What are the best practices for developing a cloud programming language?

Well, not everybody will develop a programming language, this is rather very special. As it will not be needed 1000 times, let's not start with "this is how you do it", rather with "what is missing from today's programming languages that could be improved in the cloud era."

I think, knowing the target environment where this program has to work is essential to understand the requirements, shortfalls that prevail with existing languages. At the end of the day, I think, no code or low code options will be of more interest to quickly get the business the competetive advantage by cutting down much time consuming development cycles.

I think the key points which definitely needs to be considered are: - Efficient for big tasks. - Resource-savvy for dynamic use. - Supports multitasking and asynchronous operations. - Prioritizes security for data protection. - Seamless integration with other cloud tools. - Handles large volumes of data effectively. - Robust error handling mechanisms. - Supports containerization (e.g., Docker) and orchestration (e.g., Kubernetes). - User-friendly design and simplicity. - DevOps integration for collaboration. - Cost-optimized resource usage. - Fosters a strong developer community. - Provides performance monitoring tools. - Adheres to industry rules and compliance. - Adaptable to evolving cloud trends.

In my experience, first thing for defining target domain is assess the common needs within the target domain. For example, for high-performance computing, I'd focus on optimizing the language for parallel processing and minimizing overheads that can impact performance. This might involve providing native support for common cloud computing patterns and ensuring compatibility with popular cloud platforms. By clearly defining the target domain and use cases, I can make informed decisions about the language's design

There is a large list of distributed programming languages that implement a range of paradigms. I'd be reviewing those in this context.

As per my experience, befor choosing any paradigm I would carefully consider the requirements of the target domain identified earlier to guide my choice of paradigm. For example, if the language is intended for high-performance cloud applications, a concurrent or distributed paradigm might be ideal. As a cloud consultant, My goal is always strike a balance between the expressiveness needed for the domain-specific tasks and the performance and scalability demands of cloud computing environments.

already the headings are wrong. We should start with questions like "how can we create a massively parallel programming lanugage that scales over thousands of nodes", "what's in it for the user", "how can we use preemptible machines and save the state of the program" and "how can we asynchronously process tasks, but come back at a syncpoint which would be when the function returns".

In determining the direction for a cloud programming language, precision is paramount. When selecting the paradigm and underlying model of computation, a thorough analysis of the target domain and language requirements is imperative. Consideration of paradigms such as functional, declarative, concurrent, and distributed, alongside models like actor, dataflow, lambda calculus, and logic programming, is essential. Striking the right balance ensures the language's expressiveness, performance, and usability align seamlessly with the demands of cloud programming.

HTML the ONLY programming language needed for cloud development! ?? Forget Python, Java, & JavaScript. HTML alone will power the future of the cloud. It's not just for web pages anymore; it's a full-stack revolution! #HTMLCloudTakeover #WhoNeedsRealCode"

If I have to develop cloud programming language then I would be careful that Syntax design should be clear, concise, and intuitive. And Semantics should be logical, predictable, and consistent with the syntax. This approach will help to create reliable, maintainable, and scalable cloud applications.

Designing the syntax and semantics of a programming language is a complex task that requires careful consideration of usability, expressiveness, and the specific goals of the language. Here, I'll provide a general outline of considerations for designing the syntax and semantics of a cloud programming language. Modularity Error Handling Domain-Specific Syntax Data Structures and Types Concurrency and Parallelism Constructs

From my point of view, the semantics of a language should be business-oriented. The code must be readable by everyone, even for those who are not yet familiar with it, we must ensure that everyone can contribute and review our code.

I'd make sure that cost is part of the language - cost constraint - cost reporting during execution - cost estimate of execution

I think, designing the syntax and semantics of a cloud programming language involves creating rules for writing and interpreting code. Here are some points that should be in the final checklist: Syntax Design: - Clarity and Consistency - Intuitiveness - Conciseness - Modularity - Error Handling - Standard Compliance Semantics Design: - Clear Interpretation - Meaningful Abstractions - Concurrency and Distribution - Resource Management - Scoping and Visibility - Interoperability - Documentation - Testing and Validation - Evolutionary Design Keeping clarity, consistency, and alignment with programming paradigms in focus, the design of syntax & semantics can result in a lang. that is both powerful and developer-friendly for cloud programming

"The compiler and runtime should also support the interoperability and compatibility of the code with other languages and platforms, and provide tools and libraries for debugging, testing, and monitoring." This sentence is not quite right. It would be better to explain this in more detail. What should be here is something along these lines. The compiler should provide the ability to produce compatible runtimes optimized for multiple platforms and operating systems. The compiler can produce runtimes with the appropriate hooks for real-time debugging, tracing, profiling, and verbose diagnostics. Libraries should be available to consume these hooks through user-friendly tooling.

Well... This includes many technical steps. But an overview of what could be the best approach is listed below: Compiler: - Master translation for cloud-ready executables. - Optimize for peak performance & scalability. - Prioritize interoperability & security. Runtime: - Efficiently execute cloud-based code. - Optimize for resource efficiency. - Support inter-language collaboration. - Integrate robust tooling for debugging, testing, and monitoring. - Ensure scalability for cloud demands. Again, it's hard to summarise everything in less than 750 chars, but this can be a good top level view for the same.

The final step in developing a cloud programming language involves implementing the compiler and runtime. The compiler translates the language's source code into executable code for the cloud platform, while the runtime provides the environment for this code to run. Both must be efficient, reliable, and secure, optimizing performance and scalability. Additionally, they should support interoperability with other languages and platforms and include tools for debugging, testing, and monitoring, ensuring smooth integration and maintenance in cloud environments.

Finalize development by implementing a robust compiler translating source code to executable cloud-ready code. Simultaneously, establish a reliable runtime for optimal execution. Prioritize efficiency, security, and interoperability, providing essential tools for debugging, testing, and monitoring.

I believe that once a language is put to test, it should cover almost all of the available cloud services, as there are many others that do so already. Moreover, enhancements should be made as soon as a new cloud service is available to a tenant.

More than implementing some improvement or evolution with respect to the current ones, what it should achieve is to make life easier for the developer, facilitate its use and understanding through good design and good syntax.

Evaluating and improving a cloud programming language is an essential ongoing process. It involves gathering feedback from users, developers, and researchers, using both qualitative and quantitative methods. This step aims to enhance the language's quality, usability, and usefulness while addressing any emerging issues or limitations. Additionally, it's crucial to keep the language updated with the latest trends and developments in cloud computing, ensuring it remains relevant and effective in an evolving technological landscape.

"The last but not the least practice for developing a cloud programming language is to evaluate and improve the language." This should be "first and foremost" rather than "last but not least." Programming languages not focused on improvement through qualitative and quantitative measures will wither and die quickly. One of the things that made the Go language so successful is the speed at which feedback is consumed and iterated by the Go developers.

Prioritize user feedback for satisfaction and usability. Establish comprehensive metrics, including performance and community engagement. Conduct practical usability tests and iterate based on feedback. Foster an inclusive community, enhance documentation clarity, and track and resolve issues transparently. Stay informed about industry trends, provide education and training, and ensure backward compatibility in updates. Conduct regular security audits, optimize performance, and communicate changes transparently. These practices ensure ongoing language improvement, user satisfaction, and alignment with industry advancements.

As we know, cloud environments are attractive targets for cyber threats. Because they are by default distributed and often involve handling sensitive data and critical applications. Therefore, I believe security considerations should be deeply integrated into every aspect of the language design. After all, security should be a core principle, not an afterthought.

Seems like AI generated topics here, Maybe once AI starts doing everything on its own in a dystopian future, it will invent something, for now, there's capabilities on existing languages to run on almost all hardware targets. But for anyone out there, creating a language is a very good way to learn compilers internals, and also harden ones language skills and mental models of how syntax gets translated to machine code etc.,

It may not be necessary, or even advantageous, to develop a language specific to cloud applications, since cloud applications often encompass a complex stack of compute, databases, storage, caching, networking, queueing, messaging. Instead I recommend utilizing existing languages while formulating meta frameworks for infrastructure deployment. There are already several cross platform frameworks for infrastructure definition, but there is still opportunity to develop highly intuitive open source frameworks that appeal to niche audiences.

Growing a community and ecosystem around a new language can be very hard. Hiring the right professionals is very difficult. Having the need and money to do so is a privilege to a drastic minority of companies. You probably shouldn't do it.

Adopt a simple, easy to learn programming paradigm. Most cloud-centric programming languages seem to be hypertext oriented or have highly developed libraries to handle this. Implement existing denominators. Conditional statements, loops, variable declarations etc. Identify the target cloud service for the language ie. IaaS, PaaS, SaaS etc. Your libraries should be extensive enough to handle OOP. The programming language should be able to accommodate various cloud architectures. The interoperability with the different architectural tiers also matter. Data is the gas of technology innovations. A data-first approach helps the language effectively handle data I/Os, considering that cloud systems work mostly with big data.