Over the past five years or so, serverless code has gained prominence. As both small and large cloud providers continue to upgrade their hardware, refine their tech stacks, and evolve their conceptual models, they're adding more languages to their lists of supported ones.
For me, context-switching can be exhausting. My thought process usually goes like this:
What's the objective?
How should I build it?
What approach is the most user-friendly, faster, and intuitive?
It's always a team effort—thinking for the present team and my future self.
Is it scalable?
Can it be automated?
Is it cost-effective and innovative?
I've had experience with Javascript, Java, Objective-C, AWS, Spark, CoreML, and Python. Interestingly, they all achieve similar objectives in comparable ways. We could delve into the distinctions between compiled and static languages versus native languages or discuss the concept of "write once, deploy everywhere." Another perspective to consider is coding based on necessity.
I'm fond of Swift because it eliminates many of the formalities found in other languages, spanning from scripting, data manipulation, and visualization to machine learning and serverless cloud applications. Most of this is open-source software that's currently in production.
Recently, I had the chance to contribute to a project that has undergone significant changes in the past three years: Swift AWS Lambda.
A sentiment many can understand is this: contributing voluntarily brings immense satisfaction.
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