What are the best programming languages for microservices?

Personally I prefer Java. Because I liked Java since it was born. Frameworks such as Spring makes it easy to build micro services in Java. But, it is possible to use many other languages as well. C# in dotNet environment can be a best alternative. There are other choices as well: Javascript/ nodejs, python and Google's golang. The important thing is not the language but the right choice of architecture while building micro services. One of my favourite pattern is CQRS - command query responsibility segregation - which helps us to optimise both read and write! Other important patterns are Saga (for orchestration of transaction across micro services), event driven architecture, strangular (helps us to migrate from monolith) etc,

In the microservices world, logical architecture is key which includes definition of boundaries and building services that do one thing well. This is technology agnostic and provides the ability to choose the right tool for each service without any dependency on one another. So the decision on tech stack depends on what that microservices is doing and not the architecture pattern being used.

In my recent role as a lead engineer, I spearheaded several projects centered around C# and .NET Core within a Microservices architecture. Given our organization's substantial investment in Microsoft technologies, leveraging C# emerged as a strategic choice due to its robust support for strong type checking, object-oriented programming, and modern language constructs align seamlessly with the principles of SOLID design. C# design patterns, when strategically applied, contribute to the creation of robust and adaptable Microservices. The inherent support for DI enhances modularity and testability with maintainable codebase. Furthermore, Domain-Driven Design (DDD) approach allowed us to fashion domain-rich, independent services.

The choice of programming language for microservices depends on various factors, including your team's expertise, the specific requirements of your project, and the characteristics of the microservices architecture. The recommended ones are: 1. Java: - Widely used in enterprise environments. - Offers strong support for building scalable and robust microservices. - Has a rich ecosystem and various frameworks like Spring Boot. 2. C# (with ASP.NET Core): - Suitable for building microservices on the Microsoft stack. - Integrates well with other Microsoft technologies. - ASP.NET Core provides a lightweight, modular framework.

Microservices are a software development approach that involves breaking applications into small, independent, manageable services. The choice of programming language for microservices depends on various factors like organization directions, team's expertise and the capabilities of the language to accommodate specific needs of the project.

Java and c# are good pick with good libraries to manage microservices, typescript is an option but not as robust as the other.

?? I once led a project with JavaScript, C#, and Python microservices on Azure. JavaScript handled real-time web features, C# for robust core services, and Python for data analysis. ?? The challenge? Harmonizing these different languages. JavaScript was agile but tricky with asynchronous events, C# was solid but complex to deploy, and Python's dynamic nature caused unexpected behaviors. Integrating them required meticulous debugging, using Azure's monitoring tools, and implementing strong error handling and communication protocols. ?? It was a journey of balancing the strengths and quirks of each language, resulting in a robust, well-integrated system and a team skilled in microservices architecture.

One of the strengths of microservices is also one of its weaknesses. Since each service is a separate deployment unit, you can theoretically pick the ideal language for each service. However, each language added to the mix increases the complexity of the system. You now need to stay up to date with security patches, language changes, and build processes for multiple languages. The number of languages used across microservices should be minimized. I’ve built systems that used Python in some services to access the data science/machine learning ecosystem and Go in other services that required better performance than that available through an interpreter. I see less of a case for using Java in some services and Go in others.

In microservices architecture, data management presents challenges due to the distributed nature of services and separate data stores. Challenges include ensuring data consistency across services, coordinating transactions, determining data ownership, and managing data synchronization and replication. Additionally, addressing data security concerns, implementing strategies for data versioning and evolution, and adopting best practices for data governance and monitoring are crucial. Clear architectural design decisions, effective data modeling, and the selection of appropriate technologies are essential for overcoming these challenges and ensuring the reliability and integrity of data in a microservices environment.

The inherent challenges are probably the different types of complexity in terms of: - monitoring and governance - delivery - debugging - architecture This does not mean that microservices are bad or good. They solve specific problems in a very good way. However, it is important to understand they have to be used in meaningful ways and when they make sense.

When selecting a programming language for microservices development, consider the following criteria: - Performance: The language should be efficient and performant to handle the demands of modern applications. - Scalability: The language should support horizontal scaling to accommodate increasing traffic and resource requirements. - Maturity: The language should have a mature ecosystem with a large community, extensive documentation, and available libraries. - Ease of Use: The language should be easy to learn, use, and maintain, reducing development effort and costs. - Interoperability: The language should be interoperable with other languages used in the microservices architecture.

It’s important to also consider: 1) skills on the team who will build and supporting the services 2) how the services will run 3) how the services will need to scale Choosing languages which are already being used in adjacent parts of the system enable the developers to build & troubleshoot across more of the stack. Some languages are multi-threaded, allow for more configurability or control over memory management which might be required for higher traffic systems, while others are easier to use but scale only horizontally and are less configurable. So, considering the existing skills and operational requirements is essential.

From an application architect view point, choosing a programming language for microservices should be based on the specific requirements of each service, avoiding a one-size-fits-all approach. Consider the trade-offs, development speed, scalability, and ecosystem support in the context of your project. Evaluate the unique characteristics of each language and its alignment with your architectural needs. Additionally, prioritize staying open to reevaluating choices as your project evolves, and new technologies emerge. This approach ensures that your microservices architecture remains tailored to the evolving demands of your project while maximizing developer productivity and system performance.

Other reasons I’ve selected languages: 1. Existing team language experience 2. Time to market requirements 3. Long term language viability 4. Language maturity 5. Pre-built framework options available 6. Infrastructure restrictions

The way we went about this is like, this is a multi-disciplinary decision, it involves considering the specific needs of the service, the best tool for the job, existing/planned skill sets of your team, security concerns, infra plans/sizing & cost. Additionally even in later stages of a product's growth, introducing a new software into the stack, poses challenges in security, protocols, compatibility & infra support. These are all solvable in the context of micro service framework, but in sometimes it may create more harm than good. Also mapping softwares(multi thread vs single thread) to pod effectively is crucial for optimizing performance and resource utilization. This is ongoing for us and are still learning a lot!!

In addition, you should select a language that is well suited to the application platform that the code will run on. For example, if you are writing a Lambda-backed micro service then you should choose a language that is memory efficient such as Go or python over a larger more complex object oriented runtime such as Java. Conversely, if you want to take advantage of a framework such as Spring, then Java in a container platform would be a better option.

Besides Java, Python Go and Node.js, you can also consider C++ and Rust, Kotlin, Ruby and .NET Core (C#). C++ and Rust: High-performance languages suitable for compute-intensive tasks and scenarios where low-level control is essential. Kotlin: Runs on the Java Virtual Machine (JVM) and is interoperable with Java. Offers modern features and concise syntax. Ruby: Known for its simplicity and developer-friendly syntax. Suitable for scenarios where development speed is a priority. .NET Core (C#):Microsoft's framework for building cross-platform applications. C# is well-suited for building microservices on the .NET platform.

Here are some tips for selecting the right programming language for your microservices project: 1. Consider the project's requirements: Evaluate the specific needs of your application, such as performance, scalability, and interoperability, to identify the most suitable language. 2. Assess team expertise: Choose a language that aligns with the skills and experience of your developers, ensuring a smooth development process. 3. Evaluate community support: Ensure there is a vibrant community around the chosen language, providing access to resources, libraries, and troubleshooting assistance. 4. Evaluate language maturity: Select a language with a long history and active development, ensuring stability and future support.

Any discussions among developers about languages can turn into religious wars. The right answer is generally the programming language your team is most comfortable with (assuming it's a modern language). Performance is always important, but the reality is that most modern languages have good to excellent performance, and unless you are building embedded systems or the like, the one your team is most familiar with will work fine. Hardware in the form of cloud compute is a LOT cheaper than software development these days. A caution with emerging languages like Go, Rust, and Elixir is the availability of libraries and docs is less than the more established Python, java, node, etc. But again, if this is what your team is most familiar with...

In my experience, some of the key facts in choosing a programming language are faster response, maintainability, version compatibility, long term security updates, community support, etc.

True story. I reached out to all the top educational centers in our city, delving into their teachings to understand which programming languages are gaining prominence among local developers. This research helped me to clarify for me that in the next 1 to 5 years, Python is expected to have a higher number of developers than any other language

This might seem "obvious" but it is good to keep the next points in mind: - global technical strategy of the team/company - technical debt - existing skills in the team/company - focus on creating value (in the end, the target is to create value with a good ROI; the technical aspect should "only" be a mean)

Redundancy and Reusability of the Microservice Code - Alongside choosing the right programming language, as a code writer, you must understand the redundancy and reusability of the shared code written in specific programming. - To make reusable code by applying loose coupling between the microservices and their modules where the supporting programming language selection will play a bigger role.