The article enlists the top 10 AIOps programming languages for developers to master in 2023
Artificial intelligence for IT Operations, usually known as AIOps is an application of AI, and related technologies, such as machine learning and natural language processing to traditional IT Ops activities and tasks. AIOps programming languages help Ops teams to tame the immense complexity and quantity of data generated by their modern IT environments, and thus prevent outages, maintain uptime and attain continuous service assurance. Top AIOps programming languages help organizations to operate at the speed that modern business requires, and deliver a stellar user experience. Through algorithmic analysis of IT data and Observability telemetry, AIOps programming languages help IT Ops, DevOps, and SRE teams work faster and more efficiently, so they can detect digital-service issues earlier and resolve them quickly, before business operations and customers are impacted. Here we have made a list of the ten best AIOps programming languages for 2023. Let us look into it:
Java by Oracle is one of the best programming languages available to learn. Over the years, java has adapted to the latest developments and technological advancements. The same is true for AIOps. Using Java for AIOps development can help you get some scalable applications. Java provides ease of usage and debugging and simplifies large-scale projects. You can represent the data in graphics and offer better user interaction.
Python is another programming language that provides the least code among all others. There are many reasons why we need to hire Python developers like it has prebuilt Libraries for advanced computing like Numpy, Scipy, and Pybrain. Also, it is an open-source language with support from developers from across the world. There are many Forums and Tutorials for Python that you can seek help from. There are options like Scripting, OOPs approach, and IDE that allows fast development with diverse algorithms. With all these features and many others, Python is considered one of the programming languages for AIOps development.
While Julia does not come with a large community or support, it offers many high-end features for top-notch AIOps development. When it comes to handling data analysis and numbers, Julia is the best development tool. With features like debugging, memory management, and metaprogramming, this language makes AIOps development a breeze.
Lisp is one of the oldest programming languages used for AIOps development. It was developed in the 1960s and has always been an adaptable and smart language. If your project requires modification of code, problem-solving, rapid prototyping, or dynamic development, Lisp is the best option for you. Some successful works of Lisp are Routinic, Grammarly, and DART.
Everyone is looking for high-performance, fast, and safe software development and Rust is a perfect option to achieve it. It is a general-purpose programming language that developers love to use for AIOps development. The syntax of Rust is similar to C++ but the former also offers memory safety and prevents garbage collection.
Scala is capable to make the coding process fast, easy, and much more productive. The index Scaladex that has the Scala libraries and resources helps developers to build some quality applications. It runs on the Java Virtual Machine (JVM) environment and helps developers to develop smart software. Scala is compatible with Java and JS and offers many features like pattern matching, high-performing functions, browser tools, and flexible interfaces.
While Haskell comes with limited support, it is another good AIOps programming language to be learned by developers for a bright future. It exhibits pure functionality and abstraction capabilities that make the language very flexible. However, the lack of support might delay the AIOps development process. It makes code reusability handy for the developers along with other features like type system and memory management.
R is a statistical programming language and is the first choice for projects where you need statistical computations. It supports learning libraries like MXNet, TensorFlow, Keras, etc. The language is adopted by many industries like education, finance, telecommunication, pharmaceuticals, life sciences, etc. It is the language that fuels tech giants like Microsoft, Google, Facebook, and businesses like Uber, Airbnb, etc.
Prolog is short for Programming in Logic. It was developed in 1972 in a rule-like form. It is majorly used for projects that involve computational linguistics and artificial intelligence. For projects that require a database, natural language processing, and symbolic reasoning, Prolog is the best programming language to go with. It is also used to build some high-end NLP applications by tech giants like IBM Watson.