As we choose the right tech stack, we should take into account not the features or interconnectivity of the technology, as much as the context - the set of circumstances, in which the software will be working according to its demand.
In development, a tech stack refers to the set of technologies comprising programming languages, tools, frameworks, libraries, and related data management and processing programs. Having numerous choices makes it challenging to determine which tech stack is most suitable for a given project.
We’ll also discuss why context is so important when choosing a tech stack, and describe the best ways to use context to make smarter tech stack decisions. In the following blog post, we’ll discuss what a tech stack is and how your tech stack can affect your project – as well as why context matters in the decision-making process. I'm going to outline the guidelines in this blog post, which should apply to any software development project. But we also spend a bit of time on some life science and laboratory software, and that’s because that’s our area of expertise.
A stack is a vertical ‘stack’ of objects, one on top of the other. For us, “things” are the technologies for building, deploying, and operating software.
The tech stack typically comprises a programming language, a framework, libraries, databases, and all other necessary components for the application to be built and function properly.
What are platforms and operating systems? Considering that platforms and operating systems are the environments in which our program runs. They include desktop, mobile, and online tools. There are occasions when we can choose the platforms that will be used. However, target platforms are usually specified in requirements, especially for client-side software.
A programming language is a formal language used to write and design instructions that a computer can execute. They offer humans a way to express algorithms and logic in an approachable, human-readable manner that can be understood and executed by computers, and at a higher level of abstraction than the computer itself.
Databases are the warehouse of any tech stack, and are systematic collections of data that are processed, updated, and manipulated such that they can be retrieved and searched when required.
Frameworks are pre-established architectural constructs that serve as a basis for building reusable functionalities in software development. Predefined functionalities and libraries, as well as conventions present such libraries, ease and expedite the development process by providing a structure and a standard procedure. The frameworks themselves tend to ship with libraries related to the framework’s domain, and you can use this pre-packaged code to handle everyday tasks.
Libraries are bundles of programming code that are created to perform a specific task without the need to make them from scratch. Libraries involve shortening the coding process. Libraries are commonly used to cover more involved operations or provide components, so programmers do not need to re-invent the wheel.
Development tools are programs used to aid in software development, deployment, testing, and maintenance. These tools may include integrated development environments (IDEs), such as Visual Studio, debugging tools, profiling tools, project management tools, or version control systems, like Git.
Apps generally use a frontend and a backend tech stack when we're talking tech stack. The frontend tech stack refers to the application side that users interact with in a web application or website, specifically including user interface/user experience elements. The backend refers to the server-side processing of storage and data. Frontend and backend tech stacks are not separate for standalone apps.
The tech stack includes UI-related and business logic technologies. For standalone apps, use a database like SQLite or other options like MySQL or PostgreSQL.
Figure 1 shows the examples of all technologies for every layer of the tech stack. Because of these two different features, examples are separately arranged into two sections, for server-side and client-side. We also categorize the examples into web apps, mobile apps, and client-side apps on the client-side platform. It is not necessarily an exhaustive list.
The selection of the tech stack could determine the features and functionalities that can be provided in a project. For example, picking a particular programming language or framework may have consequences on how hard or easy it is to build features or integrate with specific systems. If your project is in Python, you can easily take advantage of the large number of data analysis and scientific computing libraries and frameworks. Formally, JavaScript, as the implementation language, enables providing seamless support for web browsers.
The tech stack, ofc can also affect the scalability of the project. Some technologies are better for working with traffic and data at scale, and others might not perform well with high volumes. Picking the best tech stack can help you scale the project and evolve with market demands well into the future.
In cases where the project is expected to handle a large amount of data, it requires horizontal scalability, which can be provided by a distributed database such as Apache Cassandra or MongoDB, which distributes data across multiple nodes. It enhances the capability to handle a high volume of data and perform read and write operations effectively.
Conversely, when you place a greater value on data integrity and complex queries than you do on horizontal scaling, a relational database such as PostgreSQL or MySQL -- which have powerful querying features -- may be a better option.
Some technologies may require more maintenance due to updates or patches, or when troubleshooting issues, particularly for small companies. It may influence the total expense and resources for maintaining the project smoothly.
A choice of technology stack can influence how well a project caters to various platforms (for example, operating systems or physical devices) in multiple ways. For instance, it can affect support for cross-platform development, access to platform APIs, development tools and environments, third-party libraries, and native API integration.
Desktop computers are the most frequently used computers in the laboratories. n Mobile devices (i.e., tablets, smartphones) are increasingly employed for data collection, instrument control, and communication.
The security of the project can also depend on the tech stack. Some technologies may be built to have stronger, more secure elements, or be designed to withstand attacks better more often.
Similarly, programming languages such as Rust, with its type systems and memory safety capabilities, can address frequent security hazards, including buffer overflows and injection attacks.
The price of the solution cannot avoid being affected by the tech stack you’ll decide upon for the implementation, as well as the tech stack that you are going to be using throughout the operation of the system. Technologies presented in scenarios could come with high licensing costs or be open-source and freely available. 3) Some technologies may require more niche skills or experience, which could increase the cost of development in general.
The good, the bad, and the ugly! In the software development world, news about the latest technologies, frameworks, programming languages, and libraries breaks out on a weekly, if not almost daily, basis. And each one claims to have solved developers’ issues and complaints, and that can sound tempting and interesting to try and see if it’s better for a project. However, when it comes to projects in production, we will want to adopt reliable, low-risk technologies that have the essential tooling needed in our development flow.
A widely used technology stack is also generally better documented, enjoys community support, and offers a larger ecosystem with libraries, plugins, and utilities. A larger community also means that you have a well of knowledge to tap into, especially when something goes wrong or needs to be fixed. Also, a popular tech stack will attract more good developers with experience working with this tech, and you are not going to have any problems hiring and building a team.
A good place to start is with the “developer survey” Stack Overflow now does annually, on popularity, where you can see how used some “things” are, how loved or deprecated some “things” are, and how many want to learn how to use a“thing”.
If you want to learn more about how to make good software, then we recommend that you read this article: Don’t Save on Quality: Essential Attributes of Good Software.
It’s easy… NOT!
Now, reading through the list, you might think it’s easy to select the tech stack: stick to technologies that are full of functionality, scalable, maintainable, multi-platform, and secure and economical.
But here are at least two reasons why it’s not that simple. First, trade-offs are made if a framework is easy to use, for example, where a framework lacks some features or security, or the framework is popular and does not support certain features or target platforms. Second, every project is unique, and, like most decisions, there is no universal prescription.
For starters, let’s make sure we know what the “context” is. Now that we have a good idea of what context is, let’s dive deeper into why it’s important and how we can use it to help us choose our tech stack.
Context, in general, is about the situation, weather, or environment in which something happens or exists.
When choosing a tech stack, the context refers to the specific situation and requirements that the software application must address. Factors that can be covered include the purpose of the app, the target audience, the allocated budget and timeline for release, the level of expertise of the software development team, the need for scalability and performance, as well as the readiness to acquire servers and APIs.
Very often, context plays a crucial role in guiding the selection of the appropriate tech stack, as it can serve as a lever to ascertain what this particular project truly needs, its limitations, and objectives. Use of proper Contexts and scene management to decide on the tech stack that would be aligned with the Project and then successfully executed within budget and timeline. Without context, the team could (and likely will) choose a tech stack that’s not a good fit for the project, which will result in time and money losses, and, in the worst-case scenario, a project collapse.
Begin by learning the project goals, objectives, and requirements. These may include factors such as expected application use cases, your audience, scalability, and performance requirements.
Lab software also has unique data security and privacy constraints that inform the choice of the tech stack. For instance, some users may prefer to take breaks from an internet connection or even forego the internet altogether.
Projects in the life sciences contain a vast amount of data, including patient data, clinical trial results, and genomic data, for example. The tech stack you decide on must be able to process this data effectively and securely.
Before we make any decisions, let’s see which of our tech stack compositions are pre-decided or non-changeable due to any technical limitations. These limitations may be due to hardware or software issues, or they may be related to compatibility with existing systems.
Some of the tech stack might already be chosen. For instance, let's say you're building a new system with an old database or even a new module for an old system. It is then essential to select a tech stack that is compatible with your current system. Consider widely used stacks (technologies) that have extensive resources and community support, as well as existing open-source libraries that can help minimize project costs.
Life science projects often require interfacing with other systems, such as electronic health records systems, laboratory information management systems, and clinical trial management systems. Opt for technologies that are interoperable and can be added to and incorporated into other systems. Once again, as with the most popular combinations, this can guide your search for the tech stack with the strongest support.
Compliance & Regulation Compliance and rules are a key factor in choosing a tech stack for a software project, and especially for a laboratory. There may be some regulations (such as FDA & GxP) that have to be considered.
Based on our previous points, you can prepare a list of potential technologies that provide all the required features for your project. However, there is one more critical aspect of the project context — the team that will build the software.
If the team already knows a particular programming language or framework, they can save time and money by working with it. Yet, if the team is unfamiliar with the tech stack, you may familiarize yourself with it or provide training to work with the discipline. What’s more, for large projects that involve niche skills such as machine learning or artificial intelligence, it may be more important to choose a tech stack that suits those needs, rather than one in which your team feels most comfortable.
The fact that sometimes you can only find out if a particular technology is suitable for your project if you try it. You may not be sure whether your chosen framework or library captures all the functionality required, and in an elegant way, for a specific feature, UI element, or database query. You don’t want to write a mass of custom code to weld the library to your usage: that’s a prime recipe for making a dog dinner very quickly.
The team will need to evaluate more than one tech stack and prototype it, testing it to ensure it fulfills the project's needs and is performant. You’ll also be able to distinguish the pros and cons, limitations, and trade-offs of the tech stack you choose, like ease of development, time to market, maintenance needs, performance, scalability, and costs.
It is where we’re going to end this article, highlighting the most essential part of choosing our tech stack. We also examined how to define a tech stack and software development projects, highlighting the importance of considering the project context.
When deciding, you must fully face the implications, which include project requirements, compliance, regulations, limitations, skills, and the quality of your development team.
Although deciding wisely early in the game is key, one should never lose sight of the possibility of change. New info can always come up that alters our decisions, and it’s hard at the beginning to account for everything.
With these factors in mind and achieving the right balance between being well-informed and flexible, you can set the stage for a productive tech stack selection process.
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