How can you use Go for cloud computing in FinTech?

In the Fintech landscape, what is important is high volume of payment processing, fraud detection. Golang is highly known for Concurrency and Performance. Go's concurrency model enables building stable, reliable and scalable systems that can serve numerous requests without any wait state.

Fintech implies you need to keep your system from losing or misplacing "valuable things" such as money and digital tokens, and to do this by construction. That is pretty much only possible by ensuring that your design stays the same even when its application becomes more complicated. And that is pretty much only possible with a very formal and mathematical approach to your programming. By default, Go does not give you that, but with care, and by staying within a very strict approach of design, such as by carefully combining higher order functional programming patterns, you can write Go that is robust by construction, and reliable enough for Fintech applications.

Once again, this question seems like it was generated by an LLM. Go(lang) runs anywhere you want to run it. The cloud is a nebulous idea that still includes servers and clients. IMO, Go(lang) is best suited for applications that need concurrency by default - as I understand it goroutines and simple syntax fill this requirement. If you run a Fintech and you need these features and your team likes writing go - Go for it. Make sure you have decent definitions of 'FinTech' and 'cloud computing' first...

It’s blend of C++ efficiency and Java’s easy to write , concurrency is easy to implement via routines and channels and gives flexibility to use pointers and plenty of standard libraries to work with cryptography , http and no sql database

Go also known as Golang, gained it's popularity for its simplicity, performance, and concurrency features. It has been increasingly adopted in various industries, including FinTech. It has several advantages for cloud computing, it offers concurrency and parallelism, performance, scalability, cloud-native development, and security. FinTech companies can leverage Go to build robust, scalable, and secure cloud-native applications that meet the stringent requirements of the financial services sector.

Debugging goroutines in Go can indeed present challenges, especially when dealing with concurrency-related issues. Due to the asynchronous nature of goroutines, traditional debugging techniques may not always provide clear insights into the root cause of problems.

Lack of generics like capability and few run time polymorphism and web sessions management are areas where I would like to see evolution

I would say, they should enhance the advanced libraries and dependency management so that they can improve the scope of using in Automation.

While Go may lack features like generics and traditional OOP, its strengths lie in simplicity, performance, and robust concurrency - pivotal for FinTech and cloud computing. Go's explicit error handling, though verbose, promotes transparency and reliability in mission-critical financial systems. Its interfaces and composition model offer pragmatic code reuse and extensibility. With a rich ecosystem, lightweight binaries, and built-in concurrency primitives, Go excels at building scalable, resilient, and performant cloud-native applications crucial for modern FinTech architectures.

The garbage collection and the not low-level system management can be a exluding characteristic for mission-critical or real-time systems.

- MVP for cloud products, no performance optimization requierement. - Cryptographic applications - Fast implementation of API

Go excels in cloud native development, enabling scalable microservices with its efficient concurrency and seamless Docker and Kubernetes integration. It's not just for backend; Go also powers CLI tools and web applications, thanks to its robust library and performance. A standout use case is blockchain in fintech, where Go's efficiency in transaction processing and network communication supports the demanding needs of decentralized finance. This versatility demonstrates Go's capability across various applications, debunking the myth that it's limited to specific domains.

This use case is for small startups only. Many apps don't store any data, they take data from the user and process and display the result. Those apps can be written in Go and delivered as executables(.exe), and users can use them from their desktops. This helps the user work offline. The company does not deploy and doesn't have to pay too much for cloud infrastructure. However, executables need to be pushed to some cloud storage like S3 to make it available for the user to download. Example : 1 . CD interest calculator 2 . Mortgage calculator 3. Amortization calculator 4. Excel calculators circulating among business users

GO is very versatile, cloud or onprem computing, the defacto simplicity, secured, library support make it stand for services.

Go's tooling and ecosystem are pivotal for FinTech cloud development. Tools like gofmt, go vet, and go mod streamline code formatting, linting, and dependency management - crucial for collaborative, maintainable codebases. Rigorous testing practices with unit, integration, and end-to-end tests, along with benchmarking, ensure code quality, performance, and reliability. Logging and tracing with packages like zap and OpenTelemetry enable comprehensive monitoring and debugging, indispensable for managing complex, distributed FinTech systems in the cloud.

Logging (zerolog), gin(for building REST apis),gomock, vet, golang-migrate, go coverage, go lint, swagger for documentation, sqlc/sqlx for db code generation, go-migrate and debugging using delve are some of the best practices that can be helpful for maintaining/debugging the codebase