Top Technologies to Learn in Software Development in 2024

To know what are the top technologies to learn as software developers is a crucial habit to develop. Otherwise, the technologies take the market by storm and the learning curve will take time. Therefore we should try our best to be aware of the technologies we need in the market.

We don’t need to learn all of those technology areas in-depth but it’s important to at least know that they are becoming stronger. Our software development career might get some impact because of those major technology areas.

Java, Python, Javascript, GoLang, Kotlin

No matter what path you want to follow in your career as a software developer, it’s very important to be good in more than one language. By knowing more than one programming language we can expand our vision as programmers and become much better developers. To know one language deeply is awesome and as Java developers, we should definitely be Java specialists but it’s also very important to create personal projects with other programming languages.

If you try out another language you will find out amazing features that could be used in your favorite language. You will also realize that it’s possible to do pretty much the same thing with different languages but with a different style. By trying out different programming languages you will also learn that there is no silver bullet. You will learn the pros and cons of each programming language and will know which one to use for specific situations.

Let’s explore briefly each one of the languages:

Java: It’s a widely-used programming language, consistently the most popular language in the world, reliable, robust, mature, and secure (depending on how you code). Many programmers complain that Java is verbose. However, there is a great benefit to that, Java is a very expressive language, therefore, we know what is happening in the code. Java is in constant evolution also, from 6 to 6 months there is now a new Java version. Java has a very large community around the world and is very strong in the market.

Python: One of the main reasons why Python is popular in Data Science. Python is also very good for REST services, it’s reasonably easy to get started and there is plenty of support on the internet. According to the TIOBE list now Python is the most popular language, this is probably because Python is used in different areas of technology. For sure, a programming language is worth it to learn.

GoLang: It’s used for creating performant scripts, it’s possible to manipulate pointers with GoLang. It’s a simple language, easy to get started, and is also powerful for script creation for example. GoLang was created by a team on Google and it’s also open-source.

Kotlin: On the Kotlin website the language is defined as “A modern programming language that makes developers happier”. Kotlin is also a very close language to Java syntactically. Kotlin is also compiled with a Java Bytecode Virtual Machine. Therefore it’s a great language for Java developers to get started! If you want you can watch this amazing video from the great Venka, check it out:
Venkat Subramaniam: Kotlin for Java Programmers

Javascript: It’s a highly popular interpreted programming language, it can be used for many purposes, front-end and back-end. It’s a powerful language and it’s been gaining great traction. Javascript basically dominated front-end development, all the most popular front-end technologies are based on Javascript. Javascript is a language that allows the programmer to do too much though, it’s easy to get the code messy. Javascript is not typed, however, there is Typescript that enables us to use Javascript in a typed manner. If you are using Angular as your front-end technology, you will use Typescript for example.

You can mix your learning from new programming languages with algorithms, web project creation, and anything that is useful and fun to create!

You can also analyze the TIOBE list that has the popularity number of a programming language. Java is the language that stayed consistent through many years on the top. This time C is on the top, check it out:

If you want to explore it further, go directly to the source: Tiobe Index.

Java Frameworks/Stacks Quarkus & Spring

Quarkus is a stack created by Red Hat, it’s pretty recent and is gaining great traction in the market. With Quarkus, it’s possible to create lightweight Java applications and bootstrap an application in less than 500 milliseconds. Therefore, it’s possible to use Quarkus with Serverless technologies. Quarkus is also very mature, it has a vast range of libraries to use with it to handle data with NoSQL, secure an application, expose Rest endpoints, and so on. It’s also possible to use the amazing dev mode, which enables us to change the code with the server up and see the changes without having to restart the server, this is amazing isn’t it?

Spring is another giant player in the market, it’s used in Netflix for example. Netflix uses Spring to create its robust microservices reliably, and Spring does that gracefully. Spring has also a vast range of libraries, basically everything a developer needs. However, it’s not possible to use the dev mode from Quarkus. Starting a server with Spring also takes longer than Quarkus, it also consumes more memory. Spring is excellent for robust microservices applications but it’s not a silver bullet. For serverless, Spring is not good for the server startup time. For more information about Spring, check it out the following link: https://spring.io

DevOps

Most of the companies who develop enterprise software need their software to be delivered continuously with quality. Therefore, the DevOps culture grows more and more, and nowadays a company that doesn’t adopt it is considered obsolete. Technologies such as Jenkins, GitActions, Kubernetes, (Docker maybe), Ansible, Prometheus, Datadog, Hashcorp Vault, cloud providers, and scripting languages for automation are very important for this area.

In simple words, it’s possible to integrate and deliver software reliably through automation by using DevOps techniques. There is no need for manual processes where humans usually make mistakes. As you could see in the above-mentioned technologies, there is a vast range of technologies to be learned. Therefore, developers don’t need to go deep in all of them, instead, they should know how to solve problems with them. When it’s necessary to solve a more specific and difficult problem, a DevOps engineer should solve the problem.

Containers

In the cloud era, containers can’t be out of this list. Nowadays, it’s handy to containerize an application and move it wherever we want. With containers, the famous problem, “it works on my machine” doesn’t exist anymore. Technologies such as Kubernetes and Docker are still strong in the market. Even with the news that Kubernetes won’t support Docker anymore, Docker’s popularity won’t go away so easily.

Therefore, I believe Kubernetes and Docker are good bets of technology to learn. Both of them are powerful technologies. For software developers, Docker is still more important to learn and not as complex as the beast Kubernetes.

React, Angular and Vue

Most enterprise application has a front-end layer where the customer will interact with it. Therefore, knowing how to solve problems with React, Angular and Vue is a good advantage for your CV. You can create personal projects with those technologies and access REST endpoints created by the backend language you want to learn for example. It’s handy to do that as a hobby because you will get used to learning new things, and you will also have a project base. When you have an interview test where you need to create a project, it’s much easier for you if you already have a base project.

Let’s briefly introduce these three front-end technologies:

React: It’s a library extremely customizable and created by Facebook, this means that you can decide which library you will use for your own business necessities. It’s a component-based library as well written in Javascript. It’s quite easy to get started and it’s currently the most used front-end technology.

Angular: It’s a robust framework created by Google, and it’s vastly used in the market for mature applications. The good thing about Angular is that it’s possible to organize the code in different layers and divide the code into different responsibilities. The used language with Angular is Typescript which is a typed version of Javascript. It’s possible to make the code more reliable with Typescript. With Javascript on the other hand it’s very easy to see several different code patterns in the same project.

Vue: It’s a reactive front-end framework, the simplest of the front-end frameworks compared to React and Angular. Vue is easy to get started with and is also powerful. It’s possible to create robust applications with Vue. It’s also based on Javascript, therefore if you know Javascript you will be able to learn Vue more quickly.

Cloud Computing

Most companies nowadays are working with microservices. To make it happen, it’s necessary to deploy applications in the cloud. With cloud computing, it’s possible to scale systems quickly in small companies and use the infrastructure when necessary.

Currently, the most popular cloud provider is AWS (Amazon Web Services), therefore it’s a good technology to learn. As software developers, we don’t need to know a cloud provider very deeply but we should at least be able to deploy applications into it and know the main services.

There is a vast range of services on each cloud provider. To be able to learn a cloud provider more quickly, it’s important to know the network and Linux concepts. Because when we are working with cloud providers we deal with IP, DNS, servers, IP/Masks, subnets, internet gateway, and HTTPS protocols. In the cloud, we also use Linux servers most of the time, therefore learning and understanding Linux and command lines is crucial to be successful in the cloud.

Another big part of cloud providers that is already a strong tendency, is Serverless technology.  Serverless is practical and doesn’t require developers to know cloud technology deeply to deploy their applications. All modern languages have support for Serverless and it’s becoming more and more popular.

There are also other strong cloud providers such as Google Cloud, Azure, Oracle Cloud, and the list goes on.

Let’s see a graph showing which cloud provider is ahead:

If you want to go deeper into this subject you can access the following article:
Amazon Leads $100 Billion Cloud Market

Microservices Architecture

Microservices are already vastly adopted by many companies around the world.  The biggest trade-off to using microservices is vast complexity. That’s why companies have to consider more carefully whether it’s necessary to use microservices or not. Fortunately, companies are bit by bit understanding that microservices are not silver-bullet and they are using monoliths when it’s suitable.

When microservices came out, most developers were saying that monoliths were bad. Maybe this is just natural for developers, when something new comes out, we tend to become blind and only see what is new. Nowadays, developers are realizing that monolith is not bad, it’s still good depending on the project.

When we use microservices, we need to connect the dots between services. We need to monitor each microservice, we need to make sure the microservices are working, and the infrastructure complexity goes up high. Therefore when deciding to use microservices, make sure to have great DevOps engineers to make sure the infrastructure will be mature and will be scalable.

Along with the microservices architecture, there is the EDA (Event-Driven-Architecture) as well. The most popular EDA technology is Kafka which enables information to be exchanged more easily between microservices. Instead of having to use HTTP clients to connect microservices, we can create events that will be responsible for sending information reliably and effectively to other services. EDA also enables microservices to be less coupled. Instead of sending the information directly to the other microservice, Kafka has a broker that is responsible to orchestrate where messages will go.

In simple words, microservices are services usually separated by core modules from the business that should work isolated from the other services. Microservices shouldn’t depend on other services to work, databases should be also different for each service.

To conclude, microservices will keep strong in the market and will get more mature. Along with microservices, DevOps technologies will also become more demanding.

CyberSecurity

Since the infrastructure complexity dramatically increased, security also became complex. Therefore, engineers with security knowledge will have to be more and more technically prepared for the new challenges in the cloud.

To avoid cyber-attacks there is OWASP (Open Web Application Security Project) was founded in 2001 and is a community for developers who works to improve the security of software through led open-source software projects. There are also tools that scan security vulnerabilities such as Snyk, Vectrix, HP Fortify, and so on.

There are also popular tools in software development, such as Vault to store secrets, JWT, OAuth, and OpenID for Sigle-Sign-on applications authentication and authorization.

If you want to become a security specialist, you will have plenty of space in the market. There are even specialized AWS certifications to become a security specialist in the cloud. You can access the following link to explore more about the AWS certifications, certified security specialty.

Artificial Inteligence

Everyone is talking about artificial intelligence and this area doesn’t stop growing. I believe that in a short period of time there will be an era of robots where many jobs will be substituted by robots. People will have to adapt and figure out what to do instead since many will lose their jobs. Self-driving cars are another great example of artificial intelligence, it will soon be very popular.

According to Forbes, this is the growth prediction of artificial intelligence:

For more information check out the Forbes article here 10 Charts That Will Change Your Perspective On Artificial Intelligence’s Growth

Big Data

Hadoop, Cassandra, and Spark are very important technologies for Big Data. We consume tons of data in our day-to-day lives, we consume emails, watch many videos, and we leave our data in companies. Companies use our information to make customers more satisfied. With games, they collect information from the player to figure out where players pause or quit the game.

Big Data is also massively used by big companies such as Facebook, Google, Amazon, and Microsoft. Facebook collects our data to be able to show more precise advertising for us. Google also collects our information, sometimes it’s very obvious, after we say something, “magically” Google suggests what we said in the search bar. Google collects what we say, where we go, and what websites we access. Amazon collects our data for customer satisfaction, they have to know which product is going well, and others aren’t so that they can sell more.

It’s necessary to have Big Data also in hospitals, for example, it’s necessary to keep the patient information regarding their treatments. Currently, the global volume of data from 2013 to 2020  in healthcare is 2314 exabytes. If you don’t know how much is 1 exabyte, it’s equivalent to 1073741824 gigabytes!

Imagine how much data there is in the government! There has to have information on each citizen in the government database. Big data is also very useful to predict hurricanes, storms, and earthquakes. From the vast quantity of data that it’s possible to gather with big data, it’s also possible to make meaningful searches to collect important information.

Conclusion

As you can see, there is a vast range of technological tendencies. It’s important though to focus on what technology will give you the most benefits because if you try to learn everything you will learn nothing. Artificial intelligence for example is a vast area of technology, blockchain is another one. If you try to be good in all technologies at the same time, you will become like a duck who doesn’t fly or swim very well.

Therefore pick the technology you want to specialize in carefully and learn it deeply! Also, don’t forget to learn the technologies you need enough so you can solve problems because you will be expected to know that!

As always, be constantly breaking your own limits!