all the solutions you need, but the licensing costs, plus the risk of siloing information in an external system, could pose some issues in the long run.
• However, depending on your needs and the size of your organization, opting to develop custom solutions that hit a performance target without getting tangled in too many licensing issues is possible by collaborating with a Nearshore outsourcing company.

Scio is an established Nearshore software development company based in Mexico that specializes in providing high-quality, cost-effective technologies to help you reach new heights. We have been developing since 2003 and our experience gives us access not only to the knowledge but also the expertise needed when tackling any project. Get started today by contacting us about your project needs – we’ll be happy to help you achieve your business goals.

Curated by: Sergio A. Martínez

After all, Python has been the language of choice for many major technological projects in recent years, including Google’s App Engine, Instagram, and Pinterest, as well as being one of the most popular languages for teaching introductory computer science courses at various universities. It has even found applications in fields such as web development, scientific computing, and artificial intelligence, so given its versatility and widespread use, it’s no wonder that Python is often considered a basic skill among most developers around. 

However, is the excitement around Python warranted? You may already know that Python is praised for its readability and simplicity, often described as an «executable pseudocode,» which means that it’s easy for even non-programmers to understand, making it an ideal language for prototyping, or as a starting point for beginners.

In addition, it’s also open-source, meaning that anyone can contribute to its development (and keeps its already large library growing), so all this makes it a no-brainer when it comes to software development, but if we were to ask some actual developers about the good and bad sides to Python, maybe we can get insight on why this very dynamic (but sometimes confusing) language has earned its place in programming, so we asked Martín Ruiz and Elier Ramos, Application Developers at Scio with experience creating software with Python, to share their takes on this popular language.

What are the cool things about Python?

On one hand, Python is a very versatile programming language that offers many advantages to developers, perhaps the most notable being its readability. Thanks to its use of indentation and whitespace, Python code is often far easier for people to read and understand than code written in other languages, which saves valuable time when working on larger projects. In addition, Python is an interpreted language, which means that it doesn’t need to be compiled before it can be run. 

“I like the dynamism of Python. By being a higher leveled language than others like C, Java, or C#, it’s possible to develop the same kind of programs with briefer code”, says Martín. “It’s a multi-paradigm language where you don’t need to know OOP to generate programs capable of solving problems”.

The dynamism Martín mentions refers to, according to the words of the blog Data Towards Science, to a peculiar quality of this language, in which “to evaluate an expression, a compiler first searches the current block and then successively all the calling functions”. Additionally, even if the object-oriented features of Python are not as robust as those found in other languages, it still offers excellent support for it, making it a great choice to develop complex applications. 

“This language is widely used for mathematical simulation and data analysis, and it’s very focused on engineering, but it can also find a lot of applications to replicate what other languages can do, making it a sort of “all-in-one”, explains Elier.

Python also includes a large standard library that can be used to develop a wide range of applications, and with so many advantages, it’s no wonder that it has become one of the most popular programming languages in the world. However…

Some downsides to coding in Python

While Python is a versatile language with a wide variety of applications, it does have some well-documented disadvantages worth discussing. One potential downside, for example, is that Python code can be difficult to master, with a potentially confusing syntax due to its use of whitespace and indentation, which can make code written by more experienced programmers a challenge to understand. 

In addition, it’s not well suited for low-level tasks such as system programming or network programming, and Python’s interpreted nature can lead to slower execution times compared to languages like C++, which are compiled. Martin Ruiz, again explains some of its shortcomings:

“Since it’s more dynamic, and it doesn’t have as many restrictions as other languages, the developer is the one responsible for following good practices and documentation to achieve clean code. In other words, it’s a lot easier to generate illegible code with Python than with other languages, and it’s also more prone to generate errors thanks to this same dynamism. After all, the variables of Python can take any other value type.”

Furthermore, Python’s syntax, already somewhat difficult, is not consistent across all platforms, which can lead to compatibility issues, and the resulting code can be more difficult to debug and maintain, as well as having some structural issues that any seasoned developer must watch out for. In the words of Elier:

“Developing software with Python is very quick, but the design pattern and dependency injections can get lost very easily with this language. You can have way too many instanced things, and that gets hard to follow. I really wish the design patterns were more explicit in their instance and declaration.”

Additionally, the same popularity of Python makes finding experienced developers more difficult, as all big companies use it one way or another, reducing the available talent pool constantly. But despite these potential drawbacks, it remains a popular language for many types of projects due to its ease of use and wide range of libraries.

Final thoughts

“I started to learn Python during college, thanks to a teacher I worked with, building a system for a software conference. He used it for everything he developed, and it helped me a lot when I got my Master’s Degree because almost every teacher there used it”, explains Martín of his total experience with Python. “I would definitely add the optional use of keys to group code to make it more legible, though. And anyone willing to study this language should try to understand dynamic scoping to make full use of it, without taking the same approach as more structured languages such as Java or C#.”

So, taking it from an experienced Python developer, what this language offers is a “high risk / high reward” type of deal, where code in Python has to be very carefully constructed and documented to be maintained properly, but the results you get from it can be formidable. However, considering all this, is Python truly the code of the future? The same article for Data Towards Science sums it up:

“As we’re witnessing the shift from desktop to smartphone, it’s clear that we need robust languages to build mobile software. But Python wasn’t made with mobile in mind. So even though it might produce passable results for basic tasks, your best bet is to use a language that was created for mobile app development. […] To be clear, laptops and desktop computers should be around for many years to come. But since mobile has long surpassed desktop traffic, it’s safe to say that learning Python is not enough to become a seasoned all-around developer.”

So even with all these downsides, the continued popularity of Python in software development is still up in the air. Although this language has found its place in machine learning and web development, if you’re a seasoned programmer and want to stay ahead of the curve, you have it in your repertoire right now. It may be replaced one day by a newer language with better mobile support, but for now, it’s still the most popular option out there. And even if that does happen, maintaining the current Python-based software means it will remain a basic skill that every programmer needs to know. Dynamic or just very confusing, Python is an interesting language that is worth understanding.

Scio is a Nearshore software development company based in Mexico where we believe that everyone deserves everyone should have the opportunity to work in an environment where they feel like a part of something. A place to excel and unlock their full potential which is the best approach to create a better world. We have been collaborating with US-based clients since 2003, solving challenging programming puzzles, and in the process showcasing the skills of Latin American Engineers. Want to be part of Scio? Get in contact today!

Curated by: Sergio A. Martínez

Knowing this, and with the benefit of insight, we took a look into some of the predictions made way back in 2017, asking some of Scio’s leader, Luis Aburto, Rod Aburto y Adolfo Cruz, their thoughts about these technologies during the past five years, what they got right, and if some new developments could still await for us in the future. Enjoy!

Prediction 1: AI & Advanced Machine Learning

“It has definitely become popular”, Luis Aburto, CEO, and Co-founder of Scio, comments. “Applications like Jasper.io have advanced to a point where they are not toys anymore, but tools that a professional organization can rely on.” On the other hand, Adolfo Cruz, PMO Director, holds the opinion that this technology is still in its infancy. “There’s still a long road ahead. These programs are still unable to emulate the soul of many creative tasks. Maybe one day, but not very soon.” 

And in the case of software like the Applicant Tracking Systems we have talked about before, Luis still believes that AIs and Advanced Machine Learning are still not a “one-size-fits-all” solution. “These programs could work well in bigger companies that have an enormous amount of information to sift through, so an AI program could perform better in that case. But for medium companies like Scio or even smaller companies, human intervention keeps being preferable.” 

Prediction 2: Intelligent Apps

“Although they aren’t ubiquitous yet, applications like chatbots and virtual assistants have proven to be a valuable tool in many businesses”, comments Luis Aburto. “We are currently building a chat application along with one of our clients, and it’s an interesting challenge that will get more complex, but also more useful day by day. Someday, you’re probably not going to be talking to humans in any client service.”

Prediction 3: Digital Twinning

“Building a virtual mirror of a physical object is going to get big in manufacture and development of systems”, says Rod Aburto. “I know of business areas like airspace that can develop planes using the tons of data generated in each flight, gigabytes of information transmitted directly from the plane that could revolutionize the industry. In that sense, digital twinning might be a useful tool from now on, but I only see it in specific industries. Not much in the mainstream.” 

Prediction 4: Virtual and Augmented Reality

“I believe AR is still marching slowly. Maybe now with the Metaverse, they can jump forward, although I see more future in full virtual reality than AR”, says Luis. 

“And it’s still more of a plaything than anything else, without much in the way of practical applications”, adds Rod Aburto, referring to the current state of most popular AR uses. “At some point, it was said that doctors could do surgery at a distance with the help of this technology, but I see that as a very unlikely outcome.  

“Even Microsoft, with the big push of the Hololens, couldn’t really crack it”, continued Luis. “They sold some to the military and the like, but for the average person, it seemed more of a novelty than a truly groundbreaking tool. And the idea of everyone walking around with Google glasses, seeing augmented reality applications everywhere, is not really the future I expect.” 

Prediction 5: Blockchain

“Okay, that one is everywhere”, said Rod Aburto. “But not necessarily with their original purpose of being a public ledger audited by everyone. Their main application is still in cryptocurrency, and more as a financial gamble than anything else.”

“Although the future seems to lead to the so-called Web3, where the more transactional aspects of the blockchain become clearer”, intervenes Luis at the end. “Like the whole “digital ownership” concept of NFTs, I think that this technology still has many issues to solve, like how costly it is to make transactions and not to mention how slow it is for any practical purpose. But those things can only improve.” 

So what do you think? With all these technologies constantly growing and evolving, where will we be standing in five years’ time? Will some of these still be around as we know them, will they find new and exciting applications or something new will throw our predictions in an unexpected direction? Because one thing is sure: however the future shapes up, here at Scio we will be ready to help you explore new technological territories with the best talent in all of LATAM. Give us a call and let’s get started!

Scio is an established Nearshore software development company based in Mexico that specializes in providing high-quality, cost-effective technologies to help you reach new heights. We have been developing since 2003 and our experience gives us access not only to the knowledge but also the expertise needed when tackling any project. Get started today by contacting us about your project needs – we’ll be happy to help you achieve your business goals.